feat: add ollama support (#536)

feat(telemetry): Implement AI usage telemetry pattern and apply to ad…

.changeset/beige-doodles-type.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': patch
+---
+
+Resolve all issues related to MCP

.changeset/fifty-squids-wear.md

@@ -1,5 +0,0 @@
----
-"task-master-ai": patch
----
-
-Add CI for testing

.changeset/floppy-plants-marry.md

@@ -0,0 +1,9 @@
+---
+'task-master-ai': patch
+---
+
+Fix CLI --force flag for parse-prd command
+
+Previously, the --force flag was not respected when running `parse-prd`, causing the command to prompt for confirmation or fail even when --force was provided. This patch ensures that the flag is correctly passed and handled, allowing users to overwrite existing tasks.json files as intended.
+
+- Fixes #477

.changeset/forty-plums-stay.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': minor
+---
+
+.taskmasterconfig now supports a baseUrl field per model role (main, research, fallback), allowing endpoint overrides for any provider.

.changeset/free-bikes-smile.md

@@ -0,0 +1,11 @@
+---
+'task-master-ai': minor
+---
+
+Add Ollama as a supported AI provider.
+
+- You can now add it by running `task-master models --setup` and selecting it.
+- Ollama is a local model provider, so no API key is required.
+- Ollama models are available at `http://localhost:11434/api` by default.
+- You can change the default URL by setting the `OLLAMA_BASE_URL` environment variable or by adding a `baseUrl` property to the `ollama` model role in `.taskmasterconfig`.
+  - If you want to use a custom API key, you can set it in the `OLLAMA_API_KEY` environment variable.   

.changeset/many-wasps-sell.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': patch
+---
+
+Task Master no longer tells you to update when you're already up to date

.changeset/nice-lies-cover.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': patch
+---
+
+Adds costs information to AI commands using input/output tokens and model costs.

.changeset/pre.json

@@ -0,0 +1,23 @@
+{
+  "mode": "exit",
+  "tag": "rc",
+  "initialVersions": {
+    "task-master-ai": "0.13.2"
+  },
+  "changesets": [
+    "beige-doodles-type",
+    "floppy-plants-marry",
+    "forty-plums-stay",
+    "many-wasps-sell",
+    "red-oranges-attend",
+    "red-suns-wash",
+    "sharp-dingos-melt",
+    "six-cloths-happen",
+    "slow-singers-swim",
+    "social-masks-fold",
+    "soft-zoos-flow",
+    "ten-ways-mate",
+    "tricky-wombats-spend",
+    "wide-eyes-relax"
+  ]
+}

.changeset/red-lights-mix.md

@@ -1,5 +0,0 @@
----
-"task-master-ai": patch
----
-
-Fix github actions creating npm releases on next branch push

.changeset/red-oranges-attend.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': patch
+---
+
+Fix ERR_MODULE_NOT_FOUND when trying to run MCP Server

.changeset/red-suns-wash.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': patch
+---
+
+Add src directory to exports

.changeset/sharp-dingos-melt.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': patch
+---
+
+Fix the error handling of task status settings

.changeset/six-cloths-happen.md

@@ -0,0 +1,7 @@
+---
+'task-master-ai': patch
+---
+
+Remove caching layer from MCP direct functions for task listing, next task, and complexity report
+
+- Fixes issues users where having where they were getting stale data

.changeset/slow-singers-swim.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': patch
+---
+
+Fix for issue #409 LOG_LEVEL Pydantic validation error

.changeset/small-toys-fly.md

@@ -0,0 +1,7 @@
+---
+'task-master-ai': patch
+---
+
+Small fixes
+    - `next` command no longer incorrectly suggests that subtasks be broken down into subtasks in the CLI
+    - fixes the `append` flag so it properly works in the CLI

.changeset/social-masks-fold.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': minor
+---
+
+Display task complexity scores in task lists, next task, and task details views.

.changeset/soft-zoos-flow.md

@@ -0,0 +1,7 @@
+---
+'task-master-ai': patch
+---
+
+Fix initial .env.example to work out of the box
+
+- Closes #419

.changeset/ten-ways-mate.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': patch
+---
+
+Fix default fallback model and maxTokens in Taskmaster initialization

.changeset/tricky-wombats-spend.md

@@ -0,0 +1,5 @@
+---
+'task-master-ai': patch
+---
+
+Fix bug when updating tasks on the MCP server (#412)

.changeset/two-bats-smoke.md

@@ -1,302 +0,0 @@
----
-"task-master-ai": patch
----
-
-- Adjusts the MCP server invokation in the mcp.json we ship with `task-master init`. Fully functional now.
-- Rename the npx -y command. It's now `npx -y task-master-ai task-master-mcp`
-- Add additional binary alias: `task-master-mcp-server` pointing to the same MCP server script
-
-- **Significant improvements to model configuration:**
-  - Increase context window from 64k to 128k tokens (MAX_TOKENS=128000) for handling larger codebases
-  - Reduce temperature from 0.4 to 0.2 for more consistent, deterministic outputs
-  - Set default model to "claude-3-7-sonnet-20250219" in configuration
-  - Update Perplexity model to "sonar-pro" for research operations
-  - Increase default subtasks generation from 4 to 5 for more granular task breakdown
-  - Set consistent default priority to "medium" for all new tasks
-
-- **Clarify environment configuration approaches:**
-  - For direct MCP usage: Configure API keys directly in `.cursor/mcp.json`
-  - For npm package usage: Configure API keys in `.env` file
-  - Update templates with clearer placeholder values and formatting
-  - Provide explicit documentation about configuration methods in both environments
-  - Use consistent placeholder format "YOUR_ANTHROPIC_API_KEY_HERE" in mcp.json
-
-- Rename MCP tools to better align with API conventions and natural language in client chat:
-  - Rename `list-tasks` to `get-tasks` for more intuitive client requests like "get my tasks"
-  - Rename `show-task` to `get-task` for consistency with GET-based API naming conventions
-
-- **Refine AI-based MCP tool implementation patterns:**
-  - Establish clear responsibilities for direct functions vs MCP tools when handling AI operations
-  - Update MCP direct function signatures to expect `context = { session }` for AI-based tools, without `reportProgress`
-  - Clarify that AI client initialization, API calls, and response parsing should be handled within the direct function
-  - Define standard error codes for AI operations (`AI_CLIENT_ERROR`, `RESPONSE_PARSING_ERROR`, etc.)
-  - Document that `reportProgress` should not be used within direct functions due to client validation issues
-  - Establish that progress indication within direct functions should use standard logging (`log.info()`)
-  - Clarify that `AsyncOperationManager` should manage progress reporting at the MCP tool layer, not in direct functions
-  - Update `mcp.mdc` rule to reflect the refined patterns for AI-based MCP tools
-  - **Document and implement the Logger Wrapper Pattern:**
-    - Add comprehensive documentation in `mcp.mdc` and `utilities.mdc` on the Logger Wrapper Pattern
-    - Explain the dual purpose of the wrapper: preventing runtime errors and controlling output format
-    - Include implementation examples with detailed explanations of why and when to use this pattern
-    - Clearly document that this pattern has proven successful in resolving issues in multiple MCP tools
-    - Cross-reference between rule files to ensure consistent guidance
-  - **Fix critical issue in `analyze-project-complexity` MCP tool:**
-    - Implement proper logger wrapper in `analyzeTaskComplexityDirect` to fix `mcpLog[level] is not a function` errors
-    - Update direct function to handle both Perplexity and Claude AI properly for research-backed analysis
-    - Improve silent mode handling with proper wasSilent state tracking
-    - Add comprehensive error handling for AI client errors and report file parsing
-    - Ensure proper report format detection and analysis with fallbacks
-    - Fix variable name conflicts between the `report` logging function and data structures in `analyzeTaskComplexity`
-  - **Fix critical issue in `update-task` MCP tool:**
-    - Implement proper logger wrapper in `updateTaskByIdDirect` to ensure mcpLog[level] calls work correctly
-    - Update Zod schema in `update-task.js` to accept both string and number type IDs
-    - Fix silent mode implementation with proper try/finally blocks
-    - Add comprehensive error handling for missing parameters, invalid task IDs, and failed updates
-  - **Refactor `update-subtask` MCP tool to follow established patterns:**
-    - Update `updateSubtaskByIdDirect` function to accept `context = { session }` parameter
-    - Add proper AI client initialization with error handling for both Anthropic and Perplexity
-    - Implement the Logger Wrapper Pattern to prevent mcpLog[level] errors
-    - Support both string and number subtask IDs with appropriate validation
-    - Update MCP tool to pass session to direct function but not reportProgress
-    - Remove commented-out calls to reportProgress for cleaner code
-    - Add comprehensive error handling for various failure scenarios
-    - Implement proper silent mode with try/finally blocks
-    - Ensure detailed successful update response information
-  - **Fix issues in `set-task-status` MCP tool:**
-    - Remove reportProgress parameter as it's not needed
-    - Improve project root handling for better session awareness
-    - Reorganize function call arguments for setTaskStatusDirect
-    - Add proper silent mode handling with try/catch/finally blocks
-    - Enhance logging for both success and error cases
-  - **Refactor `update` MCP tool to follow established patterns:**
-    - Update `updateTasksDirect` function to accept `context = { session }` parameter
-    - Add proper AI client initialization with error handling
-    - Update MCP tool to pass session to direct function but not reportProgress
-    - Simplify parameter validation using string type for 'from' parameter
-    - Improve error handling for AI client errors
-    - Implement proper silent mode handling with try/finally blocks
-    - Use `isSilentMode()` function instead of accessing global variables directly
-  - **Refactor `expand-task` MCP tool to follow established patterns:**
-    - Update `expandTaskDirect` function to accept `context = { session }` parameter
-    - Add proper AI client initialization with error handling
-    - Update MCP tool to pass session to direct function but not reportProgress
-    - Add comprehensive tests for the refactored implementation
-    - Improve error handling for AI client errors
-    - Remove non-existent 'force' parameter from direct function implementation
-    - Ensure direct function parameters match core function parameters
-    - Implement proper silent mode handling with try/finally blocks
-    - Use `isSilentMode()` function instead of accessing global variables directly
-  - **Refactor `parse-prd` MCP tool to follow established patterns:**
-    - Update `parsePRDDirect` function to accept `context = { session }` parameter for proper AI initialization
-    - Implement AI client initialization with proper error handling using `getAnthropicClientForMCP`
-    - Add the Logger Wrapper Pattern to ensure proper logging via `mcpLog`
-    - Update the core `parsePRD` function to accept an AI client parameter
-    - Implement proper silent mode handling with try/finally blocks
-    - Remove `reportProgress` usage from MCP tool for better client compatibility
-    - Fix console output that was breaking the JSON response format
-    - Improve error handling with specific error codes
-    - Pass session object to the direct function correctly
-    - Update task-manager-core.js to export AI client utilities for better organization
-    - Ensure proper option passing between functions to maintain logging context
-
-- **Update MCP Logger to respect silent mode:**
-  - Import and check `isSilentMode()` function in logger implementation
-  - Skip all logging when silent mode is enabled
-  - Prevent console output from interfering with JSON responses
-  - Fix "Unexpected token 'I', "[INFO] Gene"... is not valid JSON" errors by suppressing log output during silent mode
-
-- **Refactor `expand-all` MCP tool to follow established patterns:**
-    - Update `expandAllTasksDirect` function to accept `context = { session }` parameter
-    - Add proper AI client initialization with error handling for research-backed expansion
-    - Pass session to direct function but not reportProgress in the MCP tool
-    - Implement directory switching to work around core function limitations
-    - Add comprehensive error handling with specific error codes
-    - Ensure proper restoration of working directory after execution
-    - Use try/finally pattern for both silent mode and directory management
-    - Add comprehensive tests for the refactored implementation
-
-- **Standardize and improve silent mode implementation across MCP direct functions:**
-  - Add proper import of all silent mode utilities: `import { enableSilentMode, disableSilentMode, isSilentMode } from 'utils.js'`
-  - Replace direct access to global silentMode variable with `isSilentMode()` function calls
-  - Implement consistent try/finally pattern to ensure silent mode is always properly disabled
-  - Add error handling with finally blocks to prevent silent mode from remaining enabled after errors
-  - Create proper mixed parameter/global silent mode check pattern: `const isSilent = options.silentMode || (typeof options.silentMode === 'undefined' && isSilentMode())`
-  - Update all direct functions to follow the new implementation pattern
-  - Fix issues with silent mode not being properly disabled when errors occur
-
-- **Improve parameter handling between direct functions and core functions:**
-  - Verify direct function parameters match core function signatures
-  - Remove extraction and use of parameters that don't exist in core functions (e.g., 'force')
-  - Implement appropriate type conversion for parameters (e.g., `parseInt(args.id, 10)`)
-  - Set defaults that match core function expectations
-  - Add detailed documentation on parameter matching in guidelines
-  - Add explicit examples of correct parameter handling patterns
-
-- **Create standardized MCP direct function implementation checklist:**
-  - Comprehensive imports and dependencies section
-  - Parameter validation and matching guidelines
-  - Silent mode implementation best practices
-  - Error handling and response format patterns
-  - Path resolution and core function call guidelines
-  - Function export and testing verification steps
-  - Specific issues to watch for related to silent mode, parameters, and error cases
-  - Add checklist to subtasks for uniform implementation across all direct functions
-
-- **Implement centralized AI client utilities for MCP tools:**
-  - Create new `ai-client-utils.js` module with standardized client initialization functions
-  - Implement session-aware AI client initialization for both Anthropic and Perplexity
-  - Add comprehensive error handling with user-friendly error messages
-  - Create intelligent AI model selection based on task requirements
-  - Implement model configuration utilities that respect session environment variables
-  - Add extensive unit tests for all utility functions
-  - Significantly improve MCP tool reliability for AI operations
-  - **Specific implementations include:**
-    - `getAnthropicClientForMCP`: Initializes Anthropic client with session environment variables
-    - `getPerplexityClientForMCP`: Initializes Perplexity client with session environment variables
-    - `getModelConfig`: Retrieves model parameters from session or fallbacks to defaults
-    - `getBestAvailableAIModel`: Selects the best available model based on requirements
-    - `handleClaudeError`: Processes Claude API errors into user-friendly messages
-  - **Updated direct functions to use centralized AI utilities:**
-    - Refactored `addTaskDirect` to use the new AI client utilities with proper AsyncOperationManager integration
-    - Implemented comprehensive error handling for API key validation, AI processing, and response parsing
-    - Added session-aware parameter handling with proper propagation of context to AI streaming functions
-    - Ensured proper fallback to process.env when session variables aren't available
-
-- **Refine AI services for reusable operations:**
-  - Refactor `ai-services.js` to support consistent AI operations across CLI and MCP
-  - Implement shared helpers for streaming responses, prompt building, and response parsing
-  - Standardize client initialization patterns with proper session parameter handling
-  - Enhance error handling and loading indicator management
-  - Fix process exit issues to prevent MCP server termination on API errors
-  - Ensure proper resource cleanup in all execution paths
-  - Add comprehensive test coverage for AI service functions
-  - **Key improvements include:**
-    - Stream processing safety with explicit completion detection
-    - Standardized function parameter patterns
-    - Session-aware parameter extraction with sensible defaults
-    - Proper cleanup using try/catch/finally patterns
-
-- **Optimize MCP response payloads:**
-  - Add custom `processTaskResponse` function to `get-task` MCP tool to filter out unnecessary `allTasks` array data
-  - Significantly reduce response size by returning only the specific requested task instead of all tasks
-  - Preserve dependency status relationships for the UI/CLI while keeping MCP responses lean and efficient
-
-- **Implement complete remove-task functionality:**
-  - Add `removeTask` core function to permanently delete tasks or subtasks from tasks.json
-  - Implement CLI command `remove-task` with confirmation prompt and force flag support
-  - Create MCP `remove_task` tool for AI-assisted task removal
-  - Automatically handle dependency cleanup by removing references to deleted tasks
-  - Update task files after removal to maintain consistency
-  - Provide robust error handling and detailed feedback messages
-
-- **Update Cursor rules and documentation:**
-  - Enhance `new_features.mdc` with comprehensive guidelines for implementing removal commands
-  - Update `commands.mdc` with best practices for confirmation flows and cleanup procedures
-  - Expand `mcp.mdc` with detailed instructions for MCP tool implementation patterns
-  - Add examples of proper error handling and parameter validation to all relevant rules
-  - Include new sections about handling dependencies during task removal operations
-  - Document naming conventions and implementation patterns for destructive operations
-  - Update silent mode implementation documentation with proper examples
-  - Add parameter handling guidelines emphasizing matching with core functions
-  - Update architecture documentation with dedicated section on silent mode implementation
-
-- **Implement silent mode across all direct functions:**
-  - Add `enableSilentMode` and `disableSilentMode` utility imports to all direct function files
-  - Wrap all core function calls with silent mode to prevent console logs from interfering with JSON responses
-  - Add comprehensive error handling to ensure silent mode is disabled even when errors occur
-  - Fix "Unexpected token 'I', "[INFO] Gene"... is not valid JSON" errors by suppressing log output
-  - Apply consistent silent mode pattern across all MCP direct functions
-  - Maintain clean JSON responses for better integration with client tools
-
-- **Implement AsyncOperationManager for background task processing:**
-  - Add new `async-manager.js` module to handle long-running operations asynchronously
-  - Support background execution of computationally intensive tasks like expansion and analysis
-  - Implement unique operation IDs with UUID generation for reliable tracking
-  - Add operation status tracking (pending, running, completed, failed)
-  - Create `get_operation_status` MCP tool to check on background task progress
-  - Forward progress reporting from background tasks to the client
-  - Implement operation history with automatic cleanup of completed operations
-  - Support proper error handling in background tasks with detailed status reporting
-  - Maintain context (log, session) for background operations ensuring consistent behavior
-
-- **Implement initialize_project command:**
-  - Add new MCP tool to allow project setup via integrated MCP clients
-  - Create `initialize_project` direct function with proper parameter handling
-  - Improve onboarding experience by adding to mcp.json configuration
-  - Support project-specific metadata like name, description, and version
-  - Handle shell alias creation with proper confirmation
-  - Improve first-time user experience in AI environments
-
-- **Refactor project root handling for MCP Server:**
-  - **Prioritize Session Roots**: MCP tools now extract the project root path directly from `session.roots[0].uri` provided by the client (e.g., Cursor).
-  - **New Utility `getProjectRootFromSession`**: Added to `mcp-server/src/tools/utils.js` to encapsulate session root extraction and decoding. **Further refined for more reliable detection, especially in integrated environments, including deriving root from script path and avoiding fallback to '/'.**
-  - **Simplify `findTasksJsonPath`**: The core path finding utility in `mcp-server/src/core/utils/path-utils.js` now prioritizes the `projectRoot` passed in `args` (originating from the session). Removed checks for `TASK_MASTER_PROJECT_ROOT` env var (we do not use this anymore) and package directory fallback. **Enhanced error handling to include detailed debug information (paths searched, CWD, server dir, etc.) and clearer potential solutions when `tasks.json` is not found.**
-  - **Retain CLI Fallbacks**: Kept `lastFoundProjectRoot` cache check and CWD search in `findTasksJsonPath` for compatibility with direct CLI usage.
-
-- Updated all MCP tools to use the new project root handling:
-  - Tools now call `getProjectRootFromSession` to determine the root.
-  - This root is passed explicitly as `projectRoot` in the `args` object to the corresponding `*Direct` function.
-  - Direct functions continue to use the (now simplified) `findTasksJsonPath` to locate `tasks.json` within the provided root.
-  - This ensures tools work reliably in integrated environments without requiring the user to specify `--project-root`.
-
-- Add comprehensive PROJECT_MARKERS array for detecting common project files (used in CLI fallback logic).
-- Improved error messages with specific troubleshooting guidance.
-- **Enhanced logging:**
-    - Indicate the source of project root selection more clearly.
-    - **Add verbose logging in `get-task.js` to trace session object content and resolved project root path, aiding debugging.**
-
-- DRY refactoring by centralizing path utilities in `core/utils/path-utils.js` and session handling in `tools/utils.js`.
-- Keep caching of `lastFoundProjectRoot` for CLI performance.
-
-- Split monolithic task-master-core.js into separate function files within direct-functions directory.
-- Implement update-task MCP command for updating a single task by ID.
-- Implement update-subtask MCP command for appending information to specific subtasks.
-- Implement generate MCP command for creating individual task files from tasks.json.
-- Implement set-status MCP command for updating task status.
-- Implement get-task MCP command for displaying detailed task information (renamed from show-task).
-- Implement next-task MCP command for finding the next task to work on.
-- Implement expand-task MCP command for breaking down tasks into subtasks.
-- Implement add-task MCP command for creating new tasks using AI assistance.
-- Implement add-subtask MCP command for adding subtasks to existing tasks.
-- Implement remove-subtask MCP command for removing subtasks from parent tasks.
-- Implement expand-all MCP command for expanding all tasks into subtasks.
-- Implement analyze-complexity MCP command for analyzing task complexity.
-- Implement clear-subtasks MCP command for clearing subtasks from parent tasks.
-- Implement remove-dependency MCP command for removing dependencies from tasks.
-- Implement validate-dependencies MCP command for checking validity of task dependencies.
-- Implement fix-dependencies MCP command for automatically fixing invalid dependencies.
-- Implement complexity-report MCP command for displaying task complexity analysis reports.
-- Implement add-dependency MCP command for creating dependency relationships between tasks.
-- Implement get-tasks MCP command for listing all tasks (renamed from list-tasks).
-- Implement `initialize_project` MCP tool to allow project setup via MCP client and radically improve and simplify onboarding by adding to mcp.json (e.g., Cursor).
-
-- Enhance documentation and tool descriptions:
-  - Create new `taskmaster.mdc` Cursor rule for comprehensive MCP tool and CLI command reference.
-  - Bundle taskmaster.mdc with npm package and include in project initialization.
-  - Add detailed descriptions for each tool's purpose, parameters, and common use cases.
-  - Include natural language patterns and keywords for better intent recognition.
-  - Document parameter descriptions with clear examples and default values.
-  - Add usage examples and context for each command/tool.
-  - **Update documentation (`mcp.mdc`, `utilities.mdc`, `architecture.mdc`, `new_features.mdc`, `commands.mdc`) to reflect the new session-based project root handling and the preferred MCP vs. CLI interaction model.**
-  - Improve clarity around project root auto-detection in tool documentation.
-  - Update tool descriptions to better reflect their actual behavior and capabilities.
-  - Add cross-references between related tools and commands.
-  - Include troubleshooting guidance in tool descriptions.
-  - **Add default values for `DEFAULT_SUBTASKS` and `DEFAULT_PRIORITY` to the example `.cursor/mcp.json` configuration.**
-
-- Document MCP server naming conventions in architecture.mdc and mcp.mdc files (file names use kebab-case, direct functions use camelCase with Direct suffix, tool registration functions use camelCase with Tool suffix, and MCP tool names use snake_case).
-- Update MCP tool naming to follow more intuitive conventions that better align with natural language requests in client chat applications.
-- Enhance task show view with a color-coded progress bar for visualizing subtask completion percentage.
-- Add "cancelled" status to UI module status configurations for marking tasks as cancelled without deletion.
-- Improve MCP server resource documentation with comprehensive implementation examples and best practices.
-- Enhance progress bars with status breakdown visualization showing proportional sections for different task statuses.
-- Add improved status tracking for both tasks and subtasks with detailed counts by status.
-- Optimize progress bar display with width constraints to prevent UI overflow on smaller terminals.
-- Improve status counts display with clear text labels beside status icons for better readability.
-- Treat deferred and cancelled tasks as effectively complete for progress calculation while maintaining visual distinction.
-- **Fix `reportProgress` calls** to use the correct `{ progress, total? }` format.
-- **Standardize logging in core task-manager functions (`expandTask`, `expandAllTasks`, `updateTasks`, `updateTaskById`, `updateSubtaskById`, `parsePRD`, `analyzeTaskComplexity`):**
-  - Implement a local `report` function in each to handle context-aware logging.
-  - Use `report` to choose between `mcpLog` (if available) and global `log` (from `utils.js`).
-  - Only call global `log` when `outputFormat` is 'text' and silent mode is off.
-  - Wrap CLI UI elements (tables, boxes, spinners) in `outputFormat === 'text'` checks.

.changeset/wide-eyes-relax.md

@@ -0,0 +1,11 @@
+---
+'task-master-ai': patch
+---
+
+Fix duplicate output on CLI help screen
+
+- Prevent the Task Master CLI from printing the help screen more than once when using `-h` or `--help`.
+- Removed redundant manual event handlers and guards for help output; now only the Commander `.helpInformation` override is used for custom help.
+- Simplified logic so that help is only shown once for both "no arguments" and help flag flows.
+- Ensures a clean, branded help experience with no repeated content.
+- Fixes #339

.cursor/mcp.json

@@ -1,19 +1,18 @@
 {
 	"mcpServers": {
-        "taskmaster-ai": {
+		"task-master-ai": {
 			"command": "node",
-            "args": [
-                "./mcp-server/server.js"
-            ],
+			"args": ["./mcp-server/server.js"],
 			"env": {
-                "ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE",
-                "PERPLEXITY_API_KEY": "YOUR_PERPLEXITY_API_KEY_HERE",
-                "MODEL": "claude-3-7-sonnet-20250219",
-                "PERPLEXITY_MODEL": "sonar-pro",
-                "MAX_TOKENS": 128000,
-                "TEMPERATURE": 0.2,
-                "DEFAULT_SUBTASKS": 5,
-                "DEFAULT_PRIORITY": "medium"
+				"ANTHROPIC_API_KEY": "ANTHROPIC_API_KEY_HERE",
+				"PERPLEXITY_API_KEY": "PERPLEXITY_API_KEY_HERE",
+				"OPENAI_API_KEY": "OPENAI_API_KEY_HERE",
+				"GOOGLE_API_KEY": "GOOGLE_API_KEY_HERE",
+				"XAI_API_KEY": "XAI_API_KEY_HERE",
+				"OPENROUTER_API_KEY": "OPENROUTER_API_KEY_HERE",
+				"MISTRAL_API_KEY": "MISTRAL_API_KEY_HERE",
+				"AZURE_OPENAI_API_KEY": "AZURE_OPENAI_API_KEY_HERE",
+				"OLLAMA_API_KEY": "OLLAMA_API_KEY_HERE"
 			}
 		}
 	}

.cursor/rules/ai_providers.mdc

@@ -0,0 +1,155 @@
+---
+description: Guidelines for managing Task Master AI providers and models.
+globs: 
+alwaysApply: false
+---
+# Task Master AI Provider Management
+
+This rule guides AI assistants on how to view, configure, and interact with the different AI providers and models supported by Task Master. For internal implementation details of the service layer, see [`ai_services.mdc`](mdc:.cursor/rules/ai_services.mdc).
+
+-   **Primary Interaction:**
+    -   Use the `models` MCP tool or the `task-master models` CLI command to manage AI configurations. See [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc) for detailed command/tool usage.
+
+-   **Configuration Roles:**
+    -   Task Master uses three roles for AI models:
+        -   `main`: Primary model for general tasks (generation, updates).
+        -   `research`: Model used when the `--research` flag or `research: true` parameter is used (typically models with web access or specialized knowledge).
+        -   `fallback`: Model used if the primary (`main`) model fails.
+    -   Each role is configured with a specific `provider:modelId` pair (e.g., `openai:gpt-4o`).
+
+-   **Viewing Configuration & Available Models:**
+    -   To see the current model assignments for each role and list all models available for assignment:
+        -   **MCP Tool:** `models` (call with no arguments or `listAvailableModels: true`)
+        -   **CLI Command:** `task-master models`
+    -   The output will show currently assigned models and a list of others, prefixed with their provider (e.g., `google:gemini-2.5-pro-exp-03-25`).
+
+-   **Setting Models for Roles:**
+    -   To assign a model to a role:
+        -   **MCP Tool:** `models` with `setMain`, `setResearch`, or `setFallback` parameters.
+        -   **CLI Command:** `task-master models` with `--set-main`, `--set-research`, or `--set-fallback` flags.
+    -   **Crucially:** When providing the model ID to *set*, **DO NOT include the `provider:` prefix**. Use only the model ID itself.
+        -   ✅ **DO:** `models(setMain='gpt-4o')` or `task-master models --set-main=gpt-4o`
+        -   ❌ **DON'T:** `models(setMain='openai:gpt-4o')` or `task-master models --set-main=openai:gpt-4o`
+    -   The tool/command will automatically determine the provider based on the model ID.
+
+-   **Setting Custom Models (Ollama/OpenRouter):**
+    -   To set a model ID not in the internal list for Ollama or OpenRouter:
+        -   **MCP Tool:** Use `models` with `set<Role>` and **also** `ollama: true` or `openrouter: true`.
+            -   Example: `models(setMain='my-custom-ollama-model', ollama=true)`
+            -   Example: `models(setMain='some-openrouter-model', openrouter=true)`
+        -   **CLI Command:** Use `task-master models` with `--set-<role>` and **also** `--ollama` or `--openrouter`.
+            -   Example: `task-master models --set-main=my-custom-ollama-model --ollama`
+            -   Example: `task-master models --set-main=some-openrouter-model --openrouter`
+        -   **Interactive Setup:** Use `task-master models --setup` and select the `Ollama (Enter Custom ID)` or `OpenRouter (Enter Custom ID)` options.
+    -   **OpenRouter Validation:** When setting a custom OpenRouter model, Taskmaster attempts to validate the ID against the live OpenRouter API.
+    -   **Ollama:** No live validation occurs for custom Ollama models; ensure the model is available on your Ollama server.
+
+-   **Supported Providers & Required API Keys:**
+    -   Task Master integrates with various providers via the Vercel AI SDK.
+    -   **API keys are essential** for most providers and must be configured correctly.
+    -   **Key Locations** (See [`dev_workflow.mdc`](mdc:.cursor/rules/dev_workflow.mdc) - Configuration Management):
+        -   **MCP/Cursor:** Set keys in the `env` section of `.cursor/mcp.json`.
+        -   **CLI:** Set keys in a `.env` file in the project root.
+    -   **Provider List & Keys:**
+        -   **`anthropic`**: Requires `ANTHROPIC_API_KEY`.
+        -   **`google`**: Requires `GOOGLE_API_KEY`.
+        -   **`openai`**: Requires `OPENAI_API_KEY`.
+        -   **`perplexity`**: Requires `PERPLEXITY_API_KEY`.
+        -   **`xai`**: Requires `XAI_API_KEY`.
+        -   **`mistral`**: Requires `MISTRAL_API_KEY`.
+        -   **`azure`**: Requires `AZURE_OPENAI_API_KEY` and `AZURE_OPENAI_ENDPOINT`.
+        -   **`openrouter`**: Requires `OPENROUTER_API_KEY`.
+        -   **`ollama`**: Might require `OLLAMA_API_KEY` (not currently supported) *and* `OLLAMA_BASE_URL` (default: `http://localhost:11434/api`). *Check specific setup.*
+
+-   **Troubleshooting:**
+    -   If AI commands fail (especially in MCP context):
+        1.  **Verify API Key:** Ensure the correct API key for the *selected provider* (check `models` output) exists in the appropriate location (`.cursor/mcp.json` env or `.env`).
+        2.  **Check Model ID:** Ensure the model ID set for the role is valid (use `models` listAvailableModels/`task-master models`).
+        3.  **Provider Status:** Check the status of the external AI provider's service.
+        4.  **Restart MCP:** If changes were made to configuration or provider code, restart the MCP server.
+
+## Adding a New AI Provider (Vercel AI SDK Method)
+
+Follow these steps to integrate a new AI provider that has an official Vercel AI SDK adapter (`@ai-sdk/<provider>`):
+
+1.  **Install Dependency:**
+    -   Install the provider-specific package:
+        ```bash
+        npm install @ai-sdk/<provider-name>
+        ```
+
+2.  **Create Provider Module:**
+    -   Create a new file in `src/ai-providers/` named `<provider-name>.js`.
+    -   Use existing modules (`openai.js`, `anthropic.js`, etc.) as a template.
+    -   **Import:**
+        -   Import the provider's `create<ProviderName>` function from `@ai-sdk/<provider-name>`.
+        -   Import `generateText`, `streamText`, `generateObject` from the core `ai` package.
+        -   Import the `log` utility from `../../scripts/modules/utils.js`.
+    -   **Implement Core Functions:**
+        -   `generate<ProviderName>Text(params)`:
+            -   Accepts `params` (apiKey, modelId, messages, etc.).
+            -   Instantiate the client: `const client = create<ProviderName>({ apiKey });`
+            -   Call `generateText({ model: client(modelId), ... })`.
+            -   Return `result.text`.
+            -   Include basic validation and try/catch error handling.
+        -   `stream<ProviderName>Text(params)`:
+            -   Similar structure to `generateText`.
+            -   Call `streamText({ model: client(modelId), ... })`.
+            -   Return the full stream result object.
+            -   Include basic validation and try/catch.
+        -   `generate<ProviderName>Object(params)`:
+            -   Similar structure.
+            -   Call `generateObject({ model: client(modelId), schema, messages, ... })`.
+            -   Return `result.object`.
+            -   Include basic validation and try/catch.
+    -   **Export Functions:** Export the three implemented functions (`generate<ProviderName>Text`, `stream<ProviderName>Text`, `generate<ProviderName>Object`).
+
+3.  **Integrate with Unified Service:**
+    -   Open `scripts/modules/ai-services-unified.js`.
+    -   **Import:** Add `import * as <providerName> from '../../src/ai-providers/<provider-name>.js';`
+    -   **Map:** Add an entry to the `PROVIDER_FUNCTIONS` map:
+        ```javascript
+        '<provider-name>': {
+            generateText: <providerName>.generate<ProviderName>Text,
+            streamText: <providerName>.stream<ProviderName>Text,
+            generateObject: <providerName>.generate<ProviderName>Object
+        },
+        ```
+
+4.  **Update Configuration Management:**
+    -   Open `scripts/modules/config-manager.js`.
+    -   **`MODEL_MAP`:** Add the new `<provider-name>` key to the `MODEL_MAP` loaded from `supported-models.json` (or ensure the loading handles new providers dynamically if `supported-models.json` is updated first).
+    -   **`VALID_PROVIDERS`:** Ensure the new `<provider-name>` is included in the `VALID_PROVIDERS` array (this should happen automatically if derived from `MODEL_MAP` keys).
+    -   **API Key Handling:**
+        -   Update the `keyMap` in `_resolveApiKey` and `isApiKeySet` with the correct environment variable name (e.g., `PROVIDER_API_KEY`).
+        -   Update the `switch` statement in `getMcpApiKeyStatus` to check the corresponding key in `mcp.json` and its placeholder value.
+        -   Add a case to the `switch` statement in `getMcpApiKeyStatus` for the new provider, including its placeholder string if applicable.
+    -   **Ollama Exception:** If adding Ollama or another provider *not* requiring an API key, add a specific check at the beginning of `isApiKeySet` and `getMcpApiKeyStatus` to return `true` immediately for that provider.
+
+5.  **Update Supported Models List:**
+    -   Edit `scripts/modules/supported-models.json`.
+    -   Add a new key for the `<provider-name>`.
+    -   Add an array of model objects under the provider key, each including:
+        -   `id`: The specific model identifier (e.g., `claude-3-opus-20240229`).
+        -   `name`: A user-friendly name (optional).
+        -   `swe_score`, `cost_per_1m_tokens`: (Optional) Add performance/cost data if available.
+        -   `allowed_roles`: An array of roles (`"main"`, `"research"`, `"fallback"`) the model is suitable for.
+        -   `max_tokens`: (Optional but recommended) The maximum token limit for the model.
+
+6.  **Update Environment Examples:**
+    -   Add the new `PROVIDER_API_KEY` to `.env.example`.
+    -   Add the new `PROVIDER_API_KEY` with its placeholder (`YOUR_PROVIDER_API_KEY_HERE`) to the `env` section for `taskmaster-ai` in `.cursor/mcp.json.example` (if it exists) or update instructions.
+
+7.  **Add Unit Tests:**
+    -   Create `tests/unit/ai-providers/<provider-name>.test.js`.
+    -   Mock the `@ai-sdk/<provider-name>` module and the core `ai` module functions (`generateText`, `streamText`, `generateObject`).
+    -   Write tests for each exported function (`generate<ProviderName>Text`, etc.) to verify:
+        -   Correct client instantiation.
+        -   Correct parameters passed to the mocked Vercel AI SDK functions.
+        -   Correct handling of results.
+        -   Error handling (missing API key, SDK errors).
+
+8.  **Documentation:**
+    -   Update any relevant documentation (like `README.md` or other rules) mentioning supported providers or configuration.
+
+*(Note: For providers **without** an official Vercel AI SDK adapter, the process would involve directly using the provider's own SDK or API within the `src/ai-providers/<provider-name>.js` module and manually constructing responses compatible with the unified service layer, which is significantly more complex.)*

.cursor/rules/ai_services.mdc

@@ -0,0 +1,102 @@
+---
+description: Guidelines for interacting with the unified AI service layer.
+globs: scripts/modules/ai-services-unified.js, scripts/modules/task-manager/*.js, scripts/modules/commands.js
+---
+
+# AI Services Layer Guidelines
+
+This document outlines the architecture and usage patterns for interacting with Large Language Models (LLMs) via Task Master's unified AI service layer (`ai-services-unified.js`). The goal is to centralize configuration, provider selection, API key management, fallback logic, and error handling.
+
+**Core Components:**
+
+*   **Configuration (`.taskmasterconfig` & [`config-manager.js`](mdc:scripts/modules/config-manager.js)):**
+    *   Defines the AI provider and model ID for different **roles** (`main`, `research`, `fallback`).
+    *   Stores parameters like `maxTokens` and `temperature` per role.
+    *   Managed via the `task-master models --setup` CLI command.
+    *   [`config-manager.js`](mdc:scripts/modules/config-manager.js) provides **getters** (e.g., `getMainProvider()`, `getParametersForRole()`) to access these settings. Core logic should **only** use these getters for *non-AI related application logic* (e.g., `getDefaultSubtasks`). The unified service fetches necessary AI parameters internally based on the `role`.
+    *   **API keys** are **NOT** stored here; they are resolved via `resolveEnvVariable` (in [`utils.js`](mdc:scripts/modules/utils.js)) from `.env` (for CLI) or the MCP `session.env` object (for MCP calls). See [`utilities.mdc`](mdc:.cursor/rules/utilities.mdc) and [`dev_workflow.mdc`](mdc:.cursor/rules/dev_workflow.mdc).
+
+*   **Unified Service (`ai-services-unified.js`):**
+    *   Exports primary interaction functions: `generateTextService`, `generateObjectService`. (Note: `streamTextService` exists but has known reliability issues with some providers/payloads).
+    *   Contains the core `_unifiedServiceRunner` logic.
+    *   Internally uses `config-manager.js` getters to determine the provider/model/parameters based on the requested `role`.
+    *   Implements the **fallback sequence** (e.g., main -> fallback -> research) if the primary provider/model fails.
+    *   Constructs the `messages` array required by the Vercel AI SDK.
+    *   Implements **retry logic** for specific API errors (`_attemptProviderCallWithRetries`).
+    *   Resolves API keys automatically via `_resolveApiKey` (using `resolveEnvVariable`).
+    *   Maps requests to the correct provider implementation (in `src/ai-providers/`) via `PROVIDER_FUNCTIONS`.
+    *   Returns a structured object containing the primary AI result (`mainResult`) and telemetry data (`telemetryData`). See [`telemetry.mdc`](mdc:.cursor/rules/telemetry.mdc) for details on how this telemetry data is propagated and handled.
+
+*   **Provider Implementations (`src/ai-providers/*.js`):**
+    *   Contain provider-specific wrappers around Vercel AI SDK functions (`generateText`, `generateObject`).
+
+**Usage Pattern (from Core Logic like `task-manager/*.js`):**
+
+1.  **Import Service:** Import `generateTextService` or `generateObjectService` from `../ai-services-unified.js`.
+    ```javascript
+    // Preferred for most tasks (especially with complex JSON)
+    import { generateTextService } from '../ai-services-unified.js';
+
+    // Use if structured output is reliable for the specific use case
+    // import { generateObjectService } from '../ai-services-unified.js';
+    ```
+
+2.  **Prepare Parameters:** Construct the parameters object for the service call.
+    *   `role`: **Required.** `'main'`, `'research'`, or `'fallback'`. Determines the initial provider/model/parameters used by the unified service.
+    *   `session`: **Required if called from MCP context.** Pass the `session` object received by the direct function wrapper. The unified service uses `session.env` to find API keys.
+    *   `systemPrompt`: Your system instruction string.
+    *   `prompt`: The user message string (can be long, include stringified data, etc.).
+    *   (For `generateObjectService` only): `schema` (Zod schema), `objectName`.
+
+3.  **Call Service:** Use `await` to call the service function.
+    ```javascript
+    // Example using generateTextService (most common)
+    try {
+        const resultText = await generateTextService({
+            role: useResearch ? 'research' : 'main', // Determine role based on logic
+            session: context.session, // Pass session from context object
+            systemPrompt: "You are...",
+            prompt: userMessageContent
+        });
+        // Process the raw text response (e.g., parse JSON, use directly)
+        // ...
+    } catch (error) {
+        // Handle errors thrown by the unified service (if all fallbacks/retries fail)
+        report('error', `Unified AI service call failed: ${error.message}`);
+        throw error;
+    }
+
+    // Example using generateObjectService (use cautiously)
+    try {
+        const resultObject = await generateObjectService({
+            role: 'main',
+            session: context.session,
+            schema: myZodSchema,
+            objectName: 'myDataObject',
+            systemPrompt: "You are...",
+            prompt: userMessageContent
+        });
+        // resultObject is already a validated JS object
+        // ...
+    } catch (error) {
+        report('error', `Unified AI service call failed: ${error.message}`);
+        throw error;
+    }
+    ```
+
+4.  **Handle Results/Errors:** Process the returned text/object or handle errors thrown by the unified service layer.
+
+**Key Implementation Rules & Gotchas:**
+
+*   ✅ **DO**: Centralize **all** LLM calls through `generateTextService` or `generateObjectService`.
+*   ✅ **DO**: Determine the appropriate `role` (`main`, `research`, `fallback`) in your core logic and pass it to the service.
+*   ✅ **DO**: Pass the `session` object (received in the `context` parameter, especially from direct function wrappers) to the service call when in MCP context.
+*   ✅ **DO**: Ensure API keys are correctly configured in `.env` (for CLI) or `.cursor/mcp.json` (for MCP).
+*   ✅ **DO**: Ensure `.taskmasterconfig` exists and has valid provider/model IDs for the roles you intend to use (manage via `task-master models --setup`).
+*   ✅ **DO**: Use `generateTextService` and implement robust manual JSON parsing (with Zod validation *after* parsing) when structured output is needed, as `generateObjectService` has shown unreliability with some providers/schemas.
+*   ❌ **DON'T**: Import or call anything from the old `ai-services.js`, `ai-client-factory.js`, or `ai-client-utils.js` files.
+*   ❌ **DON'T**: Initialize AI clients (Anthropic, Perplexity, etc.) directly within core logic (`task-manager/`) or MCP direct functions.
+*   ❌ **DON'T**: Fetch AI-specific parameters (model ID, max tokens, temp) using `config-manager.js` getters *for the AI call*. Pass the `role` instead.
+*   ❌ **DON'T**: Implement fallback or retry logic outside `ai-services-unified.js`.
+*   ❌ **DON'T**: Handle API key resolution outside the service layer (it uses `utils.js` internally).
+*   ⚠️ **generateObjectService Caution**: Be aware of potential reliability issues with `generateObjectService` across different providers and complex schemas. Prefer `generateTextService` + manual parsing as a more robust alternative for structured data needs.

.cursor/rules/architecture.mdc

@@ -3,7 +3,6 @@ description: Describes the high-level architecture of the Task Master CLI applic
 globs: scripts/modules/*.js
 alwaysApply: false
 ---
-
 # Application Architecture Overview
 
 - **Modular Structure**: The Task Master CLI is built using a modular architecture, with distinct modules responsible for different aspects of the application. This promotes separation of concerns, maintainability, and testability.
@@ -14,148 +13,75 @@ alwaysApply: false
     - **Purpose**: Defines and registers all CLI commands using Commander.js.
     - **Responsibilities** (See also: [`commands.mdc`](mdc:.cursor/rules/commands.mdc)):
       - Parses command-line arguments and options.
-      - Invokes appropriate functions from other modules to execute commands.
-      - Handles user input and output related to command execution.
-      - Implements input validation and error handling for CLI commands.
-    - **Key Components**:
-      - `programInstance` (Commander.js `Command` instance): Manages command definitions.
-      - `registerCommands(programInstance)`: Function to register all application commands.
-      - Command action handlers: Functions executed when a specific command is invoked.
+      - Invokes appropriate core logic functions from `scripts/modules/`.
+      - Handles user input/output for CLI.
+      - Implements CLI-specific validation.
 
-  - **[`task-manager.js`](mdc:scripts/modules/task-manager.js): Task Data Management**
-    - **Purpose**: Manages task data, including loading, saving, creating, updating, deleting, and querying tasks.
+  - **[`task-manager.js`](mdc:scripts/modules/task-manager.js) & `task-manager/` directory: Task Data & Core Logic**
+    - **Purpose**: Contains core functions for task data manipulation (CRUD), AI interactions, and related logic.
     - **Responsibilities**:
-      - Reads and writes task data to `tasks.json` file.
-      - Implements functions for task CRUD operations (Create, Read, Update, Delete).
-      - Handles task parsing from PRD documents using AI.
-      - Manages task expansion and subtask generation.
-      - Updates task statuses and properties.
-      - Implements task listing and display logic.
-      - Performs task complexity analysis using AI.
-    - **Key Functions**:
-      - `readTasks(tasksPath)` / `writeTasks(tasksPath, tasksData)`: Load and save task data.
-      - `parsePRD(prdFilePath, outputPath, numTasks)`: Parses PRD document to create tasks.
-      - `expandTask(taskId, numSubtasks, useResearch, prompt, force)`: Expands a task into subtasks.
-      - `setTaskStatus(tasksPath, taskIdInput, newStatus)`: Updates task status.
-      - `listTasks(tasksPath, statusFilter, withSubtasks)`: Lists tasks with filtering and subtask display options.
-      - `analyzeComplexity(tasksPath, reportPath, useResearch, thresholdScore)`: Analyzes task complexity.
+      - Reading/writing `tasks.json`.
+      - Implementing functions for task CRUD, parsing PRDs, expanding tasks, updating status, etc.
+      - **Delegating AI interactions** to the `ai-services-unified.js` layer.
+      - Accessing non-AI configuration via `config-manager.js` getters.
+    - **Key Files**: Individual files within `scripts/modules/task-manager/` handle specific actions (e.g., `add-task.js`, `expand-task.js`).
 
   - **[`dependency-manager.js`](mdc:scripts/modules/dependency-manager.js): Dependency Management**
-    - **Purpose**: Manages task dependencies, including adding, removing, validating, and fixing dependency relationships.
-    - **Responsibilities**:
-      - Adds and removes task dependencies.
-      - Validates dependency relationships to prevent circular dependencies and invalid references.
-      - Fixes invalid dependencies by removing non-existent or self-referential dependencies.
-      - Provides functions to check for circular dependencies.
-    - **Key Functions**:
-      - `addDependency(tasksPath, taskId, dependencyId)`: Adds a dependency between tasks.
-      - `removeDependency(tasksPath, taskId, dependencyId)`: Removes a dependency.
-      - `validateDependencies(tasksPath)`: Validates task dependencies.
-      - `fixDependencies(tasksPath)`: Fixes invalid task dependencies.
-      - `isCircularDependency(tasks, taskId, dependencyChain)`: Detects circular dependencies.
+    - **Purpose**: Manages task dependencies.
+    - **Responsibilities**: Add/remove/validate/fix dependencies.
 
   - **[`ui.js`](mdc:scripts/modules/ui.js): User Interface Components**
-    - **Purpose**: Handles all user interface elements, including displaying information, formatting output, and providing user feedback.
-    - **Responsibilities**:
-      - Displays task lists, task details, and command outputs in a formatted way.
-      - Uses `chalk` for colored output and `boxen` for boxed messages.
-      - Implements table display using `cli-table3`.
-      - Shows loading indicators using `ora`.
-      - Provides helper functions for status formatting, dependency display, and progress reporting.
-      - Suggests next actions to the user after command execution.
-    - **Key Functions**:
-      - `displayTaskList(tasks, statusFilter, withSubtasks)`: Displays a list of tasks in a table.
-      - `displayTaskDetails(task)`: Displays detailed information for a single task.
-      - `displayComplexityReport(reportPath)`: Displays the task complexity report.
-      - `startLoadingIndicator(message)` / `stopLoadingIndicator(indicator)`: Manages loading indicators.
-      - `getStatusWithColor(status)`: Returns status string with color formatting.
-      - `formatDependenciesWithStatus(dependencies, allTasks, inTable)`: Formats dependency list with status indicators.
+    - **Purpose**: Handles CLI output formatting (tables, colors, boxes, spinners).
+    - **Responsibilities**: Displaying tasks, reports, progress, suggestions.
 
-  - **[`ai-services.js`](mdc:scripts/modules/ai-services.js) (Conceptual): AI Integration**
-    - **Purpose**:  Abstracts interactions with AI models (like Anthropic Claude and Perplexity AI) for various features. *Note: This module might be implicitly implemented within `task-manager.js` and `utils.js` or could be explicitly created for better organization as the project evolves.*
-    - **Responsibilities**:
-      - Handles API calls to AI services.
-      - Manages prompts and parameters for AI requests.
-      - Parses AI responses and extracts relevant information.
-      - Implements logic for task complexity analysis, task expansion, and PRD parsing using AI.
-    - **Potential Functions**:
-      - `getAIResponse(prompt, model, maxTokens, temperature)`: Generic function to interact with AI model.
-      - `analyzeTaskComplexityWithAI(taskDescription)`: Sends task description to AI for complexity analysis.
-      - `expandTaskWithAI(taskDescription, numSubtasks, researchContext)`: Generates subtasks using AI.
-      - `parsePRDWithAI(prdContent)`: Extracts tasks from PRD content using AI.
+  - **[`ai-services-unified.js`](mdc:scripts/modules/ai-services-unified.js): Unified AI Service Layer**
+    - **Purpose**: Centralized interface for all LLM interactions using Vercel AI SDK.
+    - **Responsibilities** (See also: [`ai_services.mdc`](mdc:.cursor/rules/ai_services.mdc)):
+      - Exports `generateTextService`, `generateObjectService`.
+      - Handles provider/model selection based on `role` and `.taskmasterconfig`.
+      - Resolves API keys (from `.env` or `session.env`).
+      - Implements fallback and retry logic.
+      - Orchestrates calls to provider-specific implementations (`src/ai-providers/`).
+    - Telemetry data generated by the AI service layer is propagated upwards through core logic, direct functions, and MCP tools. See [`telemetry.mdc`](mdc:.cursor/rules/telemetry.mdc) for the detailed integration pattern.
 
-  - **[`utils.js`](mdc:scripts/modules/utils.js): Utility Functions and Configuration**
-    - **Purpose**: Provides reusable utility functions and global configuration settings used across the **CLI application**.
+  - **[`src/ai-providers/*.js`](mdc:src/ai-providers/): Provider-Specific Implementations**
+    - **Purpose**: Provider-specific wrappers for Vercel AI SDK functions.
+    - **Responsibilities**: Interact directly with Vercel AI SDK adapters.
+
+  - **[`config-manager.js`](mdc:scripts/modules/config-manager.js): Configuration Management**
+    - **Purpose**: Loads, validates, and provides access to configuration.
     - **Responsibilities** (See also: [`utilities.mdc`](mdc:.cursor/rules/utilities.mdc)):
-      - Manages global configuration settings loaded from environment variables and defaults.
-      - Implements logging utility with different log levels and output formatting.
-      - Provides file system operation utilities (read/write JSON files).
-      - Includes string manipulation utilities (e.g., `truncate`, `sanitizePrompt`).
-      - Offers task-specific utility functions (e.g., `formatTaskId`, `findTaskById`, `taskExists`).
-      - Implements graph algorithms like cycle detection for dependency management.
-      - **Silent Mode Control**: Provides `enableSilentMode` and `disableSilentMode` functions to control log output.
-    - **Key Components**:
-      - `CONFIG`: Global configuration object.
-      - `log(level, ...args)`: Logging function.
-      - `readJSON(filepath)` / `writeJSON(filepath, data)`: File I/O utilities for JSON files.
-      - `truncate(text, maxLength)`: String truncation utility.
-      - `formatTaskId(id)` / `findTaskById(tasks, taskId)`: Task ID and search utilities.
-      - `findCycles(subtaskId, dependencyMap)`: Cycle detection algorithm.
-      - `enableSilentMode()` / `disableSilentMode()`: Control console logging output.
+      - Reads and merges `.taskmasterconfig` with defaults.
+      - Provides getters (e.g., `getMainProvider`, `getLogLevel`, `getDefaultSubtasks`) for accessing settings.
+      - **Note**: Does **not** store or directly handle API keys (keys are in `.env` or MCP `session.env`).
+
+  - **[`utils.js`](mdc:scripts/modules/utils.js): Core Utility Functions**
+    - **Purpose**: Low-level, reusable CLI utilities.
+    - **Responsibilities** (See also: [`utilities.mdc`](mdc:.cursor/rules/utilities.mdc)):
+      - Logging (`log` function), File I/O (`readJSON`, `writeJSON`), String utils (`truncate`).
+      - Task utils (`findTaskById`), Dependency utils (`findCycles`).
+      - API Key Resolution (`resolveEnvVariable`).
+      - Silent Mode Control (`enableSilentMode`, `disableSilentMode`).
 
   - **[`mcp-server/`](mdc:mcp-server/): MCP Server Integration**
-    - **Purpose**: Provides an MCP (Model Context Protocol) interface for Task Master, allowing integration with external tools like Cursor. Uses FastMCP framework.
+    - **Purpose**: Provides MCP interface using FastMCP.
     - **Responsibilities** (See also: [`mcp.mdc`](mdc:.cursor/rules/mcp.mdc)):
-      - Registers Task Master functionalities as tools consumable via MCP.
-      - Handles MCP requests via tool `execute` methods defined in `mcp-server/src/tools/*.js`.
-      - Tool `execute` methods call corresponding **direct function wrappers**.
-      - Tool `execute` methods use `getProjectRootFromSession` (from [`tools/utils.js`](mdc:mcp-server/src/tools/utils.js)) to determine the project root from the client session and pass it to the direct function.
-      - **Direct function wrappers (`*Direct` functions in `mcp-server/src/core/direct-functions/*.js`) contain the main logic for handling MCP requests**, including path resolution, argument validation, caching, and calling core Task Master functions.
-      - Direct functions use `findTasksJsonPath` (from [`core/utils/path-utils.js`](mdc:mcp-server/src/core/utils/path-utils.js)) to locate `tasks.json` based on the provided `projectRoot`.
-      - **Silent Mode Implementation**: Direct functions use `enableSilentMode` and `disableSilentMode` to prevent logs from interfering with JSON responses.
-      - **Async Operations**: Uses `AsyncOperationManager` to handle long-running operations in the background.
-      - **Project Initialization**: Provides `initialize_project` command for setting up new projects from within integrated clients.
-      - Tool `execute` methods use `handleApiResult` from [`tools/utils.js`](mdc:mcp-server/src/tools/utils.js) to process the result from the direct function and format the final MCP response.
-      - Uses CLI execution via `executeTaskMasterCommand` as a fallback only when necessary.
-      - **Implements Robust Path Finding**: The utility [`tools/utils.js`](mdc:mcp-server/src/tools/utils.js) (specifically `getProjectRootFromSession`) and [`core/utils/path-utils.js`](mdc:mcp-server/src/core/utils/path-utils.js) (specifically `findTasksJsonPath`) work together. The tool gets the root via session, passes it to the direct function, which uses `findTasksJsonPath` to locate the specific `tasks.json` file within that root.
-      - **Implements Caching**: Utilizes a caching layer (`ContextManager` with `lru-cache`). Caching logic is invoked *within* the direct function wrappers using the `getCachedOrExecute` utility for performance-sensitive read operations.
-      - Standardizes response formatting and data filtering using utilities in [`tools/utils.js`](mdc:mcp-server/src/tools/utils.js).
-      - **Resource Management**: Provides access to static and dynamic resources.
-    - **Key Components**:
-      - `mcp-server/src/index.js`: Main server class definition with FastMCP initialization, resource registration, and server lifecycle management.
-      - `mcp-server/src/server.js`: Main server setup and initialization.
-      - `mcp-server/src/tools/`: Directory containing individual tool definitions. Each tool's `execute` method orchestrates the call to core logic and handles the response.
-      - `mcp-server/src/tools/utils.js`: Provides MCP-specific utilities like `handleApiResult`, `processMCPResponseData`, `getCachedOrExecute`, and **`getProjectRootFromSession`**.
-      - `mcp-server/src/core/utils/`: Directory containing utility functions specific to the MCP server, like **`path-utils.js` for resolving `tasks.json` within a given root** and **`async-manager.js` for handling background operations**.
-      - `mcp-server/src/core/direct-functions/`: Directory containing individual files for each **direct function wrapper (`*Direct`)**. These files contain the primary logic for MCP tool execution.
-      - `mcp-server/src/core/resources/`: Directory containing resource handlers for task templates, workflow definitions, and other static/dynamic data exposed to LLM clients.
-      - [`task-master-core.js`](mdc:mcp-server/src/core/task-master-core.js): Acts as an import/export hub, collecting and exporting direct functions from the `direct-functions` directory and MCP utility functions.
-    - **Naming Conventions**:
-      - **Files** use **kebab-case**: `list-tasks.js`, `set-task-status.js`, `parse-prd.js`
-      - **Direct Functions** use **camelCase** with `Direct` suffix: `listTasksDirect`, `setTaskStatusDirect`, `parsePRDDirect`
-      - **Tool Registration Functions** use **camelCase** with `Tool` suffix: `registerListTasksTool`, `registerSetTaskStatusTool`
-      - **MCP Tool Names** use **snake_case**: `list_tasks`, `set_task_status`, `parse_prd_document`
-      - **Resource Handlers** use **camelCase** with pattern URI: `@mcp.resource("tasks://templates/{template_id}")`
-    - **AsyncOperationManager**:
-      - **Purpose**: Manages background execution of long-running operations.
-      - **Location**: `mcp-server/src/core/utils/async-manager.js`
-      - **Key Features**:
-        - Operation tracking with unique IDs using UUID
-        - Status management (pending, running, completed, failed)
-        - Progress reporting forwarded from background tasks
-        - Operation history with automatic cleanup of completed operations
-        - Context preservation (log, session, reportProgress)
-        - Robust error handling for background tasks
-      - **Usage**: Used for CPU-intensive operations like task expansion and PRD parsing
+      - Registers tools (`mcp-server/src/tools/*.js`). Tool `execute` methods **should be wrapped** with the `withNormalizedProjectRoot` HOF (from `tools/utils.js`) to ensure consistent path handling.
+      - The HOF provides a normalized `args.projectRoot` to the `execute` method.
+      - Tool `execute` methods call **direct function wrappers** (`mcp-server/src/core/direct-functions/*.js`), passing the normalized `projectRoot` and other args.
+      - Direct functions use path utilities (`mcp-server/src/core/utils/`) to resolve paths based on `projectRoot` from session.
+      - Direct functions implement silent mode, logger wrappers, and call core logic functions from `scripts/modules/`.
+      - Manages MCP caching and response formatting.
 
-- **Data Flow and Module Dependencies**:
+  - **[`init.js`](mdc:scripts/init.js): Project Initialization Logic**
+    - **Purpose**: Sets up new Task Master project structure.
+    - **Responsibilities**: Creates directories, copies templates, manages `package.json`, sets up `.cursor/mcp.json`.
 
-  - **Commands Initiate Actions**: User commands entered via the CLI (handled by [`commands.js`](mdc:scripts/modules/commands.js)) are the entry points for most operations.
-  - **Command Handlers Delegate to Managers**: Command handlers in [`commands.js`](mdc:scripts/modules/commands.js) call functions in [`task-manager.js`](mdc:scripts/modules/task-manager.js) and [`dependency-manager.js`](mdc:scripts/modules/dependency-manager.js) to perform core task and dependency management logic.
-  - **UI for Presentation**:  [`ui.js`](mdc:scripts/modules/ui.js) is used by command handlers and task/dependency managers to display information to the user. UI functions primarily consume data and format it for output, without modifying core application state.
-  - **Utilities for Common Tasks**: [`utils.js`](mdc:scripts/modules/utils.js) provides helper functions used by all other modules for configuration, logging, file operations, and common data manipulations.
-  - **AI Services Integration**: AI functionalities (complexity analysis, task expansion, PRD parsing) are invoked from [`task-manager.js`](mdc:scripts/modules/task-manager.js) and potentially [`commands.js`](mdc:scripts/modules/commands.js), likely using functions that would reside in a dedicated `ai-services.js` module or be integrated within `utils.js` or `task-manager.js`.
-  - **MCP Server Interaction**: External tools interact with the `mcp-server`. MCP Tool `execute` methods use `getProjectRootFromSession` to find the project root, then call direct function wrappers (in `mcp-server/src/core/direct-functions/`) passing the root in `args`. These wrappers handle path finding for `tasks.json` (using `path-utils.js`), validation, caching, call the core logic from `scripts/modules/` (passing logging context via the standard wrapper pattern detailed in mcp.mdc), and return a standardized result. The final MCP response is formatted by `mcp-server/src/tools/utils.js`. See [`mcp.mdc`](mdc:.cursor/rules/mcp.mdc) for details.
+- **Data Flow and Module Dependencies (Updated)**:
+
+  - **CLI**: `bin/task-master.js` -> `scripts/dev.js` (loads `.env`) -> `scripts/modules/commands.js` -> Core Logic (`scripts/modules/*`) -> Unified AI Service (`ai-services-unified.js`) -> Provider Adapters -> LLM API.
+  - **MCP**: External Tool -> `mcp-server/server.js` -> Tool (`mcp-server/src/tools/*`) -> Direct Function (`mcp-server/src/core/direct-functions/*`) -> Core Logic (`scripts/modules/*`) -> Unified AI Service (`ai-services-unified.js`) -> Provider Adapters -> LLM API.
+  - **Configuration**: Core logic needing non-AI settings calls `config-manager.js` getters (passing `session.env` via `explicitRoot` if from MCP). Unified AI Service internally calls `config-manager.js` getters (using `role`) for AI params and `utils.js` (`resolveEnvVariable` with `session.env`) for API keys.
 
 ## Silent Mode Implementation Pattern in MCP Direct Functions
 
@@ -353,19 +279,8 @@ The `initialize_project` command provides a way to set up a new Task Master proj
   - Configures project metadata (name, description, version)
   - Handles shell alias creation if requested
   - Works in both interactive and non-interactive modes
-
-## Async Operation Management
-
-The AsyncOperationManager provides background task execution capabilities:
-
-- **Location**: `mcp-server/src/core/utils/async-manager.js`
-- **Key Components**:
-  - `asyncOperationManager` singleton instance
-  - `addOperation(operationFn, args, context)` method
-  - `getStatus(operationId)` method
-- **Usage Flow**:
-  1. Client calls an MCP tool that may take time to complete
-  2. Tool uses AsyncOperationManager to run the operation in background
-  3. Tool returns immediate response with operation ID
-  4. Client polls `get_operation_status` tool with the ID
-  5. Once completed, client can access operation results
+  - Creates necessary directories and files for a new project
+  - Sets up `tasks.json` and initial task files
+  - Configures project metadata (name, description, version)
+  - Handles shell alias creation if requested
+  - Works in both interactive and non-interactive modes

.cursor/rules/commands.mdc

@@ -24,7 +24,7 @@ While this document details the implementation of Task Master's **CLI commands**
   programInstance
     .command('command-name')
     .description('Clear, concise description of what the command does')
-    .option('-s, --short-option <value>', 'Option description', 'default value')
+    .option('-o, --option <value>', 'Option description', 'default value')
     .option('--long-option <value>', 'Option description')
     .action(async (options) => {
       // Command implementation
@@ -34,7 +34,8 @@ While this document details the implementation of Task Master's **CLI commands**
 - **Command Handler Organization**:
   - ✅ DO: Keep action handlers concise and focused
   - ✅ DO: Extract core functionality to appropriate modules
-  - ✅ DO: Include validation for required parameters
+  - ✅ DO: Have the action handler import and call the relevant functions from core modules, like `task-manager.js` or `init.js`, passing the parsed `options`.
+  - ✅ DO: Perform basic parameter validation, such as checking for required options, within the action handler or at the start of the called core function.
   - ❌ DON'T: Implement business logic in command handlers
 
 ## Best Practices for Removal/Delete Commands
@@ -43,7 +44,7 @@ When implementing commands that delete or remove data (like `remove-task` or `re
 
 - **Confirmation Prompts**:
   - ✅ **DO**: Include a confirmation prompt by default for destructive operations
-  - ✅ **DO**: Provide a `--yes` or `-y` flag to skip confirmation for scripting/automation
+  - ✅ **DO**: Provide a `--yes` or `-y` flag to skip confirmation, useful for scripting or automation
   - ✅ **DO**: Show what will be deleted in the confirmation message
   - ❌ **DON'T**: Perform destructive operations without user confirmation unless explicitly overridden
 
@@ -77,7 +78,7 @@ When implementing commands that delete or remove data (like `remove-task` or `re
 
 - **File Path Handling**:
   - ✅ **DO**: Use `path.join()` to construct file paths
-  - ✅ **DO**: Follow established naming conventions for tasks (e.g., `task_001.txt`)
+  - ✅ **DO**: Follow established naming conventions for tasks, like `task_001.txt`
   - ✅ **DO**: Check if files exist before attempting to delete them
   - ✅ **DO**: Handle file deletion errors gracefully
   - ❌ **DON'T**: Construct paths with string concatenation
@@ -165,10 +166,10 @@ When implementing commands that delete or remove data (like `remove-task` or `re
   - ✅ DO: Use descriptive, action-oriented names
 
 - **Option Names**:
-  - ✅ DO: Use kebab-case for long-form option names (`--output-format`)
-  - ✅ DO: Provide single-letter shortcuts when appropriate (`-f, --file`)
+  - ✅ DO: Use kebab-case for long-form option names, like `--output-format`
+  - ✅ DO: Provide single-letter shortcuts when appropriate, like `-f, --file`
   - ✅ DO: Use consistent option names across similar commands
-  - ❌ DON'T: Use different names for the same concept (`--file` in one command, `--path` in another)
+  - ❌ DON'T: Use different names for the same concept, such as `--file` in one command and `--path` in another
 
   ```javascript
   // ✅ DO: Use consistent option naming
@@ -180,7 +181,7 @@ When implementing commands that delete or remove data (like `remove-task` or `re
   .option('-p, --path <dir>', 'Output directory') // Should be --output
   ```
 
-  > **Note**: Although options are defined with kebab-case (`--num-tasks`), Commander.js stores them internally as camelCase properties. Access them in code as `options.numTasks`, not `options['num-tasks']`.
+  > **Note**: Although options are defined with kebab-case, like `--num-tasks`, Commander.js stores them internally as camelCase properties. Access them in code as `options.numTasks`, not `options['num-tasks']`.
 
 - **Boolean Flag Conventions**:
   - ✅ DO: Use positive flags with `--skip-` prefix for disabling behavior
@@ -209,7 +210,7 @@ When implementing commands that delete or remove data (like `remove-task` or `re
 - **Required Parameters**:
   - ✅ DO: Check that required parameters are provided
   - ✅ DO: Provide clear error messages when parameters are missing
-  - ✅ DO: Use early returns with process.exit(1) for validation failures
+  - ✅ DO: Use early returns with `process.exit(1)` for validation failures
 
   ```javascript
   // ✅ DO: Validate required parameters early
@@ -220,7 +221,7 @@ When implementing commands that delete or remove data (like `remove-task` or `re
   ```
 
 - **Parameter Type Conversion**:
-  - ✅ DO: Convert string inputs to appropriate types (numbers, booleans)
+  - ✅ DO: Convert string inputs to appropriate types, such as numbers or booleans
   - ✅ DO: Handle conversion errors gracefully
 
   ```javascript
@@ -253,7 +254,7 @@ When implementing commands that delete or remove data (like `remove-task` or `re
   const taskId = parseInt(options.id, 10);
   if (isNaN(taskId) || taskId <= 0) {
     console.error(chalk.red(`Error: Invalid task ID: ${options.id}. Task ID must be a positive integer.`));
-    console.log(chalk.yellow('Usage example: task-master update-task --id=\'23\' --prompt=\'Update with new information.\nEnsure proper error handling.\''));
+    console.log(chalk.yellow("Usage example: task-master update-task --id='23' --prompt='Update with new information.\\nEnsure proper error handling.'"));
     process.exit(1);
   }
   
@@ -391,9 +392,9 @@ When implementing commands that delete or remove data (like `remove-task` or `re
   process.on('uncaughtException', (err) => {
     // Handle Commander-specific errors
     if (err.code === 'commander.unknownOption') {
-      const option = err.message.match(/'([^']+)'/)?.[1];
+      const option = err.message.match(/'([^']+)'/)?.[1]; // Safely extract option name
       console.error(chalk.red(`Error: Unknown option '${option}'`));
-      console.error(chalk.yellow(`Run 'task-master <command> --help' to see available options`));
+      console.error(chalk.yellow("Run 'task-master <command> --help' to see available options"));
       process.exit(1);
     }
     
@@ -463,9 +464,9 @@ When implementing commands that delete or remove data (like `remove-task` or `re
     .option('-f, --file <path>', 'Path to the tasks file', 'tasks/tasks.json')
     .option('-p, --parent <id>', 'ID of the parent task (required)')
     .option('-i, --task-id <id>', 'Existing task ID to convert to subtask')
-    .option('-t, --title <title>', 'Title for the new subtask (when not converting)')
-    .option('-d, --description <description>', 'Description for the new subtask (when not converting)')
-    .option('--details <details>', 'Implementation details for the new subtask (when not converting)')
+    .option('-t, --title <title>', 'Title for the new subtask, required if not converting')
+    .option('-d, --description <description>', 'Description for the new subtask, optional')
+    .option('--details <details>', 'Implementation details for the new subtask, optional')
     .option('--dependencies <ids>', 'Comma-separated list of subtask IDs this subtask depends on')
     .option('--status <status>', 'Initial status for the subtask', 'pending')
     .option('--skip-generate', 'Skip regenerating task files')
@@ -488,8 +489,8 @@ When implementing commands that delete or remove data (like `remove-task` or `re
     .command('remove-subtask')
     .description('Remove a subtask from its parent task, optionally converting it to a standalone task')
     .option('-f, --file <path>', 'Path to the tasks file', 'tasks/tasks.json')
-    .option('-i, --id <id>', 'ID of the subtask to remove in format "parentId.subtaskId" (required)')
-    .option('-c, --convert', 'Convert the subtask to a standalone task')
+    .option('-i, --id <id>', 'ID of the subtask to remove in format parentId.subtaskId, required')
+    .option('-c, --convert', 'Convert the subtask to a standalone task instead of deleting')
     .option('--skip-generate', 'Skip regenerating task files')
     .action(async (options) => {
       // Implementation with detailed error handling
@@ -512,7 +513,8 @@ When implementing commands that delete or remove data (like `remove-task` or `re
   // ✅ DO: Implement version checking function
   async function checkForUpdate() {
     // Implementation details...
-    return { currentVersion, latestVersion, needsUpdate };
+    // Example return structure:
+    return { currentVersion, latestVersion, updateAvailable };
   }
   
   // ✅ DO: Implement semantic version comparison
@@ -552,7 +554,7 @@ When implementing commands that delete or remove data (like `remove-task` or `re
       
       // After command execution, check if an update is available
       const updateInfo = await updateCheckPromise;
-      if (updateInfo.needsUpdate) {
+      if (updateInfo.updateAvailable) {
         displayUpgradeNotification(updateInfo.currentVersion, updateInfo.latestVersion);
       }
     } catch (error) {

.cursor/rules/dev_workflow.mdc

@@ -3,7 +3,6 @@ description: Guide for using Task Master to manage task-driven development workf
 globs: **/*
 alwaysApply: true
 ---
-
 # Task Master Development Workflow
 
 This guide outlines the typical process for using Task Master to manage software development projects.
@@ -29,21 +28,21 @@ Task Master offers two primary ways to interact:
 
 ## Standard Development Workflow Process
 
--   Start new projects by running `init` tool / `task-master init` or `parse_prd` / `task-master parse-prd --input='<prd-file.txt>'` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) to generate initial tasks.json
+-   Start new projects by running `initialize_project` tool / `task-master init` or `parse_prd` / `task-master parse-prd --input='<prd-file.txt>'` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) to generate initial tasks.json
 -   Begin coding sessions with `get_tasks` / `task-master list` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) to see current tasks, status, and IDs
 -   Determine the next task to work on using `next_task` / `task-master next` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)).
--   Analyze task complexity with `analyze_complexity` / `task-master analyze-complexity --research` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) before breaking down tasks
+-   Analyze task complexity with `analyze_project_complexity` / `task-master analyze-complexity --research` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) before breaking down tasks
 -   Review complexity report using `complexity_report` / `task-master complexity-report` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)).
 -   Select tasks based on dependencies (all marked 'done'), priority level, and ID order
 -   Clarify tasks by checking task files in tasks/ directory or asking for user input
 -   View specific task details using `get_task` / `task-master show <id>` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) to understand implementation requirements
--   Break down complex tasks using `expand_task` / `task-master expand --id=<id>` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) with appropriate flags
+-   Break down complex tasks using `expand_task` / `task-master expand --id=<id> --force --research` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) with appropriate flags like `--force` (to replace existing subtasks) and `--research`.
 -   Clear existing subtasks if needed using `clear_subtasks` / `task-master clear-subtasks --id=<id>` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) before regenerating
 -   Implement code following task details, dependencies, and project standards
 -   Verify tasks according to test strategies before marking as complete (See [`tests.mdc`](mdc:.cursor/rules/tests.mdc))
 -   Mark completed tasks with `set_task_status` / `task-master set-status --id=<id> --status=done` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc))
 -   Update dependent tasks when implementation differs from original plan using `update` / `task-master update --from=<id> --prompt="..."` or `update_task` / `task-master update-task --id=<id> --prompt="..."` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc))
--   Add new tasks discovered during implementation using `add_task` / `task-master add-task --prompt="..."` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)).
+-   Add new tasks discovered during implementation using `add_task` / `task-master add-task --prompt="..." --research` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)).
 -   Add new subtasks as needed using `add_subtask` / `task-master add-subtask --parent=<id> --title="..."` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)).
 -   Append notes or details to subtasks using `update_subtask` / `task-master update-subtask --id=<subtaskId> --prompt='Add implementation notes here...\nMore details...'` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)).
 -   Generate task files with `generate` / `task-master generate` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) after updating tasks.json
@@ -53,29 +52,30 @@ Task Master offers two primary ways to interact:
 
 ## Task Complexity Analysis
 
--   Run `analyze_complexity` / `task-master analyze-complexity --research` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) for comprehensive analysis
+-   Run `analyze_project_complexity` / `task-master analyze-complexity --research` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) for comprehensive analysis
 -   Review complexity report via `complexity_report` / `task-master complexity-report` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) for a formatted, readable version.
 -   Focus on tasks with highest complexity scores (8-10) for detailed breakdown
 -   Use analysis results to determine appropriate subtask allocation
--   Note that reports are automatically used by the `expand` tool/command
+-   Note that reports are automatically used by the `expand_task` tool/command
 
 ## Task Breakdown Process
 
--   For tasks with complexity analysis, use `expand_task` / `task-master expand --id=<id>` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc))
--   Otherwise use `expand_task` / `task-master expand --id=<id> --num=<number>`
--   Add `--research` flag to leverage Perplexity AI for research-backed expansion
--   Use `--prompt="<context>"` to provide additional context when needed
--   Review and adjust generated subtasks as necessary
--   Use `--all` flag with `expand` or `expand_all` to expand multiple pending tasks at once
--   If subtasks need regeneration, clear them first with `clear_subtasks` / `task-master clear-subtasks` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)).
+-   Use `expand_task` / `task-master expand --id=<id>`. It automatically uses the complexity report if found, otherwise generates default number of subtasks.
+-   Use `--num=<number>` to specify an explicit number of subtasks, overriding defaults or complexity report recommendations.
+-   Add `--research` flag to leverage Perplexity AI for research-backed expansion.
+-   Add `--force` flag to clear existing subtasks before generating new ones (default is to append).
+-   Use `--prompt="<context>"` to provide additional context when needed.
+-   Review and adjust generated subtasks as necessary.
+-   Use `expand_all` tool or `task-master expand --all` to expand multiple pending tasks at once, respecting flags like `--force` and `--research`.
+-   If subtasks need complete replacement (regardless of the `--force` flag on `expand`), clear them first with `clear_subtasks` / `task-master clear-subtasks --id=<id>`.
 
 ## Implementation Drift Handling
 
 -   When implementation differs significantly from planned approach
 -   When future tasks need modification due to current implementation choices
 -   When new dependencies or requirements emerge
--   Use `update` / `task-master update --from=<futureTaskId> --prompt='<explanation>\nUpdate context...'` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) to update multiple future tasks.
--   Use `update_task` / `task-master update-task --id=<taskId> --prompt='<explanation>\nUpdate context...'` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) to update a single specific task.
+-   Use `update` / `task-master update --from=<futureTaskId> --prompt='<explanation>\nUpdate context...' --research` to update multiple future tasks.
+-   Use `update_task` / `task-master update-task --id=<taskId> --prompt='<explanation>\nUpdate context...' --research` to update a single specific task.
 
 ## Task Status Management
 
@@ -97,28 +97,32 @@ Task Master offers two primary ways to interact:
 - **details**: In-depth implementation instructions (Example: `"Use GitHub client ID/secret, handle callback, set session token."`) 
 - **testStrategy**: Verification approach (Example: `"Deploy and call endpoint to confirm 'Hello World' response."`) 
 - **subtasks**: List of smaller, more specific tasks (Example: `[{"id": 1, "title": "Configure OAuth", ...}]`) 
-- Refer to [`tasks.mdc`](mdc:.cursor/rules/tasks.mdc) for more details on the task data structure.
+- Refer to task structure details (previously linked to `tasks.mdc`).
 
-## Environment Variables Configuration
+## Configuration Management (Updated)
 
-- Task Master behavior is configured via environment variables:
-  - **ANTHROPIC_API_KEY** (Required): Your Anthropic API key for Claude.
-  - **MODEL**: Claude model to use (e.g., `claude-3-opus-20240229`).
-  - **MAX_TOKENS**: Maximum tokens for AI responses.
-  - **TEMPERATURE**: Temperature for AI model responses.
-  - **DEBUG**: Enable debug logging (`true`/`false`).
-  - **LOG_LEVEL**: Console output level (`debug`, `info`, `warn`, `error`).
-  - **DEFAULT_SUBTASKS**: Default number of subtasks for `expand`.
-  - **DEFAULT_PRIORITY**: Default priority for new tasks.
-  - **PROJECT_NAME**: Project name used in metadata.
-  - **PROJECT_VERSION**: Project version used in metadata.
-  - **PERPLEXITY_API_KEY**: API key for Perplexity AI (for `--research` flags).
-  - **PERPLEXITY_MODEL**: Perplexity model to use (e.g., `sonar-medium-online`).
-- See [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc) for default values and examples.
+Taskmaster configuration is managed through two main mechanisms:
+
+1.  **`.taskmasterconfig` File (Primary):**
+    *   Located in the project root directory.
+    *   Stores most configuration settings: AI model selections (main, research, fallback), parameters (max tokens, temperature), logging level, default subtasks/priority, project name, etc.
+    *   **Managed via `task-master models --setup` command.** Do not edit manually unless you know what you are doing.
+    *   **View/Set specific models via `task-master models` command or `models` MCP tool.**
+    *   Created automatically when you run `task-master models --setup` for the first time.
+
+2.  **Environment Variables (`.env` / `mcp.json`):**
+    *   Used **only** for sensitive API keys and specific endpoint URLs.
+    *   Place API keys (one per provider) in a `.env` file in the project root for CLI usage.
+    *   For MCP/Cursor integration, configure these keys in the `env` section of `.cursor/mcp.json`.
+    *   Available keys/variables: See `assets/env.example` or the Configuration section in the command reference (previously linked to `taskmaster.mdc`).
+
+**Important:** Non-API key settings (like model selections, `MAX_TOKENS`, `TASKMASTER_LOG_LEVEL`) are **no longer configured via environment variables**. Use the `task-master models` command (or `--setup` for interactive configuration) or the `models` MCP tool.
+**If AI commands FAIL in MCP** verify that the API key for the selected provider is present in the `env` section of `.cursor/mcp.json`.
+**If AI commands FAIL in CLI** verify that the API key for the selected provider is present in the `.env` file in the root of the project.
 
 ## Determining the Next Task
 
-- Run `next_task` / `task-master next` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) to show the next task to work on
+- Run `next_task` / `task-master next` to show the next task to work on.
 - The command identifies tasks with all dependencies satisfied
 - Tasks are prioritized by priority level, dependency count, and ID
 - The command shows comprehensive task information including:
@@ -133,7 +137,7 @@ Task Master offers two primary ways to interact:
 
 ## Viewing Specific Task Details
 
-- Run `get_task` / `task-master show <id>` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) to view a specific task
+- Run `get_task` / `task-master show <id>` to view a specific task.
 - Use dot notation for subtasks: `task-master show 1.2` (shows subtask 2 of task 1)
 - Displays comprehensive information similar to the next command, but for a specific task
 - For parent tasks, shows all subtasks and their current status
@@ -143,8 +147,8 @@ Task Master offers two primary ways to interact:
 
 ## Managing Task Dependencies
 
-- Use `add_dependency` / `task-master add-dependency --id=<id> --depends-on=<id>` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) to add a dependency
-- Use `remove_dependency` / `task-master remove-dependency --id=<id> --depends-on=<id>` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)) to remove a dependency
+- Use `add_dependency` / `task-master add-dependency --id=<id> --depends-on=<id>` to add a dependency.
+- Use `remove_dependency` / `task-master remove-dependency --id=<id> --depends-on=<id>` to remove a dependency.
 - The system prevents circular dependencies and duplicate dependency entries
 - Dependencies are checked for existence before being added or removed
 - Task files are automatically regenerated after dependency changes
@@ -164,14 +168,14 @@ Once a task has been broken down into subtasks using `expand_task` or similar me
     *   Gather *all* relevant details from this exploration phase.
 
 3.  **Log the Plan:**
-    *   Run `update_subtask` / `task-master update-subtask --id=<subtaskId> --prompt='<detailed plan>'` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)).
+    *   Run `update_subtask` / `task-master update-subtask --id=<subtaskId> --prompt='<detailed plan>'`.
     *   Provide the *complete and detailed* findings from the exploration phase in the prompt. Include file paths, line numbers, proposed diffs, reasoning, and any potential challenges identified. Do not omit details. The goal is to create a rich, timestamped log within the subtask's `details`.
 
 4.  **Verify the Plan:**
     *   Run `get_task` / `task-master show <subtaskId>` again to confirm that the detailed implementation plan has been successfully appended to the subtask's details.
 
 5.  **Begin Implementation:**
-    *   Set the subtask status using `set_task_status` / `task-master set-status --id=<subtaskId> --status=in-progress` (see [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc)).
+    *   Set the subtask status using `set_task_status` / `task-master set-status --id=<subtaskId> --status=in-progress`.
     *   Start coding based on the logged plan.
 
 6.  **Refine and Log Progress (Iteration 2+):**
@@ -189,7 +193,7 @@ Once a task has been broken down into subtasks using `expand_task` or similar me
 7.  **Review & Update Rules (Post-Implementation):**
     *   Once the implementation for the subtask is functionally complete, review all code changes and the relevant chat history.
     *   Identify any new or modified code patterns, conventions, or best practices established during the implementation.
-    *   Create new or update existing Cursor rules in the `.cursor/rules/` directory to capture these patterns, following the guidelines in [`cursor_rules.mdc`](mdc:.cursor/rules/cursor_rules.mdc) and [`self_improve.mdc`](mdc:.cursor/rules/self_improve.mdc).
+    *   Create new or update existing rules following internal guidelines (previously linked to `cursor_rules.mdc` and `self_improve.mdc`).
 
 8.  **Mark Task Complete:**
     *   After verifying the implementation and updating any necessary rules, mark the subtask as completed: `set_task_status` / `task-master set-status --id=<subtaskId> --status=done`.
@@ -198,10 +202,10 @@ Once a task has been broken down into subtasks using `expand_task` or similar me
     *   Stage the relevant code changes and any updated/new rule files (`git add .`).
     *   Craft a comprehensive Git commit message summarizing the work done for the subtask, including both code implementation and any rule adjustments.
     *   Execute the commit command directly in the terminal (e.g., `git commit -m 'feat(module): Implement feature X for subtask <subtaskId>\n\n- Details about changes...\n- Updated rule Y for pattern Z'`).
-    *   Consider if a Changeset is needed according to [`changeset.mdc`](mdc:.cursor/rules/changeset.mdc). If so, run `npm run changeset`, stage the generated file, and amend the commit or create a new one.
+    *   Consider if a Changeset is needed according to internal versioning guidelines (previously linked to `changeset.mdc`). If so, run `npm run changeset`, stage the generated file, and amend the commit or create a new one.
 
 10. **Proceed to Next Subtask:**
-    *   Identify the next subtask in the dependency chain (e.g., using `next_task` / `task-master next`) and repeat this iterative process starting from step 1.
+    *   Identify the next subtask (e.g., using `next_task` / `task-master next`).
 
 ## Code Analysis & Refactoring Techniques
 

.cursor/rules/glossary.mdc

@@ -3,7 +3,6 @@ description: Glossary of other Cursor rules
 globs: **/*
 alwaysApply: true
 ---
-
 # Glossary of Task Master Cursor Rules
 
 This file provides a quick reference to the purpose of each rule file located in the `.cursor/rules` directory.
@@ -23,4 +22,5 @@ This file provides a quick reference to the purpose of each rule file located in
 - **[`tests.mdc`](mdc:.cursor/rules/tests.mdc)**: Guidelines for implementing and maintaining tests for Task Master CLI.
 - **[`ui.mdc`](mdc:.cursor/rules/ui.mdc)**: Guidelines for implementing and maintaining user interface components.
 - **[`utilities.mdc`](mdc:.cursor/rules/utilities.mdc)**: Guidelines for implementing utility functions.
+- **[`telemetry.mdc`](mdc:.cursor/rules/telemetry.mdc)**: Guidelines for integrating AI usage telemetry across Task Master.
 

.cursor/rules/mcp.mdc

@@ -3,7 +3,6 @@ description: Guidelines for implementing and interacting with the Task Master MC
 globs: mcp-server/src/**/*, scripts/modules/**/*
 alwaysApply: false
 ---
-
 # Task Master MCP Server Guidelines
 
 This document outlines the architecture and implementation patterns for the Task Master Model Context Protocol (MCP) server, designed for integration with tools like Cursor.
@@ -90,69 +89,54 @@ When implementing a new direct function in `mcp-server/src/core/direct-functions
      ```
 
 5. **Handling Logging Context (`mcpLog`)**:
-   - **Requirement**: Core functions that use the internal `report` helper function (common in `task-manager.js`, `dependency-manager.js`, etc.) expect the `options` object to potentially contain an `mcpLog` property. This `mcpLog` object **must** have callable methods for each log level (e.g., `mcpLog.info(...)`, `mcpLog.error(...)`).
-   - **Challenge**: The `log` object provided by FastMCP to the direct function's context, while functional, might not perfectly match this expected structure or could change in the future. Passing it directly can lead to runtime errors like `mcpLog[level] is not a function`.
-   - **Solution: The Logger Wrapper Pattern**: To reliably bridge the FastMCP `log` object and the core function's `mcpLog` expectation, use a simple wrapper object within the direct function:
+   - **Requirement**: Core functions (like those in `task-manager.js`) may accept an `options` object containing an optional `mcpLog` property. If provided, the core function expects this object to have methods like `mcpLog.info(...)`, `mcpLog.error(...)`.
+   - **Solution: The Logger Wrapper Pattern**: When calling a core function from a direct function, pass the `log` object provided by FastMCP *wrapped* in the standard `logWrapper` object. This ensures the core function receives a logger with the expected method structure.
      ```javascript
      // Standard logWrapper pattern within a Direct Function
      const logWrapper = {
        info: (message, ...args) => log.info(message, ...args),
        warn: (message, ...args) => log.warn(message, ...args),
        error: (message, ...args) => log.error(message, ...args),
-       debug: (message, ...args) => log.debug && log.debug(message, ...args), // Handle optional debug
-       success: (message, ...args) => log.info(message, ...args) // Map success to info if needed
+       debug: (message, ...args) => log.debug && log.debug(message, ...args),
+       success: (message, ...args) => log.info(message, ...args)
      };
 
      // ... later when calling the core function ...
      await coreFunction(
        // ... other arguments ...
-       tasksPath, 
-       taskId,
        { 
          mcpLog: logWrapper, // Pass the wrapper object
-         session 
+         session // Also pass session if needed by core logic or AI service
        },
        'json' // Pass 'json' output format if supported by core function
      );
      ```
-   - **Critical For JSON Output Format**: Passing the `logWrapper` as `mcpLog` serves a dual purpose:
-     1. **Prevents Runtime Errors**: It ensures the `mcpLog[level](...)` calls within the core function succeed
-     2. **Controls Output Format**: In functions like `updateTaskById` and `updateSubtaskById`, the presence of `mcpLog` in the options triggers setting `outputFormat = 'json'` (instead of 'text'). This prevents UI elements (spinners, boxes) from being generated, which would break the JSON response.
-   - **Proven Solution**: This pattern has successfully fixed multiple issues in our MCP tools (including `update-task` and `update-subtask`), where direct passing of the `log` object or omitting `mcpLog` led to either runtime errors or JSON parsing failures from UI output.
-   - **When To Use**: Implement this wrapper in any direct function that calls a core function with an `options` object that might use `mcpLog` for logging or output format control.
-   - **Why it Works**: The `logWrapper` explicitly defines the `.info()`, `.warn()`, `.error()`, etc., methods that the core function's `report` helper needs, ensuring the `mcpLog[level](...)` call succeeds. It simply forwards the logging calls to the actual FastMCP `log` object.
-   - **Combined with Silent Mode**: Remember that using the `logWrapper` for `mcpLog` is **necessary *in addition* to using `enableSilentMode()` / `disableSilentMode()`** (see next point). The wrapper handles structured logging *within* the core function, while silent mode suppresses direct `console.log` and UI elements (spinners, boxes) that would break the MCP JSON response.
+   - **JSON Output**: Passing `mcpLog` (via the wrapper) often triggers the core function to use a JSON-friendly output format, suppressing spinners/boxes.
+   - ✅ **DO**: Implement this pattern in direct functions calling core functions that might use `mcpLog`.
 
 6. **Silent Mode Implementation**:
-    - ✅ **DO**: Import silent mode utilities at the top: `import { enableSilentMode, disableSilentMode, isSilentMode } from '../../../../scripts/modules/utils.js';`
-    - ✅ **DO**: Ensure core Task Master functions called from direct functions do **not** pollute `stdout` with console output (banners, spinners, logs) that would break MCP's JSON communication.
-      - **Preferred**: Modify the core function to accept an `outputFormat: 'json'` parameter and check it internally before printing UI elements. Pass `'json'` from the direct function.
-      - **Required Fallback/Guarantee**: If the core function cannot be modified or its output suppression is unreliable, **wrap the core function call** within the direct function using `enableSilentMode()` / `disableSilentMode()` in a `try/finally` block. This guarantees no console output interferes with the MCP response.
-    - ✅ **DO**: Use `isSilentMode()` function to check global silent mode status if needed (rare in direct functions), NEVER access the global `silentMode` variable directly.
-    - ❌ **DON'T**: Wrap AI client initialization or AI API calls in `enable/disableSilentMode`; their logging is controlled via the `log` object (passed potentially within the `logWrapper` for core functions).
-    - ❌ **DON'T**: Assume a core function is silent just because it *should* be. Verify or use the `enable/disableSilentMode` wrapper.
-    - **Example (Direct Function Guaranteeing Silence and using Log Wrapper)**:
+    - ✅ **DO**: Import silent mode utilities: `import { enableSilentMode, disableSilentMode, isSilentMode } from '../../../../scripts/modules/utils.js';`
+    - ✅ **DO**: Wrap core function calls *within direct functions* using `enableSilentMode()` / `disableSilentMode()` in a `try/finally` block if the core function might produce console output (spinners, boxes, direct `console.log`) that isn't reliably controlled by passing `{ mcpLog }` or an `outputFormat` parameter.
+    - ✅ **DO**: Always disable silent mode in the `finally` block.
+    - ❌ **DON'T**: Wrap calls to the unified AI service (`generateTextService`, `generateObjectService`) in silent mode; their logging is handled internally.
+    - **Example (Direct Function Guaranteeing Silence & using Log Wrapper)**:
       ```javascript
       export async function coreWrapperDirect(args, log, context = {}) {
         const { session } = context;
         const tasksPath = findTasksJsonPath(args, log);
-        
-        // Create the logger wrapper
-        const logWrapper = { /* ... as defined above ... */ };
+        const logWrapper = { /* ... */ };
 
         enableSilentMode(); // Ensure silence for direct console output
         try {
-          // Call core function, passing wrapper and 'json' format
           const result = await coreFunction(
              tasksPath,
              args.param1,
-             { mcpLog: logWrapper, session }, 
-             'json' // Explicitly request JSON format if supported
+             { mcpLog: logWrapper, session }, // Pass context
+             'json' // Request JSON format if supported
           );
           return { success: true, data: result };
         } catch (error) {
            log.error(`Error: ${error.message}`);
-           // Return standardized error object
            return { success: false, error: { /* ... */ } };
         } finally {
            disableSilentMode(); // Critical: Always disable in finally
@@ -163,32 +147,6 @@ When implementing a new direct function in `mcp-server/src/core/direct-functions
 7. **Debugging MCP/Core Logic Interaction**:
     - ✅ **DO**: If an MCP tool fails with unclear errors (like JSON parsing failures), run the equivalent `task-master` CLI command in the terminal. The CLI often provides more detailed error messages originating from the core logic (e.g., `ReferenceError`, stack traces) that are obscured by the MCP layer.
 
-### Specific Guidelines for AI-Based Direct Functions
-
-Direct functions that interact with AI (e.g., `addTaskDirect`, `expandTaskDirect`) have additional responsibilities:
-
-- **Context Parameter**: These functions receive an additional `context` object as their third parameter. **Critically, this object should only contain `{ session }`**. Do NOT expect or use `reportProgress` from this context.
-  ```javascript
-  export async function yourAIDirect(args, log, context = {}) {
-    const { session } = context; // Only expect session
-    // ...
-  }
-  ```
-- **AI Client Initialization**:
-  - ✅ **DO**: Use the utilities from [`mcp-server/src/core/utils/ai-client-utils.js`](mdc:mcp-server/src/core/utils/ai-client-utils.js) (e.g., `getAnthropicClientForMCP(session, log)`) to get AI client instances. These correctly use the `session` object to resolve API keys.
-  - ✅ **DO**: Wrap client initialization in a try/catch block and return a specific `AI_CLIENT_ERROR` on failure.
-- **AI Interaction**:
-  - ✅ **DO**: Build prompts using helper functions where appropriate (e.g., from `ai-prompt-helpers.js`).
-  - ✅ **DO**: Make the AI API call using appropriate helpers (e.g., `_handleAnthropicStream`). Pass the `log` object to these helpers for internal logging. **Do NOT pass `reportProgress`**.
-  - ✅ **DO**: Parse the AI response using helpers (e.g., `parseTaskJsonResponse`) and handle parsing errors with a specific code (e.g., `RESPONSE_PARSING_ERROR`).
-- **Calling Core Logic**:
-  - ✅ **DO**: After successful AI interaction, call the relevant core Task Master function (from `scripts/modules/`) if needed (e.g., `addTaskDirect` calls `addTask`).
-  - ✅ **DO**: Pass necessary data, including potentially the parsed AI results, to the core function.
-  - ✅ **DO**: If the core function can produce console output, call it with an `outputFormat: 'json'` argument (or similar, depending on the function) to suppress CLI output. Ensure the core function is updated to respect this. Use `enableSilentMode/disableSilentMode` around the core function call as a fallback if `outputFormat` is not supported or insufficient.
-- **Progress Indication**:
-  - ❌ **DON'T**: Call `reportProgress` within the direct function.
-  - ✅ **DO**: If intermediate progress status is needed *within* the long-running direct function, use standard logging: `log.info('Progress: Processing AI response...')`.
-
 ## Tool Definition and Execution
 
 ### Tool Structure
@@ -221,151 +179,78 @@ server.addTool({
 The `execute` function receives validated arguments and the FastMCP context:
 
 ```javascript
-// Standard signature
-execute: async (args, context) => {
-  // Tool implementation
-}
-
 // Destructured signature (recommended)
-execute: async (args, { log, reportProgress, session }) => {
+execute: async (args, { log, session }) => {
   // Tool implementation
 }
 ```
 
-- **args**: The first parameter contains all the validated parameters defined in the tool's schema.
-- **context**: The second parameter is an object containing `{ log, reportProgress, session }` provided by FastMCP.
-  - ✅ **DO**: Use `{ log, session }` when calling direct functions.
-  - ⚠️ **WARNING**: Avoid passing `reportProgress` down to direct functions due to client compatibility issues. See Progress Reporting Convention below.
+- **args**: Validated parameters.
+- **context**: Contains `{ log, session }` from FastMCP. (Removed `reportProgress`).
 
-### Standard Tool Execution Pattern
+### Standard Tool Execution Pattern with Path Normalization (Updated)
 
-The `execute` method within each MCP tool (in `mcp-server/src/tools/*.js`) should follow this standard pattern:
+To ensure consistent handling of project paths across different client environments (Windows, macOS, Linux, WSL) and input formats (e.g., `file:///...`, URI encoded paths), all MCP tool `execute` methods that require access to the project root **MUST** be wrapped with the `withNormalizedProjectRoot` Higher-Order Function (HOF).
 
-1.  **Log Entry**: Log the start of the tool execution with relevant arguments.
-2.  **Get Project Root**: Use the `getProjectRootFromSession(session, log)` utility (from [`tools/utils.js`](mdc:mcp-server/src/tools/utils.js)) to extract the project root path from the client session. Fall back to `args.projectRoot` if the session doesn't provide a root.
-3.  **Call Direct Function**: Invoke the corresponding `*Direct` function wrapper (e.g., `listTasksDirect` from [`task-master-core.js`](mdc:mcp-server/src/core/task-master-core.js)), passing an updated `args` object that includes the resolved `projectRoot`. Crucially, the third argument (context) passed to the direct function should **only include `{ log, session }`**. **Do NOT pass `reportProgress`**.
-    ```javascript
-    // Example call to a non-AI direct function
-    const result = await someDirectFunction({ ...args, projectRoot }, log); 
+This HOF, defined in [`mcp-server/src/tools/utils.js`](mdc:mcp-server/src/tools/utils.js), performs the following before calling the tool's core logic:
 
-    // Example call to an AI-based direct function
-    const resultAI = await someAIDirect({ ...args, projectRoot }, log, { session }); 
-    ```
-4.  **Handle Result**: Receive the result object (`{ success, data/error, fromCache }`) from the `*Direct` function.
-5.  **Format Response**: Pass this result object to the `handleApiResult` utility (from [`tools/utils.js`](mdc:mcp-server/src/tools/utils.js)) for standardized MCP response formatting and error handling.
-6.  **Return**: Return the formatted response object provided by `handleApiResult`.
+1.  **Determines the Raw Root:** It prioritizes `args.projectRoot` if provided by the client, otherwise it calls `getRawProjectRootFromSession` to extract the path from the session.
+2.  **Normalizes the Path:** It uses the `normalizeProjectRoot` helper to decode URIs, strip `file://` prefixes, fix potential Windows drive letter prefixes (e.g., `/C:/`), convert backslashes (`\`) to forward slashes (`/`), and resolve the path to an absolute path suitable for the server's OS.
+3.  **Injects Normalized Path:** It updates the `args` object by replacing the original `projectRoot` (or adding it) with the normalized, absolute path.
+4.  **Executes Original Logic:** It calls the original `execute` function body, passing the updated `args` object.
+
+**Implementation Example:**
 
 ```javascript
-// Example execute method structure for a tool calling an AI-based direct function
-import { getProjectRootFromSession, handleApiResult, createErrorResponse } from './utils.js';
-import { someAIDirectFunction } from '../core/task-master-core.js';
+// In mcp-server/src/tools/your-tool.js
+import {
+    handleApiResult,
+    createErrorResponse,
+    withNormalizedProjectRoot // <<< Import HOF
+} from './utils.js';
+import { yourDirectFunction } from '../core/task-master-core.js';
+import { findTasksJsonPath } from '../core/utils/path-utils.js'; // If needed
+
+export function registerYourTool(server) {
+    server.addTool({
+        name: "your_tool",
+        description: "...".
+        parameters: z.object({
+            // ... other parameters ...
+            projectRoot: z.string().optional().describe('...') // projectRoot is optional here, HOF handles fallback
+        }),
+        // Wrap the entire execute function
+        execute: withNormalizedProjectRoot(async (args, { log, session }) => {
+            // args.projectRoot is now guaranteed to be normalized and absolute
+            const { /* other args */, projectRoot } = args;
 
-// ... inside server.addTool({...})
-execute: async (args, { log, session }) => { // Note: reportProgress is omitted here
             try {
-    log.info(`Starting AI tool execution with args: ${JSON.stringify(args)}`);
+                log.info(`Executing your_tool with normalized root: ${projectRoot}`);
 
-    // 1. Get Project Root
-    let rootFolder = getProjectRootFromSession(session, log);
-    if (!rootFolder && args.projectRoot) { // Fallback if needed
-      rootFolder = args.projectRoot;
-      log.info(`Using project root from args as fallback: ${rootFolder}`);
-    }
+                // Resolve paths using the normalized projectRoot
+                let tasksPath = findTasksJsonPath({ projectRoot, file: args.file }, log);
 
-    // 2. Call AI-Based Direct Function (passing only log and session in context)
-    const result = await someAIDirectFunction({
-      ...args,
-      projectRoot: rootFolder // Ensure projectRoot is explicitly passed
-    }, log, { session }); // Pass session here, NO reportProgress
+                // Call direct function, passing normalized projectRoot if needed by direct func
+                const result = await yourDirectFunction(
+                    {
+                        /* other args */,
+                        projectRoot // Pass it if direct function needs it
+                    },
+                    log,
+                    { session }
+                );
 
-    // 3. Handle and Format Response
                 return handleApiResult(result, log);
-
             } catch (error) {
-    log.error(`Error during AI tool execution: ${error.message}`);
+                log.error(`Error in your_tool: ${error.message}`);
                 return createErrorResponse(error.message);
             }
+        }) // End HOF wrap
+    });
 }
 ```
 
-### Using AsyncOperationManager for Background Tasks
-
-For tools that execute potentially long-running operations *where the AI call is just one part* (e.g., `expand-task`, `update`), use the AsyncOperationManager. The `add-task` command, as refactored, does *not* require this in the MCP tool layer because the direct function handles the primary AI work and returns the final result synchronously from the perspective of the MCP tool.
-
-For tools that *do* use `AsyncOperationManager`:
-
-```javascript
-import { AsyncOperationManager } from '../utils/async-operation-manager.js'; // Correct path assuming utils location
-import { getProjectRootFromSession, createContentResponse, createErrorResponse } from './utils.js';
-import { someIntensiveDirect } from '../core/task-master-core.js';
-
-// ... inside server.addTool({...})
-execute: async (args, { log, session }) => { // Note: reportProgress omitted
-  try {
-    log.info(`Starting background operation with args: ${JSON.stringify(args)}`);
-
-    // 1. Get Project Root
-    let rootFolder = getProjectRootFromSession(session, log);
-    if (!rootFolder && args.projectRoot) {
-      rootFolder = args.projectRoot;
-      log.info(`Using project root from args as fallback: ${rootFolder}`);
-    }
-    
-    // Create operation description
-    const operationDescription = `Expanding task ${args.id}...`; // Example
-
-    // 2. Start async operation using AsyncOperationManager
-    const operation = AsyncOperationManager.createOperation(
-      operationDescription,
-      async (reportProgressCallback) => { // This callback is provided by AsyncOperationManager
-        // This runs in the background
-        try {
-          // Report initial progress *from the manager's callback*
-          reportProgressCallback({ progress: 0, status: 'Starting operation...' });
-
-          // Call the direct function (passing only session context)
-          const result = await someIntensiveDirect(
-            { ...args, projectRoot: rootFolder }, 
-            log, 
-            { session } // Pass session, NO reportProgress
-          );
-
-          // Report final progress *from the manager's callback*
-          reportProgressCallback({
-            progress: 100,
-            status: result.success ? 'Operation completed' : 'Operation failed',
-            result: result.data, // Include final data if successful
-            error: result.error   // Include error object if failed
-          });
-
-          return result; // Return the direct function's result
-        } catch (error) {
-          // Handle errors within the async task
-           reportProgressCallback({
-            progress: 100,
-            status: 'Operation failed critically',
-            error: { message: error.message, code: error.code || 'ASYNC_OPERATION_FAILED' }
-          });
-          throw error; // Re-throw for the manager to catch
-        }
-      }
-    );
-
-    // 3. Return immediate response with operation ID
-    return {
-        status: 202, // StatusCodes.ACCEPTED
-        body: {
-            success: true,
-            message: 'Operation started',
-            operationId: operation.id
-        }
-    };
-  } catch (error) {
-    log.error(`Error starting background operation: ${error.message}`);
-    return createErrorResponse(`Failed to start operation: ${error.message}`); // Use standard error response
-  }
-}
-```
+By using this HOF, the core logic within the `execute` method and any downstream functions (like `findTasksJsonPath` or direct functions) can reliably expect `args.projectRoot` to be a clean, absolute path suitable for the server environment.
 
 ### Project Initialization Tool
 
@@ -417,19 +302,13 @@ log.error(`Error occurred: ${error.message}`, { stack: error.stack });
 log.info('Progress: 50% - AI call initiated...'); // Example progress logging
 ```
 
-### Progress Reporting Convention
-
-- ⚠️ **DEPRECATED within Direct Functions**: The `reportProgress` function passed in the `context` object should **NOT** be called from within `*Direct` functions. Doing so can cause client-side validation errors due to missing/incorrect `progressToken` handling.
-- ✅ **DO**: For tools using `AsyncOperationManager`, use the `reportProgressCallback` function *provided by the manager* within the background task definition (as shown in the `AsyncOperationManager` example above) to report progress updates for the *overall operation*.
-- ✅ **DO**: If finer-grained progress needs to be indicated *during* the execution of a `*Direct` function (whether called directly or via `AsyncOperationManager`), use `log.info()` statements (e.g., `log.info('Progress: Parsing AI response...')`).
-
-### Session Usage Convention
+## Session Usage Convention
 
 The `session` object (destructured from `context`) contains authenticated session data and client information.
 
 - **Authentication**: Access user-specific data (`session.userId`, etc.) if authentication is implemented.
 - **Project Root**: The primary use in Task Master is accessing `session.roots` to determine the client's project root directory via the `getProjectRootFromSession` utility (from [`tools/utils.js`](mdc:mcp-server/src/tools/utils.js)). See the Standard Tool Execution Pattern above.
-- **Environment Variables**: The `session.env` object is critical for AI tools. Pass the `session` object to the `*Direct` function's context, and then to AI client utility functions (like `getAnthropicClientForMCP`) which will extract API keys and other relevant environment settings (e.g., `MODEL`, `MAX_TOKENS`) from `session.env`.
+- **Environment Variables**: The `session.env` object provides access to environment variables set in the MCP client configuration (e.g., `.cursor/mcp.json`). This is the **primary mechanism** for the unified AI service layer (`ai-services-unified.js`) to securely access **API keys** when called from MCP context.
 - **Capabilities**: Can be used to check client capabilities (`session.clientCapabilities`).
 
 ## Direct Function Wrappers (`*Direct`)
@@ -438,24 +317,25 @@ These functions, located in `mcp-server/src/core/direct-functions/`, form the co
 
 - **Purpose**: Bridge MCP tools and core Task Master modules (`scripts/modules/*`). Handle AI interactions if applicable.
 - **Responsibilities**:
-  - Receive `args` (including the `projectRoot` determined by the tool), `log` object, and optionally a `context` object (containing **only `{ session }` if needed).
-  - **Find `tasks.json`**: Use `findTasksJsonPath(args, log)` from [`core/utils/path-utils.js`](mdc:mcp-server/src/core/utils/path-utils.js).
-  - Validate arguments specific to the core logic.
-  - **Handle AI Logic (if applicable)**: Initialize AI clients (using `session` from context), build prompts, make AI calls, parse responses.
-  - **Implement Caching (if applicable)**: Use `getCachedOrExecute` from [`tools/utils.js`](mdc:mcp-server/src/tools/utils.js) for read operations.
-  - **Call Core Logic**: Call the underlying function from the core Task Master modules, passing necessary data (including AI results if applicable).
-    - ✅ **DO**: Pass `outputFormat: 'json'` (or similar) to the core function if it might produce console output.
-    - ✅ **DO**: Wrap the core function call with `enableSilentMode/disableSilentMode` if necessary.
-  - Handle errors gracefully (AI errors, core logic errors, file errors).
-  - Return a standardized result object: `{ success: boolean, data?: any, error?: { code: string, message: string }, fromCache?: boolean }`.
-  - ❌ **DON'T**: Call `reportProgress`. Use `log.info` for progress indication if needed.
+  - Receive `args` (including `projectRoot`), `log`, and optionally `{ session }` context.
+  - Find `tasks.json` using `findTasksJsonPath`.
+  - Validate arguments.
+  - **Implement Caching (if applicable)**: Use `getCachedOrExecute`.
+  - **Call Core Logic**: Invoke function from `scripts/modules/*`.
+    - Pass `outputFormat: 'json'` if applicable.
+    - Wrap with `enableSilentMode/disableSilentMode` if needed.
+    - Pass `{ mcpLog: logWrapper, session }` context if core logic needs it.
+  - Handle errors.
+  - Return standardized result object.
+  - ❌ **DON'T**: Call `reportProgress`.
+  - ❌ **DON'T**: Initialize AI clients or call AI services directly.
 
 ## Key Principles
 
 - **Prefer Direct Function Calls**: MCP tools should always call `*Direct` wrappers instead of `executeTaskMasterCommand`.
 - **Standardized Execution Flow**: Follow the pattern: MCP Tool -> `getProjectRootFromSession` -> `*Direct` Function -> Core Logic / AI Logic.
 - **Path Resolution via Direct Functions**: The `*Direct` function is responsible for finding the exact `tasks.json` path using `findTasksJsonPath`, relying on the `projectRoot` passed in `args`.
-- **AI Logic in Direct Functions**: For AI-based tools, the `*Direct` function handles AI client initialization, calls, and parsing, using the `session` object passed in its context.
+- **AI Logic in Core Modules**: AI interactions (prompt building, calling unified service) reside within the core logic functions (`scripts/modules/*`), not direct functions.
 - **Silent Mode in Direct Functions**: Wrap *core function* calls (from `scripts/modules`) with `enableSilentMode()` and `disableSilentMode()` if they produce console output not handled by `outputFormat`. Do not wrap AI calls.
 - **Selective Async Processing**: Use `AsyncOperationManager` in the *MCP Tool layer* for operations involving multiple steps or long waits beyond a single AI call (e.g., file processing + AI call + file writing). Simple AI calls handled entirely within the `*Direct` function (like `addTaskDirect`) may not need it at the tool layer.
 - **No `reportProgress` in Direct Functions**: Do not pass or use `reportProgress` within `*Direct` functions. Use `log.info()` for internal progress or report progress from the `AsyncOperationManager` callback in the MCP tool layer.
@@ -642,3 +522,8 @@ Follow these steps to add MCP support for an existing Task Master command (see [
       // Add more functions as implemented
     };
     ```
+
+## Telemetry Integration
+
+- Direct functions calling core logic that involves AI should receive and pass through `telemetryData` within their successful `data` payload. See [`telemetry.mdc`](mdc:.cursor/rules/telemetry.mdc) for the standard pattern.
+- MCP tools use `handleApiResult`, which ensures the `data` object (potentially including `telemetryData`) from the direct function is correctly included in the final response.

.cursor/rules/new_features.mdc

@@ -3,7 +3,6 @@ description: Guidelines for integrating new features into the Task Master CLI
 globs: scripts/modules/*.js
 alwaysApply: false
 ---
-
 # Task Master Feature Integration Guidelines
 
 ## Feature Placement Decision Process
@@ -25,11 +24,17 @@ alwaysApply: false
 The standard pattern for adding a feature follows this workflow:
 
 1. **Core Logic**: Implement the business logic in the appropriate module (e.g., [`task-manager.js`](mdc:scripts/modules/task-manager.js)).
-2. **UI Components**: Add any display functions to [`ui.js`](mdc:scripts/modules/ui.js) following [`ui.mdc`](mdc:.cursor/rules/ui.mdc).
-3. **Command Integration**: Add the CLI command to [`commands.js`](mdc:scripts/modules/commands.js) following [`commands.mdc`](mdc:.cursor/rules/commands.mdc).
-4. **Testing**: Write tests for all components of the feature (following [`tests.mdc`](mdc:.cursor/rules/tests.mdc))
-5. **Configuration**: Update any configuration in [`utils.js`](mdc:scripts/modules/utils.js) if needed, following [`utilities.mdc`](mdc:.cursor/rules/utilities.mdc).
-6. **Documentation**: Update help text and documentation in [dev_workflow.mdc](mdc:scripts/modules/dev_workflow.mdc)
+2. **AI Integration (If Applicable)**: 
+   - Import necessary service functions (e.g., `generateTextService`, `streamTextService`) from [`ai-services-unified.js`](mdc:scripts/modules/ai-services-unified.js).
+   - Prepare parameters (`role`, `session`, `systemPrompt`, `prompt`).
+   - Call the service function.
+   - Handle the response (direct text or stream object).
+   - **Important**: Prefer `generateTextService` for calls sending large context (like stringified JSON) where incremental display is not needed. See [`ai_services.mdc`](mdc:.cursor/rules/ai_services.mdc) for detailed usage patterns and cautions.
+3. **UI Components**: Add any display functions to [`ui.js`](mdc:scripts/modules/ui.js) following [`ui.mdc`](mdc:.cursor/rules/ui.mdc).
+4. **Command Integration**: Add the CLI command to [`commands.js`](mdc:scripts/modules/commands.js) following [`commands.mdc`](mdc:.cursor/rules/commands.mdc).
+5. **Testing**: Write tests for all components of the feature (following [`tests.mdc`](mdc:.cursor/rules/tests.mdc))
+6. **Configuration**: Update configuration settings or add new ones in [`config-manager.js`](mdc:scripts/modules/config-manager.js) and ensure getters/setters are appropriate. Update documentation in [`utilities.mdc`](mdc:.cursor/rules/utilities.mdc) and [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc). Update the `.taskmasterconfig` structure if needed.
+7. **Documentation**: Update help text and documentation in [`dev_workflow.mdc`](mdc:.cursor/rules/dev_workflow.mdc) and [`taskmaster.mdc`](mdc:.cursor/rules/taskmaster.mdc).
 
 ## Critical Checklist for New Features
 
@@ -190,6 +195,8 @@ The standard pattern for adding a feature follows this workflow:
   - ✅ **DO**: If an MCP tool fails with vague errors (e.g., JSON parsing issues like `Unexpected token ... is not valid JSON`), **try running the equivalent CLI command directly in the terminal** (e.g., `task-master expand --all`). CLI output often provides much more specific error messages (like missing function definitions or stack traces from the core logic) that pinpoint the root cause.
   - ❌ **DON'T**: Rely solely on MCP logs if the error is unclear; use the CLI as a complementary debugging tool for core logic issues.
 
+- **Telemetry Integration**: Ensure AI calls correctly handle and propagate `telemetryData` as described in [`telemetry.mdc`](mdc:.cursor/rules/telemetry.mdc).
+
 ```javascript
 // 1. CORE LOGIC: Add function to appropriate module (example in task-manager.js)
 /**
@@ -211,7 +218,29 @@ export {
 ```
 
 ```javascript
-// 2. UI COMPONENTS: Add display function to ui.js
+// 2. AI Integration: Add import and use necessary service functions
+import { generateTextService } from './ai-services-unified.js';
+
+// Example usage:
+async function handleAIInteraction() {
+  const role = 'user';
+  const session = 'exampleSession';
+  const systemPrompt = 'You are a helpful assistant.';
+  const prompt = 'What is the capital of France?';
+
+  const result = await generateTextService(role, session, systemPrompt, prompt);
+  console.log(result);
+}
+
+// Export from the module
+export {
+  // ... existing exports ...
+  handleAIInteraction,
+};
+```
+
+```javascript
+// 3. UI COMPONENTS: Add display function to ui.js
 /**
  * Display archive operation results
  * @param {string} archivePath - Path to the archive file
@@ -232,7 +261,7 @@ export {
 ```
 
 ```javascript
-// 3. COMMAND INTEGRATION: Add to commands.js
+// 4. COMMAND INTEGRATION: Add to commands.js
 import { archiveTasks } from './task-manager.js';
 import { displayArchiveResults } from './ui.js';
 
@@ -452,7 +481,7 @@ npm test
 For each new feature:
 
 1. Add help text to the command definition
-2. Update [`dev_workflow.mdc`](mdc:scripts/modules/dev_workflow.mdc) with command reference
+2. Update [`dev_workflow.mdc`](mdc:.cursor/rules/dev_workflow.mdc) with command reference
 3. Consider updating [`architecture.mdc`](mdc:.cursor/rules/architecture.mdc) if the feature significantly changes module responsibilities.
 
 Follow the existing command reference format:
@@ -495,14 +524,24 @@ Integrating Task Master commands with the MCP server (for use by tools like Curs
 
 4.  **Create MCP Tool (`mcp-server/src/tools/`)**:
     - Create a new file (e.g., `your-command.js`) using **kebab-case**.
-    - Import `zod`, `handleApiResult`, `createErrorResponse`, **`getProjectRootFromSession`**, and your `yourCommandDirect` function.
+    - Import `zod`, `handleApiResult`, **`withNormalizedProjectRoot` HOF**, and your `yourCommandDirect` function.
     - Implement `registerYourCommandTool(server)`.
-    - Define the tool `name` using **snake_case** (e.g., `your_command`).
-    - Define the `parameters` using `zod`. **Crucially, define `projectRoot` as optional**: `projectRoot: z.string().optional().describe(...)`. Include `file` if applicable.
-    - Implement the standard `async execute(args, { log, reportProgress, session })` method:
-      - Get `rootFolder` using `getProjectRootFromSession` (with fallback to `args.projectRoot`).
-      - Call `yourCommandDirect({ ...args, projectRoot: rootFolder }, log)`. 
-      - Pass the result to `handleApiResult(result, log, 'Error Message')`.
+    - **Define parameters**: Make `projectRoot` optional (`z.string().optional().describe(...)`) as the HOF handles fallback.
+    - Consider if this operation should run in the background using `AsyncOperationManager`.
+    - Implement the standard `execute` method **wrapped with `withNormalizedProjectRoot`**:
+      ```javascript
+      execute: withNormalizedProjectRoot(async (args, { log, session }) => {
+          // args.projectRoot is now normalized
+          const { projectRoot /*, other args */ } = args;
+          // ... resolve tasks path if needed using normalized projectRoot ...
+          const result = await yourCommandDirect(
+              { /* other args */, projectRoot /* if needed by direct func */ }, 
+              log, 
+              { session }
+          );
+          return handleApiResult(result, log);
+      })
+      ```
 
 5.  **Register Tool**: Import and call `registerYourCommandTool` in `mcp-server/src/tools/index.js`.
 

.cursor/rules/self_improve.mdc

@@ -69,5 +69,4 @@ alwaysApply: true
   - Update references to external docs
   - Maintain links between related rules
   - Document breaking changes
-
 Follow [cursor_rules.mdc](mdc:.cursor/rules/cursor_rules.mdc) for proper rule formatting and structure.

.cursor/rules/taskmaster.mdc

@@ -3,14 +3,13 @@ description: Comprehensive reference for Taskmaster MCP tools and CLI commands.
 globs: **/*
 alwaysApply: true
 ---
-
 # Taskmaster Tool & Command Reference
 
-This document provides a detailed reference for interacting with Taskmaster, covering both the recommended MCP tools (for integrations like Cursor) and the corresponding `task-master` CLI commands (for direct user interaction or fallback).
+This document provides a detailed reference for interacting with Taskmaster, covering both the recommended MCP tools, suitable for integrations like Cursor, and the corresponding `task-master` CLI commands, designed for direct user interaction or fallback.
 
-**Note:** For interacting with Taskmaster programmatically or via integrated tools, using the **MCP tools is strongly recommended** due to better performance, structured data, and error handling. The CLI commands serve as a user-friendly alternative and fallback. See [`mcp.mdc`](mdc:.cursor/rules/mcp.mdc) for MCP implementation details and [`commands.mdc`](mdc:.cursor/rules/commands.mdc) for CLI implementation guidelines.
+**Note:** For interacting with Taskmaster programmatically or via integrated tools, using the **MCP tools is strongly recommended** due to better performance, structured data, and error handling. The CLI commands serve as a user-friendly alternative and fallback. 
 
-**Important:** Several MCP tools involve AI processing and are long-running operations that may take up to a minute to complete. When using these tools, always inform users that the operation is in progress and to wait patiently for results. The AI-powered tools include: `parse_prd`, `analyze_project_complexity`, `update_subtask`, `update_task`, `update`, `expand_all`, `expand_task`, and `add_task`.
+**Important:** Several MCP tools involve AI processing... The AI-powered tools include `parse_prd`, `analyze_project_complexity`, `update_subtask`, `update_task`, `update`, `expand_all`, `expand_task`, and `add_task`.
 
 ---
 
@@ -24,34 +23,64 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **Key CLI Options:**
     *   `--name <name>`: `Set the name for your project in Taskmaster's configuration.`
     *   `--description <text>`: `Provide a brief description for your project.`
-    *   `--version <version>`: `Set the initial version for your project (e.g., '0.1.0').`
+    *   `--version <version>`: `Set the initial version for your project, e.g., '0.1.0'.`
     *   `-y, --yes`: `Initialize Taskmaster quickly using default settings without interactive prompts.`
 *   **Usage:** Run this once at the beginning of a new project.
 *   **MCP Variant Description:** `Set up the basic Taskmaster file structure and configuration in the current directory for a new project by running the 'task-master init' command.`
 *   **Key MCP Parameters/Options:**
     *   `projectName`: `Set the name for your project.` (CLI: `--name <name>`)
     *   `projectDescription`: `Provide a brief description for your project.` (CLI: `--description <text>`)
-    *   `projectVersion`: `Set the initial version for your project (e.g., '0.1.0').` (CLI: `--version <version>`)
+    *   `projectVersion`: `Set the initial version for your project, e.g., '0.1.0'.` (CLI: `--version <version>`)
     *   `authorName`: `Author name.` (CLI: `--author <author>`)
-    *   `skipInstall`: `Skip installing dependencies (default: false).` (CLI: `--skip-install`)
-    *   `addAliases`: `Add shell aliases (tm, taskmaster) (default: false).` (CLI: `--aliases`)
-    *   `yes`: `Skip prompts and use defaults/provided arguments (default: false).` (CLI: `-y, --yes`)
+    *   `skipInstall`: `Skip installing dependencies. Default is false.` (CLI: `--skip-install`)
+    *   `addAliases`: `Add shell aliases tm and taskmaster. Default is false.` (CLI: `--aliases`)
+    *   `yes`: `Skip prompts and use defaults/provided arguments. Default is false.` (CLI: `-y, --yes`)
 *   **Usage:** Run this once at the beginning of a new project, typically via an integrated tool like Cursor. Operates on the current working directory of the MCP server. 
-
+*   **Important:** Once complete, you *MUST* parse a prd in order to generate tasks. There will be no tasks files until then. The next step after initializing should be to create a PRD using the example PRD in scripts/example_prd.txt. 
 
 ### 2. Parse PRD (`parse_prd`)
 
 *   **MCP Tool:** `parse_prd`
 *   **CLI Command:** `task-master parse-prd [file] [options]`
-*   **Description:** `Parse a Product Requirements Document (PRD) or text file with Taskmaster to automatically generate an initial set of tasks in tasks.json.`
+*   **Description:** `Parse a Product Requirements Document, PRD, or text file with Taskmaster to automatically generate an initial set of tasks in tasks.json.`
 *   **Key Parameters/Options:**
     *   `input`: `Path to your PRD or requirements text file that Taskmaster should parse for tasks.` (CLI: `[file]` positional or `-i, --input <file>`)
-    *   `output`: `Specify where Taskmaster should save the generated 'tasks.json' file (default: 'tasks/tasks.json').` (CLI: `-o, --output <file>`)
+    *   `output`: `Specify where Taskmaster should save the generated 'tasks.json' file. Defaults to 'tasks/tasks.json'.` (CLI: `-o, --output <file>`)
     *   `numTasks`: `Approximate number of top-level tasks Taskmaster should aim to generate from the document.` (CLI: `-n, --num-tasks <number>`)
     *   `force`: `Use this to allow Taskmaster to overwrite an existing 'tasks.json' without asking for confirmation.` (CLI: `-f, --force`)
 *   **Usage:** Useful for bootstrapping a project from an existing requirements document.
-*   **Notes:** Task Master will strictly adhere to any specific requirements mentioned in the PRD (libraries, database schemas, frameworks, tech stacks, etc.) while filling in any gaps where the PRD isn't fully specified. Tasks are designed to provide the most direct implementation path while avoiding over-engineering.
-*   **Important:** This MCP tool makes AI calls and can take up to a minute to complete. Please inform users to hang tight while the operation is in progress.
+*   **Notes:** Task Master will strictly adhere to any specific requirements mentioned in the PRD, such as libraries, database schemas, frameworks, tech stacks, etc., while filling in any gaps where the PRD isn't fully specified. Tasks are designed to provide the most direct implementation path while avoiding over-engineering.
+*   **Important:** This MCP tool makes AI calls and can take up to a minute to complete. Please inform users to hang tight while the operation is in progress. If the user does not have a PRD, suggest discussing their idea and then use the example PRD in `scripts/example_prd.txt` as a template for creating the PRD based on their idea, for use with `parse-prd`.
+
+---
+
+## AI Model Configuration
+
+### 2. Manage Models (`models`)
+*   **MCP Tool:** `models`
+*   **CLI Command:** `task-master models [options]`
+*   **Description:** `View the current AI model configuration or set specific models for different roles (main, research, fallback). Allows setting custom model IDs for Ollama and OpenRouter.`
+*   **Key MCP Parameters/Options:**
+    *   `setMain <model_id>`: `Set the primary model ID for task generation/updates.` (CLI: `--set-main <model_id>`)
+    *   `setResearch <model_id>`: `Set the model ID for research-backed operations.` (CLI: `--set-research <model_id>`)
+    *   `setFallback <model_id>`: `Set the model ID to use if the primary fails.` (CLI: `--set-fallback <model_id>`)
+    *   `ollama <boolean>`: `Indicates the set model ID is a custom Ollama model.` (CLI: `--ollama`)
+    *   `openrouter <boolean>`: `Indicates the set model ID is a custom OpenRouter model.` (CLI: `--openrouter`)
+    *   `listAvailableModels <boolean>`: `If true, lists available models not currently assigned to a role.` (CLI: No direct equivalent; CLI lists available automatically)
+    *   `projectRoot <string>`: `Optional. Absolute path to the project root directory.` (CLI: Determined automatically)
+*   **Key CLI Options:**
+    *   `--set-main <model_id>`: `Set the primary model.`
+    *   `--set-research <model_id>`: `Set the research model.`
+    *   `--set-fallback <model_id>`: `Set the fallback model.`
+    *   `--ollama`: `Specify that the provided model ID is for Ollama (use with --set-*).`
+    *   `--openrouter`: `Specify that the provided model ID is for OpenRouter (use with --set-*). Validates against OpenRouter API.`
+    *   `--setup`: `Run interactive setup to configure models, including custom Ollama/OpenRouter IDs.`
+*   **Usage (MCP):** Call without set flags to get current config. Use `setMain`, `setResearch`, or `setFallback` with a valid model ID to update the configuration. Use `listAvailableModels: true` to get a list of unassigned models. To set a custom model, provide the model ID and set `ollama: true` or `openrouter: true`.
+*   **Usage (CLI):** Run without flags to view current configuration and available models. Use set flags to update specific roles. Use `--setup` for guided configuration, including custom models. To set a custom model via flags, use `--set-<role>=<model_id>` along with either `--ollama` or `--openrouter`.
+*   **Notes:** Configuration is stored in `.taskmasterconfig` in the project root. This command/tool modifies that file. Use `listAvailableModels` or `task-master models` to see internally supported models. OpenRouter custom models are validated against their live API. Ollama custom models are not validated live.
+*   **API note:** API keys for selected AI providers (based on their model) need to exist in the mcp.json file to be accessible in MCP context. The API keys must be present in the local .env file for the CLI to be able to read them.
+*   **Model costs:** The costs in supported models are expressed in dollars. An input/output value of 3 is $3.00. A value of 0.8 is $0.80. 
+*   **Warning:** DO NOT MANUALLY EDIT THE .taskmasterconfig FILE. Use the included commands either in the MCP or CLI format as needed. Always prioritize MCP tools when available and use the CLI as a fallback.
 
 ---
 
@@ -63,9 +92,9 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **CLI Command:** `task-master list [options]`
 *   **Description:** `List your Taskmaster tasks, optionally filtering by status and showing subtasks.`
 *   **Key Parameters/Options:**
-    *   `status`: `Show only Taskmaster tasks matching this status (e.g., 'pending', 'done').` (CLI: `-s, --status <status>`)
+    *   `status`: `Show only Taskmaster tasks matching this status, e.g., 'pending' or 'done'.` (CLI: `-s, --status <status>`)
     *   `withSubtasks`: `Include subtasks indented under their parent tasks in the list.` (CLI: `--with-subtasks`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Get an overview of the project status, often used at the start of a work session.
 
 ### 4. Get Next Task (`next_task`)
@@ -74,7 +103,7 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **CLI Command:** `task-master next [options]`
 *   **Description:** `Ask Taskmaster to show the next available task you can work on, based on status and completed dependencies.`
 *   **Key Parameters/Options:**
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Identify what to work on next according to the plan.
 
 ### 5. Get Task Details (`get_task`)
@@ -83,8 +112,8 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **CLI Command:** `task-master show [id] [options]`
 *   **Description:** `Display detailed information for a specific Taskmaster task or subtask by its ID.`
 *   **Key Parameters/Options:**
-    *   `id`: `Required. The ID of the Taskmaster task (e.g., '15') or subtask (e.g., '15.2') you want to view.` (CLI: `[id]` positional or `-i, --id <id>`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `id`: `Required. The ID of the Taskmaster task, e.g., '15', or subtask, e.g., '15.2', you want to view.` (CLI: `[id]` positional or `-i, --id <id>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Understand the full details, implementation notes, and test strategy for a specific task before starting work.
 
 ---
@@ -97,10 +126,11 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **CLI Command:** `task-master add-task [options]`
 *   **Description:** `Add a new task to Taskmaster by describing it; AI will structure it.`
 *   **Key Parameters/Options:**
-    *   `prompt`: `Required. Describe the new task you want Taskmaster to create (e.g., "Implement user authentication using JWT").` (CLI: `-p, --prompt <text>`)
-    *   `dependencies`: `Specify the IDs of any Taskmaster tasks that must be completed before this new one can start (e.g., '12,14').` (CLI: `-d, --dependencies <ids>`)
-    *   `priority`: `Set the priority for the new task ('high', 'medium', 'low'; default: 'medium').` (CLI: `--priority <priority>`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `prompt`: `Required. Describe the new task you want Taskmaster to create, e.g., "Implement user authentication using JWT".` (CLI: `-p, --prompt <text>`)
+    *   `dependencies`: `Specify the IDs of any Taskmaster tasks that must be completed before this new one can start, e.g., '12,14'.` (CLI: `-d, --dependencies <ids>`)
+    *   `priority`: `Set the priority for the new task: 'high', 'medium', or 'low'. Default is 'medium'.` (CLI: `--priority <priority>`)
+    *   `research`: `Enable Taskmaster to use the research role for potentially more informed task creation.` (CLI: `-r, --research`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Quickly add newly identified tasks during development.
 *   **Important:** This MCP tool makes AI calls and can take up to a minute to complete. Please inform users to hang tight while the operation is in progress.
 
@@ -112,13 +142,13 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **Key Parameters/Options:**
     *   `id` / `parent`: `Required. The ID of the Taskmaster task that will be the parent.` (MCP: `id`, CLI: `-p, --parent <id>`)
     *   `taskId`: `Use this if you want to convert an existing top-level Taskmaster task into a subtask of the specified parent.` (CLI: `-i, --task-id <id>`)
-    *   `title`: `Required (if not using taskId). The title for the new subtask Taskmaster should create.` (CLI: `-t, --title <title>`)
+    *   `title`: `Required if not using taskId. The title for the new subtask Taskmaster should create.` (CLI: `-t, --title <title>`)
     *   `description`: `A brief description for the new subtask.` (CLI: `-d, --description <text>`)
     *   `details`: `Provide implementation notes or details for the new subtask.` (CLI: `--details <text>`)
-    *   `dependencies`: `Specify IDs of other tasks or subtasks (e.g., '15', '16.1') that must be done before this new subtask.` (CLI: `--dependencies <ids>`)
-    *   `status`: `Set the initial status for the new subtask (default: 'pending').` (CLI: `-s, --status <status>`)
+    *   `dependencies`: `Specify IDs of other tasks or subtasks, e.g., '15' or '16.1', that must be done before this new subtask.` (CLI: `--dependencies <ids>`)
+    *   `status`: `Set the initial status for the new subtask. Default is 'pending'.` (CLI: `-s, --status <status>`)
     *   `skipGenerate`: `Prevent Taskmaster from automatically regenerating markdown task files after adding the subtask.` (CLI: `--skip-generate`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Break down tasks manually or reorganize existing tasks.
 
 ### 8. Update Tasks (`update`)
@@ -127,10 +157,10 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **CLI Command:** `task-master update [options]`
 *   **Description:** `Update multiple upcoming tasks in Taskmaster based on new context or changes, starting from a specific task ID.`
 *   **Key Parameters/Options:**
-    *   `from`: `Required. The ID of the first task Taskmaster should update. All tasks with this ID or higher (and not 'done') will be considered.` (CLI: `--from <id>`)
-    *   `prompt`: `Required. Explain the change or new context for Taskmaster to apply to the tasks (e.g., "We are now using React Query instead of Redux Toolkit for data fetching").` (CLI: `-p, --prompt <text>`)
-    *   `research`: `Enable Taskmaster to use Perplexity AI for more informed updates based on external knowledge (requires PERPLEXITY_API_KEY).` (CLI: `-r, --research`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `from`: `Required. The ID of the first task Taskmaster should update. All tasks with this ID or higher that are not 'done' will be considered.` (CLI: `--from <id>`)
+    *   `prompt`: `Required. Explain the change or new context for Taskmaster to apply to the tasks, e.g., "We are now using React Query instead of Redux Toolkit for data fetching".` (CLI: `-p, --prompt <text>`)
+    *   `research`: `Enable Taskmaster to use the research role for more informed updates. Requires appropriate API key.` (CLI: `-r, --research`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Handle significant implementation changes or pivots that affect multiple future tasks. Example CLI: `task-master update --from='18' --prompt='Switching to React Query.\nNeed to refactor data fetching...'`
 *   **Important:** This MCP tool makes AI calls and can take up to a minute to complete. Please inform users to hang tight while the operation is in progress.
 
@@ -138,12 +168,12 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 
 *   **MCP Tool:** `update_task`
 *   **CLI Command:** `task-master update-task [options]`
-*   **Description:** `Modify a specific Taskmaster task (or subtask) by its ID, incorporating new information or changes.`
+*   **Description:** `Modify a specific Taskmaster task or subtask by its ID, incorporating new information or changes.`
 *   **Key Parameters/Options:**
-    *   `id`: `Required. The specific ID of the Taskmaster task (e.g., '15') or subtask (e.g., '15.2') you want to update.` (CLI: `-i, --id <id>`)
+    *   `id`: `Required. The specific ID of the Taskmaster task, e.g., '15', or subtask, e.g., '15.2', you want to update.` (CLI: `-i, --id <id>`)
     *   `prompt`: `Required. Explain the specific changes or provide the new information Taskmaster should incorporate into this task.` (CLI: `-p, --prompt <text>`)
-    *   `research`: `Enable Taskmaster to use Perplexity AI for more informed updates (requires PERPLEXITY_API_KEY).` (CLI: `-r, --research`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `research`: `Enable Taskmaster to use the research role for more informed updates. Requires appropriate API key.` (CLI: `-r, --research`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Refine a specific task based on new understanding or feedback. Example CLI: `task-master update-task --id='15' --prompt='Clarification: Use PostgreSQL instead of MySQL.\nUpdate schema details...'`
 *   **Important:** This MCP tool makes AI calls and can take up to a minute to complete. Please inform users to hang tight while the operation is in progress.
 
@@ -153,10 +183,10 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **CLI Command:** `task-master update-subtask [options]`
 *   **Description:** `Append timestamped notes or details to a specific Taskmaster subtask without overwriting existing content. Intended for iterative implementation logging.`
 *   **Key Parameters/Options:**
-    *   `id`: `Required. The specific ID of the Taskmaster subtask (e.g., '15.2') you want to add information to.` (CLI: `-i, --id <id>`)
+    *   `id`: `Required. The specific ID of the Taskmaster subtask, e.g., '15.2', you want to add information to.` (CLI: `-i, --id <id>`)
     *   `prompt`: `Required. Provide the information or notes Taskmaster should append to the subtask's details. Ensure this adds *new* information not already present.` (CLI: `-p, --prompt <text>`)
-    *   `research`: `Enable Taskmaster to use Perplexity AI for more informed updates (requires PERPLEXITY_API_KEY).` (CLI: `-r, --research`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `research`: `Enable Taskmaster to use the research role for more informed updates. Requires appropriate API key.` (CLI: `-r, --research`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Add implementation notes, code snippets, or clarifications to a subtask during development. Before calling, review the subtask's current details to append only fresh insights, helping to build a detailed log of the implementation journey and avoid redundancy. Example CLI: `task-master update-subtask --id='15.2' --prompt='Discovered that the API requires header X.\nImplementation needs adjustment...'`
 *   **Important:** This MCP tool makes AI calls and can take up to a minute to complete. Please inform users to hang tight while the operation is in progress.
 
@@ -164,11 +194,11 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 
 *   **MCP Tool:** `set_task_status`
 *   **CLI Command:** `task-master set-status [options]`
-*   **Description:** `Update the status of one or more Taskmaster tasks or subtasks (e.g., 'pending', 'in-progress', 'done').`
+*   **Description:** `Update the status of one or more Taskmaster tasks or subtasks, e.g., 'pending', 'in-progress', 'done'.`
 *   **Key Parameters/Options:**
-    *   `id`: `Required. The ID(s) of the Taskmaster task(s) or subtask(s) (e.g., '15', '15.2', '16,17.1') to update.` (CLI: `-i, --id <id>`)
-    *   `status`: `Required. The new status to set (e.g., 'done', 'pending', 'in-progress', 'review', 'cancelled').` (CLI: `-s, --status <status>`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `id`: `Required. The ID(s) of the Taskmaster task(s) or subtask(s), e.g., '15', '15.2', or '16,17.1', to update.` (CLI: `-i, --id <id>`)
+    *   `status`: `Required. The new status to set, e.g., 'done', 'pending', 'in-progress', 'review', 'cancelled'.` (CLI: `-s, --status <status>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Mark progress as tasks move through the development cycle.
 
 ### 12. Remove Task (`remove_task`)
@@ -177,9 +207,9 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **CLI Command:** `task-master remove-task [options]`
 *   **Description:** `Permanently remove a task or subtask from the Taskmaster tasks list.`
 *   **Key Parameters/Options:**
-    *   `id`: `Required. The ID of the Taskmaster task (e.g., '5') or subtask (e.g., '5.2') to permanently remove.` (CLI: `-i, --id <id>`)
+    *   `id`: `Required. The ID of the Taskmaster task, e.g., '5', or subtask, e.g., '5.2', to permanently remove.` (CLI: `-i, --id <id>`)
     *   `yes`: `Skip the confirmation prompt and immediately delete the task.` (CLI: `-y, --yes`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Permanently delete tasks or subtasks that are no longer needed in the project.
 *   **Notes:** Use with caution as this operation cannot be undone. Consider using 'blocked', 'cancelled', or 'deferred' status instead if you just want to exclude a task from active planning but keep it for reference. The command automatically cleans up dependency references in other tasks.
 
@@ -191,28 +221,28 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 
 *   **MCP Tool:** `expand_task`
 *   **CLI Command:** `task-master expand [options]`
-*   **Description:** `Use Taskmaster's AI to break down a complex task (or all tasks) into smaller, manageable subtasks.`
+*   **Description:** `Use Taskmaster's AI to break down a complex task into smaller, manageable subtasks. Appends subtasks by default.`
 *   **Key Parameters/Options:**
     *   `id`: `The ID of the specific Taskmaster task you want to break down into subtasks.` (CLI: `-i, --id <id>`)
-    *   `num`: `Suggests how many subtasks Taskmaster should aim to create (uses complexity analysis by default).` (CLI: `-n, --num <number>`)
-    *   `research`: `Enable Taskmaster to use Perplexity AI for more informed subtask generation (requires PERPLEXITY_API_KEY).` (CLI: `-r, --research`)
-    *   `prompt`: `Provide extra context or specific instructions to Taskmaster for generating the subtasks.` (CLI: `-p, --prompt <text>`)
-    *   `force`: `Use this to make Taskmaster replace existing subtasks with newly generated ones.` (CLI: `--force`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
-*   **Usage:** Generate a detailed implementation plan for a complex task before starting coding.
+    *   `num`: `Optional: Suggests how many subtasks Taskmaster should aim to create. Uses complexity analysis/defaults otherwise.` (CLI: `-n, --num <number>`)
+    *   `research`: `Enable Taskmaster to use the research role for more informed subtask generation. Requires appropriate API key.` (CLI: `-r, --research`)
+    *   `prompt`: `Optional: Provide extra context or specific instructions to Taskmaster for generating the subtasks.` (CLI: `-p, --prompt <text>`)
+    *   `force`: `Optional: If true, clear existing subtasks before generating new ones. Default is false (append).` (CLI: `--force`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
+*   **Usage:** Generate a detailed implementation plan for a complex task before starting coding. Automatically uses complexity report recommendations if available and `num` is not specified.
 *   **Important:** This MCP tool makes AI calls and can take up to a minute to complete. Please inform users to hang tight while the operation is in progress.
 
 ### 14. Expand All Tasks (`expand_all`)
 
 *   **MCP Tool:** `expand_all`
 *   **CLI Command:** `task-master expand --all [options]` (Note: CLI uses the `expand` command with the `--all` flag)
-*   **Description:** `Tell Taskmaster to automatically expand all 'pending' tasks based on complexity analysis.`
+*   **Description:** `Tell Taskmaster to automatically expand all eligible pending/in-progress tasks based on complexity analysis or defaults. Appends subtasks by default.`
 *   **Key Parameters/Options:**
-    *   `num`: `Suggests how many subtasks Taskmaster should aim to create per task.` (CLI: `-n, --num <number>`)
-    *   `research`: `Enable Perplexity AI for more informed subtask generation (requires PERPLEXITY_API_KEY).` (CLI: `-r, --research`)
-    *   `prompt`: `Provide extra context for Taskmaster to apply generally during expansion.` (CLI: `-p, --prompt <text>`)
-    *   `force`: `Make Taskmaster replace existing subtasks.` (CLI: `--force`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `num`: `Optional: Suggests how many subtasks Taskmaster should aim to create per task.` (CLI: `-n, --num <number>`)
+    *   `research`: `Enable research role for more informed subtask generation. Requires appropriate API key.` (CLI: `-r, --research`)
+    *   `prompt`: `Optional: Provide extra context for Taskmaster to apply generally during expansion.` (CLI: `-p, --prompt <text>`)
+    *   `force`: `Optional: If true, clear existing subtasks before generating new ones for each eligible task. Default is false (append).` (CLI: `--force`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Useful after initial task generation or complexity analysis to break down multiple tasks at once.
 *   **Important:** This MCP tool makes AI calls and can take up to a minute to complete. Please inform users to hang tight while the operation is in progress.
 
@@ -222,9 +252,9 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **CLI Command:** `task-master clear-subtasks [options]`
 *   **Description:** `Remove all subtasks from one or more specified Taskmaster parent tasks.`
 *   **Key Parameters/Options:**
-    *   `id`: `The ID(s) of the Taskmaster parent task(s) whose subtasks you want to remove (e.g., '15', '16,18').` (Required unless using `all`) (CLI: `-i, --id <ids>`)
+    *   `id`: `The ID(s) of the Taskmaster parent task(s) whose subtasks you want to remove, e.g., '15' or '16,18'. Required unless using `all`.) (CLI: `-i, --id <ids>`)
     *   `all`: `Tell Taskmaster to remove subtasks from all parent tasks.` (CLI: `--all`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Used before regenerating subtasks with `expand_task` if the previous breakdown needs replacement.
 
 ### 16. Remove Subtask (`remove_subtask`)
@@ -233,10 +263,10 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **CLI Command:** `task-master remove-subtask [options]`
 *   **Description:** `Remove a subtask from its Taskmaster parent, optionally converting it into a standalone task.`
 *   **Key Parameters/Options:**
-    *   `id`: `Required. The ID(s) of the Taskmaster subtask(s) to remove (e.g., '15.2', '16.1,16.3').` (CLI: `-i, --id <id>`)
+    *   `id`: `Required. The ID(s) of the Taskmaster subtask(s) to remove, e.g., '15.2' or '16.1,16.3'.` (CLI: `-i, --id <id>`)
     *   `convert`: `If used, Taskmaster will turn the subtask into a regular top-level task instead of deleting it.` (CLI: `-c, --convert`)
     *   `skipGenerate`: `Prevent Taskmaster from automatically regenerating markdown task files after removing the subtask.` (CLI: `--skip-generate`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Delete unnecessary subtasks or promote a subtask to a top-level task.
 
 ---
@@ -250,8 +280,8 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **Description:** `Define a dependency in Taskmaster, making one task a prerequisite for another.`
 *   **Key Parameters/Options:**
     *   `id`: `Required. The ID of the Taskmaster task that will depend on another.` (CLI: `-i, --id <id>`)
-    *   `dependsOn`: `Required. The ID of the Taskmaster task that must be completed first (the prerequisite).` (CLI: `-d, --depends-on <id>`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `dependsOn`: `Required. The ID of the Taskmaster task that must be completed first, the prerequisite.` (CLI: `-d, --depends-on <id>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <path>`)
 *   **Usage:** Establish the correct order of execution between tasks.
 
 ### 18. Remove Dependency (`remove_dependency`)
@@ -262,7 +292,7 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **Key Parameters/Options:**
     *   `id`: `Required. The ID of the Taskmaster task you want to remove a prerequisite from.` (CLI: `-i, --id <id>`)
     *   `dependsOn`: `Required. The ID of the Taskmaster task that should no longer be a prerequisite.` (CLI: `-d, --depends-on <id>`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Update task relationships when the order of execution changes.
 
 ### 19. Validate Dependencies (`validate_dependencies`)
@@ -271,7 +301,7 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **CLI Command:** `task-master validate-dependencies [options]`
 *   **Description:** `Check your Taskmaster tasks for dependency issues (like circular references or links to non-existent tasks) without making changes.`
 *   **Key Parameters/Options:**
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Audit the integrity of your task dependencies.
 
 ### 20. Fix Dependencies (`fix_dependencies`)
@@ -280,7 +310,7 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **CLI Command:** `task-master fix-dependencies [options]`
 *   **Description:** `Automatically fix dependency issues (like circular references or links to non-existent tasks) in your Taskmaster tasks.`
 *   **Key Parameters/Options:**
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Clean up dependency errors automatically.
 
 ---
@@ -295,8 +325,8 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **Key Parameters/Options:**
     *   `output`: `Where to save the complexity analysis report (default: 'scripts/task-complexity-report.json').` (CLI: `-o, --output <file>`)
     *   `threshold`: `The minimum complexity score (1-10) that should trigger a recommendation to expand a task.` (CLI: `-t, --threshold <number>`)
-    *   `research`: `Enable Perplexity AI for more accurate complexity analysis (requires PERPLEXITY_API_KEY).` (CLI: `-r, --research`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `research`: `Enable research role for more accurate complexity analysis. Requires appropriate API key.` (CLI: `-r, --research`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Used before breaking down tasks to identify which ones need the most attention.
 *   **Important:** This MCP tool makes AI calls and can take up to a minute to complete. Please inform users to hang tight while the operation is in progress.
 
@@ -320,34 +350,33 @@ This document provides a detailed reference for interacting with Taskmaster, cov
 *   **Description:** `Create or update individual Markdown files for each task based on your tasks.json.`
 *   **Key Parameters/Options:**
     *   `output`: `The directory where Taskmaster should save the task files (default: in a 'tasks' directory).` (CLI: `-o, --output <directory>`)
-    *   `file`: `Path to your Taskmaster 'tasks.json' file (default relies on auto-detection).` (CLI: `-f, --file <file>`)
+    *   `file`: `Path to your Taskmaster 'tasks.json' file. Default relies on auto-detection.` (CLI: `-f, --file <file>`)
 *   **Usage:** Run this after making changes to tasks.json to keep individual task files up to date.
 
 ---
 
-## Environment Variables Configuration
+## Environment Variables Configuration (Updated)
 
-Taskmaster's behavior can be customized via environment variables. These affect both CLI and MCP server operation:
+Taskmaster primarily uses the **`.taskmasterconfig`** file (in project root) for configuration (models, parameters, logging level, etc.), managed via `task-master models --setup`.
 
-*   **ANTHROPIC_API_KEY** (Required): Your Anthropic API key for Claude.
-*   **MODEL**: Claude model to use (default: `claude-3-opus-20240229`). 
-*   **MAX_TOKENS**: Maximum tokens for AI responses (default: 8192).
-*   **TEMPERATURE**: Temperature for AI model responses (default: 0.7).
-*   **DEBUG**: Enable debug logging (`true`/`false`, default: `false`).
-*   **LOG_LEVEL**: Console output level (`debug`, `info`, `warn`, `error`, default: `info`).
-*   **DEFAULT_SUBTASKS**: Default number of subtasks for `expand` (default: 5).
-*   **DEFAULT_PRIORITY**: Default priority for new tasks (default: `medium`).
-*   **PROJECT_NAME**: Project name used in metadata.
-*   **PROJECT_VERSION**: Project version used in metadata.
-*   **PERPLEXITY_API_KEY**: API key for Perplexity AI (for `--research` flags).
-*   **PERPLEXITY_MODEL**: Perplexity model to use (default: `sonar-medium-online`).
+Environment variables are used **only** for sensitive API keys related to AI providers and specific overrides like the Ollama base URL:
 
-Set these in your `.env` file in the project root or in your environment before running Taskmaster.
+*   **API Keys (Required for corresponding provider):**
+    *   `ANTHROPIC_API_KEY`
+    *   `PERPLEXITY_API_KEY`
+    *   `OPENAI_API_KEY`
+    *   `GOOGLE_API_KEY`
+    *   `MISTRAL_API_KEY`
+    *   `AZURE_OPENAI_API_KEY` (Requires `AZURE_OPENAI_ENDPOINT` too)
+    *   `OPENROUTER_API_KEY`
+    *   `XAI_API_KEY`
+    *   `OLLANA_API_KEY` (Requires `OLLAMA_BASE_URL` too)
+*   **Endpoints (Optional/Provider Specific inside .taskmasterconfig):**
+    *   `AZURE_OPENAI_ENDPOINT`
+    *   `OLLAMA_BASE_URL` (Default: `http://localhost:11434/api`)
+
+**Set API keys** in your **`.env`** file in the project root (for CLI use) or within the `env` section of your **`.cursor/mcp.json`** file (for MCP/Cursor integration). All other settings (model choice, max tokens, temperature, log level, custom endpoints) are managed in `.taskmasterconfig` via `task-master models` command or `models` MCP tool.
 
 ---
 
-For implementation details:
-*   CLI commands: See [`commands.mdc`](mdc:.cursor/rules/commands.mdc)
-*   MCP server: See [`mcp.mdc`](mdc:.cursor/rules/mcp.mdc)
-*   Task structure: See [`tasks.mdc`](mdc:.cursor/rules/tasks.mdc)
-*   Workflow: See [`dev_workflow.mdc`](mdc:.cursor/rules/dev_workflow.mdc)
+For details on how these commands fit into the development process, see the [Development Workflow Guide](mdc:.cursor/rules/dev_workflow.mdc).

.cursor/rules/telemetry.mdc

@@ -0,0 +1,228 @@
+---
+description: Guidelines for integrating AI usage telemetry across Task Master.
+globs: scripts/modules/**/*.js,mcp-server/src/**/*.js
+alwaysApply: true
+---
+
+# AI Usage Telemetry Integration
+
+This document outlines the standard pattern for capturing, propagating, and handling AI usage telemetry data (cost, tokens, model, etc.) across the Task Master stack. This ensures consistent telemetry for both CLI and MCP interactions.
+
+## Overview
+
+Telemetry data is generated within the unified AI service layer ([`ai-services-unified.js`](mdc:scripts/modules/ai-services-unified.js)) and then passed upwards through the calling functions.
+
+- **Data Source**: [`ai-services-unified.js`](mdc:scripts/modules/ai-services-unified.js) (specifically its `generateTextService`, `generateObjectService`, etc.) returns an object like `{ mainResult: AI_CALL_OUTPUT, telemetryData: TELEMETRY_OBJECT }`.
+- **`telemetryData` Object Structure**:
+  ```json
+  {
+    "timestamp": "ISO_STRING_DATE",
+    "userId": "USER_ID_FROM_CONFIG",
+    "commandName": "invoking_command_or_tool_name",
+    "modelUsed": "ai_model_id",
+    "providerName": "ai_provider_name",
+    "inputTokens": NUMBER,
+    "outputTokens": NUMBER,
+    "totalTokens": NUMBER,
+    "totalCost": NUMBER, // e.g., 0.012414
+    "currency": "USD" // e.g., "USD"
+  }
+  ```
+
+## Integration Pattern by Layer
+
+The key principle is that each layer receives telemetry data from the layer below it (if applicable) and passes it to the layer above it, or handles it for display in the case of the CLI.
+
+### 1. Core Logic Functions (e.g., in `scripts/modules/task-manager/`)
+
+Functions in this layer that invoke AI services are responsible for handling the `telemetryData` they receive from [`ai-services-unified.js`](mdc:scripts/modules/ai-services-unified.js).
+
+- **Actions**:
+    1.  Call the appropriate AI service function (e.g., `generateObjectService`).
+        -   Pass `commandName` (e.g., `add-task`, `expand-task`) and `outputType` (e.g., `cli` or `mcp`) in the `params` object to the AI service. The `outputType` can be derived from context (e.g., presence of `mcpLog`).
+    2.  The AI service returns an object, e.g., `aiServiceResponse = { mainResult: {/*AI output*/}, telemetryData: {/*telemetry data*/} }`.
+    3.  Extract `aiServiceResponse.mainResult` for the core processing.
+    4.  **Must return an object that includes `aiServiceResponse.telemetryData`**.
+        Example: `return { operationSpecificData: /*...*/, telemetryData: aiServiceResponse.telemetryData };`
+
+- **CLI Output Handling (If Applicable)**:
+    -   If the core function also handles CLI output (e.g., it has an `outputFormat` parameter that can be `'text'` or `'cli'`):
+        1.  Check if `outputFormat === 'text'` (or `'cli'`).
+        2.  If so, and if `aiServiceResponse.telemetryData` is available, call `displayAiUsageSummary(aiServiceResponse.telemetryData, 'cli')` from [`scripts/modules/ui.js`](mdc:scripts/modules/ui.js).
+        - This ensures telemetry is displayed directly to CLI users after the main command output.
+
+- **Example Snippet (Core Logic in `scripts/modules/task-manager/someAiAction.js`)**:
+  ```javascript
+  import { generateObjectService } from '../ai-services-unified.js';
+  import { displayAiUsageSummary } from '../ui.js';
+
+  async function performAiRelatedAction(params, context, outputFormat = 'text') {
+    const { commandNameFromContext, /* other context vars */ } = context;
+    let aiServiceResponse = null;
+
+    try {
+      aiServiceResponse = await generateObjectService({
+        // ... other parameters for AI service ...
+        commandName: commandNameFromContext || 'default-action-name',
+        outputType: context.mcpLog ? 'mcp' : 'cli' // Derive outputType
+      });
+
+      const usefulAiOutput = aiServiceResponse.mainResult.object;
+      // ... do work with usefulAiOutput ...
+
+      if (outputFormat === 'text' && aiServiceResponse.telemetryData) {
+        displayAiUsageSummary(aiServiceResponse.telemetryData, 'cli');
+      }
+
+      return {
+        actionData: /* results of processing */,
+        telemetryData: aiServiceResponse.telemetryData
+      };
+    } catch (error) {
+      // ... handle error ...
+      throw error;
+    }
+  }
+  ```
+
+### 2. Direct Function Wrappers (in `mcp-server/src/core/direct-functions/`)
+
+These functions adapt core logic for the MCP server, ensuring structured responses.
+
+- **Actions**:
+    1.  Call the corresponding core logic function.
+        -   Pass necessary context (e.g., `session`, `mcpLog`, `projectRoot`).
+        -   Provide the `commandName` (typically derived from the MCP tool name) and `outputType: 'mcp'` in the context object passed to the core function.
+        -   If the core function supports an `outputFormat` parameter, pass `'json'` to suppress CLI-specific UI.
+    2.  The core logic function returns an object (e.g., `coreResult = { actionData: ..., telemetryData: ... }`).
+    3.  Include `coreResult.telemetryData` as a field within the `data` object of the successful response returned by the direct function.
+
+- **Example Snippet (Direct Function `someAiActionDirect.js`)**:
+  ```javascript
+  import { performAiRelatedAction } from '../../../../scripts/modules/task-manager/someAiAction.js'; // Core function
+  import { createLogWrapper } from '../../tools/utils.js'; // MCP Log wrapper
+
+  export async function someAiActionDirect(args, log, context = {}) {
+    const { session } = context;
+    // ... prepare arguments for core function from args, including args.projectRoot ...
+
+    try {
+      const coreResult = await performAiRelatedAction(
+        { /* parameters for core function */ },
+        { // Context for core function
+          session,
+          mcpLog: createLogWrapper(log),
+          projectRoot: args.projectRoot,
+          commandNameFromContext: 'mcp_tool_some_ai_action', // Example command name
+          outputType: 'mcp'
+        },
+        'json' // Request 'json' output format from core function
+      );
+
+      return {
+        success: true,
+        data: {
+          operationSpecificData: coreResult.actionData,
+          telemetryData: coreResult.telemetryData // Pass telemetry through
+        }
+      };
+    } catch (error) {
+      // ... error handling, return { success: false, error: ... } ...
+    }
+  }
+  ```
+
+### 3. MCP Tools (in `mcp-server/src/tools/`)
+
+These are the exposed endpoints for MCP clients.
+
+- **Actions**:
+    1.  Call the corresponding direct function wrapper.
+    2.  The direct function returns an object structured like `{ success: true, data: { operationSpecificData: ..., telemetryData: ... } }` (or an error object).
+    3.  Pass this entire result object to `handleApiResult(result, log)` from [`mcp-server/src/tools/utils.js`](mdc:mcp-server/src/tools/utils.js).
+    4.  `handleApiResult` ensures that the `data` field from the direct function's response (which correctly includes `telemetryData`) is part of the final MCP response.
+
+- **Example Snippet (MCP Tool `some_ai_action.js`)**:
+  ```javascript
+  import { someAiActionDirect } from '../core/task-master-core.js';
+  import { handleApiResult, withNormalizedProjectRoot } from './utils.js';
+  // ... zod for parameters ...
+
+  export function registerSomeAiActionTool(server) {
+    server.addTool({
+      name: "some_ai_action",
+      // ... description, parameters ...
+      execute: withNormalizedProjectRoot(async (args, { log, session }) => {
+        try {
+          const resultFromDirectFunction = await someAiActionDirect(
+            { /* args including projectRoot */ },
+            log,
+            { session }
+          );
+          return handleApiResult(resultFromDirectFunction, log); // This passes the nested telemetryData through
+        } catch (error) {
+          // ... error handling ...
+        }
+      })
+    });
+  }
+  ```
+
+### 4. CLI Commands (`scripts/modules/commands.js`)
+
+These define the command-line interface.
+
+- **Actions**:
+    1.  Call the appropriate core logic function.
+    2.  Pass `outputFormat: 'text'` (or ensure the core function defaults to text-based output for CLI).
+    3.  The core logic function (as per Section 1) is responsible for calling `displayAiUsageSummary` if telemetry data is available and it's in CLI mode.
+    4.  The command action itself **should not** call `displayAiUsageSummary` if the core logic function already handles this. This avoids duplicate display.
+
+- **Example Snippet (CLI Command in `commands.js`)**:
+  ```javascript
+  // In scripts/modules/commands.js
+  import { performAiRelatedAction } from './task-manager/someAiAction.js'; // Core function
+
+  programInstance
+    .command('some-cli-ai-action')
+    // ... .option() ...
+    .action(async (options) => {
+      try {
+        const projectRoot = findProjectRoot() || '.'; // Example root finding
+        // ... prepare parameters for core function from command options ...
+        await performAiRelatedAction(
+          { /* parameters for core function */ },
+          { // Context for core function
+            projectRoot,
+            commandNameFromContext: 'some-cli-ai-action',
+            outputType: 'cli'
+          },
+          'text' // Explicitly request text output format for CLI
+        );
+        // Core function handles displayAiUsageSummary internally for 'text' outputFormat
+      } catch (error) {
+        // ... error handling ...
+      }
+    });
+  ```
+
+## Summary Flow
+
+The telemetry data flows as follows:
+
+1.  **[`ai-services-unified.js`](mdc:scripts/modules/ai-services-unified.js)**: Generates `telemetryData` and returns `{ mainResult, telemetryData }`.
+2.  **Core Logic Function**:
+    *   Receives `{ mainResult, telemetryData }`.
+    *   Uses `mainResult`.
+    *   If CLI (`outputFormat: 'text'`), calls `displayAiUsageSummary(telemetryData)`.
+    *   Returns `{ operationSpecificData, telemetryData }`.
+3.  **Direct Function Wrapper**:
+    *   Receives `{ operationSpecificData, telemetryData }` from core logic.
+    *   Returns `{ success: true, data: { operationSpecificData, telemetryData } }`.
+4.  **MCP Tool**:
+    *   Receives direct function response.
+    *   `handleApiResult` ensures the final MCP response to the client is `{ success: true, data: { operationSpecificData, telemetryData } }`.
+5.  **CLI Command**:
+    *   Calls core logic with `outputFormat: 'text'`. Display is handled by core logic.
+
+This pattern ensures telemetry is captured and appropriately handled/exposed across all interaction modes.

.cursor/rules/tests.mdc

@@ -5,6 +5,8 @@ globs: "**/*.test.js,tests/**/*"
 
 # Testing Guidelines for Task Master CLI
 
+*Note:* Never use asynchronous operations in tests. Always mock tests properly based on the way the tested functions are defined and used. Do not arbitrarily create tests. Based them on the low-level details and execution of the underlying code being tested. 
+
 ## Test Organization Structure
 
 - **Unit Tests** (See [`architecture.mdc`](mdc:.cursor/rules/architecture.mdc) for module breakdown)
@@ -88,6 +90,122 @@ describe('Feature or Function Name', () => {
 });
 ```
 
+## Commander.js Command Testing Best Practices
+
+When testing CLI commands built with Commander.js, several special considerations must be made to avoid common pitfalls:
+
+- **Direct Action Handler Testing**
+  - ✅ **DO**: Test the command action handlers directly rather than trying to mock the entire Commander.js chain
+  - ✅ **DO**: Create simplified test-specific implementations of command handlers that match the original behavior
+  - ✅ **DO**: Explicitly handle all options, including defaults and shorthand flags (e.g., `-p` for `--prompt`)
+  - ✅ **DO**: Include null/undefined checks in test implementations for parameters that might be optional
+  - ✅ **DO**: Use fixtures from `tests/fixtures/` for consistent sample data across tests
+  
+  ```javascript
+  // ✅ DO: Create a simplified test version of the command handler
+  const testAddTaskAction = async (options) => {
+    options = options || {}; // Ensure options aren't undefined
+    
+    // Validate parameters
+    const isManualCreation = options.title && options.description;
+    const prompt = options.prompt || options.p; // Handle shorthand flags
+    
+    if (!prompt && !isManualCreation) {
+      throw new Error('Expected error message');
+    }
+    
+    // Call the mocked task manager
+    return mockTaskManager.addTask(/* parameters */);
+  };
+  
+  test('should handle required parameters correctly', async () => {
+    // Call the test implementation directly
+    await expect(async () => {
+      await testAddTaskAction({ file: 'tasks.json' });
+    }).rejects.toThrow('Expected error message');
+  });
+  ```
+
+- **Commander Chain Mocking (If Necessary)**
+  - ✅ **DO**: Mock ALL chainable methods (`option`, `argument`, `action`, `on`, etc.)
+  - ✅ **DO**: Return `this` (or the mock object) from all chainable method mocks
+  - ✅ **DO**: Remember to mock not only the initial object but also all objects returned by methods
+  - ✅ **DO**: Implement a mechanism to capture the action handler for direct testing
+  
+  ```javascript
+  // If you must mock the Commander.js chain:
+  const mockCommand = {
+    command: jest.fn().mockReturnThis(),
+    description: jest.fn().mockReturnThis(),
+    option: jest.fn().mockReturnThis(),
+    argument: jest.fn().mockReturnThis(), // Don't forget this one
+    action: jest.fn(fn => { 
+      actionHandler = fn; // Capture the handler for testing
+      return mockCommand; 
+    }),
+    on: jest.fn().mockReturnThis() // Don't forget this one
+  };
+  ```
+
+- **Parameter Handling**
+  - ✅ **DO**: Check for both main flag and shorthand flags (e.g., `prompt` and `p`)
+  - ✅ **DO**: Handle parameters like Commander would (comma-separated lists, etc.)
+  - ✅ **DO**: Set proper default values as defined in the command
+  - ✅ **DO**: Validate that required parameters are actually required in tests
+  
+  ```javascript
+  // Parse dependencies like Commander would
+  const dependencies = options.dependencies 
+    ? options.dependencies.split(',').map(id => id.trim())
+    : [];
+  ```
+
+- **Environment and Session Handling**
+  - ✅ **DO**: Properly mock session objects when required by functions
+  - ✅ **DO**: Reset environment variables between tests if modified
+  - ✅ **DO**: Use a consistent pattern for environment-dependent tests
+  
+  ```javascript
+  // Session parameter mock pattern
+  const sessionMock = { session: process.env };
+  
+  // In test:
+  expect(mockAddTask).toHaveBeenCalledWith(
+    expect.any(String),
+    'Test prompt',
+    [],
+    'medium',
+    sessionMock,
+    false,
+    null,
+    null
+  );
+  ```
+
+- **Common Pitfalls to Avoid**
+  - ❌ **DON'T**: Try to use the real action implementation without proper mocking
+  - ❌ **DON'T**: Mock Commander partially - either mock it completely or test the action directly
+  - ❌ **DON'T**: Forget to handle optional parameters that may be undefined
+  - ❌ **DON'T**: Neglect to test shorthand flag functionality (e.g., `-p`, `-r`)
+  - ❌ **DON'T**: Create circular dependencies in your test mocks
+  - ❌ **DON'T**: Access variables before initialization in your test implementations
+  - ❌ **DON'T**: Include actual command execution in unit tests
+  - ❌ **DON'T**: Overwrite the same file path in multiple tests
+  
+  ```javascript
+  // ❌ DON'T: Create circular references in mocks
+  const badMock = {
+    method: jest.fn().mockImplementation(() => badMock.method())
+  };
+  
+  // ❌ DON'T: Access uninitialized variables
+  const badImplementation = () => {
+    const result = uninitialized;
+    let uninitialized = 'value';
+    return result;
+  };
+  ```
+
 ## Jest Module Mocking Best Practices
 
 - **Mock Hoisting Behavior**
@@ -165,107 +283,97 @@ When testing ES modules (`"type": "module"` in package.json), traditional mockin
   - Imported functions may not use your mocked dependencies even with proper jest.mock() setup
   - ES module exports are read-only properties (cannot be reassigned during tests)
 
-- **Mocking Entire Modules**
-  ```javascript
-  // Mock the entire module with custom implementation
-  jest.mock('../../scripts/modules/task-manager.js', () => {
-    // Get original implementation for functions you want to preserve
-    const originalModule = jest.requireActual('../../scripts/modules/task-manager.js');
+- **Mocking Modules Statically Imported**
+  - For modules imported with standard `import` statements at the top level:
+    - Use `jest.mock('path/to/module', factory)` **before** any imports.
+    - Jest hoists these mocks.
+    - Ensure the factory function returns the mocked structure correctly.
 
-    // Return mix of original and mocked functionality
-    return {
-      ...originalModule,
-      generateTaskFiles: jest.fn() // Replace specific functions
-    };
+- **Mocking Dependencies for Dynamically Imported Modules**
+  - **Problem**: Standard `jest.mock()` often fails for dependencies of modules loaded later using dynamic `import('path/to/module')`. The mocks aren't applied correctly when the dynamic import resolves.
+  - **Solution**: Use `jest.unstable_mockModule(modulePath, factory)` **before** the dynamic `import()` call.
+  ```javascript
+  // 1. Define mock function instances
+  const mockExistsSync = jest.fn();
+  const mockReadFileSync = jest.fn();
+  // ... other mocks
+
+  // 2. Mock the dependency module *before* the dynamic import
+  jest.unstable_mockModule('fs', () => ({
+    __esModule: true, // Important for ES module mocks
+    // Mock named exports
+    existsSync: mockExistsSync,
+    readFileSync: mockReadFileSync,
+    // Mock default export if necessary
+    // default: { ... }
+  }));
+
+  // 3. Dynamically import the module under test (e.g., in beforeAll or test case)
+  let moduleUnderTest;
+  beforeAll(async () => {
+    // Ensure mocks are reset if needed before import
+    mockExistsSync.mockReset();
+    mockReadFileSync.mockReset();
+    // ... reset other mocks ...
+
+    // Import *after* unstable_mockModule is called
+    moduleUnderTest = await import('../../scripts/modules/module-using-fs.js');
   });
 
-  // Import after mocks
-  import * as taskManager from '../../scripts/modules/task-manager.js';
+  // 4. Now tests can use moduleUnderTest, and its 'fs' calls will hit the mocks
+  test('should use mocked fs.readFileSync', () => {
+    mockReadFileSync.mockReturnValue('mock data');
+    moduleUnderTest.readFileAndProcess();
+    expect(mockReadFileSync).toHaveBeenCalled();
+    // ... other assertions
+  });
+  ```
+  - ✅ **DO**: Call `jest.unstable_mockModule()` before `await import()`.
+  - ✅ **DO**: Include `__esModule: true` in the mock factory for ES modules.
+  - ✅ **DO**: Mock named and default exports as needed within the factory.
+  - ✅ **DO**: Reset mock functions (`mockFn.mockReset()`) before the dynamic import if they might have been called previously.
 
-  // Now you can use the mock directly
-  const { generateTaskFiles } = taskManager;
+- **Mocking Entire Modules (Static Import)**
+  ```javascript
+  // Mock the entire module with custom implementation for static imports
+  // ... (existing example remains valid) ...
   ```
 
 - **Direct Implementation Testing**
   - Instead of calling the actual function which may have module-scope reference issues:
   ```javascript
-  test('should perform expected actions', () => {
-    // Setup mocks for this specific test
-    mockReadJSON.mockImplementationOnce(() => sampleData);
-    
-    // Manually simulate the function's behavior
-    const data = mockReadJSON('path/file.json');
-    mockValidateAndFixDependencies(data, 'path/file.json');
-    
-    // Skip calling the actual function and verify mocks directly
-    expect(mockReadJSON).toHaveBeenCalledWith('path/file.json');
-    expect(mockValidateAndFixDependencies).toHaveBeenCalledWith(data, 'path/file.json');
-  });
+  // ... (existing example remains valid) ...
   ```
 
 - **Avoiding Module Property Assignment**
   ```javascript
-  // ❌ DON'T: This causes "Cannot assign to read only property" errors
-  const utils = await import('../../scripts/modules/utils.js');
-  utils.readJSON = mockReadJSON; // Error: read-only property
-  
-  // ✅ DO: Use the module factory pattern in jest.mock()
-  jest.mock('../../scripts/modules/utils.js', () => ({
-    readJSON: mockReadJSONFunc,
-    writeJSON: mockWriteJSONFunc
-  }));
+  // ... (existing example remains valid) ...
   ```
 
 - **Handling Mock Verification Failures**
   - If verification like `expect(mockFn).toHaveBeenCalled()` fails:
-    1. Check that your mock setup is before imports
-    2. Ensure you're using the right mock instance
-    3. Verify your test invokes behavior that would call the mock
-    4. Use `jest.clearAllMocks()` in beforeEach to reset mock state
-    5. Consider implementing a simpler test that directly verifies mock behavior
-
-- **Full Example Pattern**
+    1.  Check that your mock setup (`jest.mock` or `jest.unstable_mockModule`) is correctly placed **before** imports (static or dynamic).
+    2.  Ensure you're using the right mock instance and it's properly passed to the module.
+    3.  Verify your test invokes behavior that *should* call the mock.
+    4.  Use `jest.clearAllMocks()` or specific `mockFn.mockReset()` in `beforeEach` to prevent state leakage between tests.
+    5.  **Check Console Assertions**: If verifying `console.log`, `console.warn`, or `console.error` calls, ensure your assertion matches the *actual* arguments passed. If the code logs a single formatted string, assert against that single string (using `expect.stringContaining` or exact match), not multiple `expect.stringContaining` arguments.
         ```javascript
-  // 1. Define mock implementations
-  const mockReadJSON = jest.fn();
-  const mockValidateAndFixDependencies = jest.fn();
-  
-  // 2. Mock modules
-  jest.mock('../../scripts/modules/utils.js', () => ({
-    readJSON: mockReadJSON,
-    // Include other functions as needed
-  }));
-  
-  jest.mock('../../scripts/modules/dependency-manager.js', () => ({
-    validateAndFixDependencies: mockValidateAndFixDependencies
-  }));
-  
-  // 3. Import after mocks
-  import * as taskManager from '../../scripts/modules/task-manager.js';
-  
-  describe('generateTaskFiles function', () => {
-    beforeEach(() => {
-      jest.clearAllMocks();
-    });
-    
-    test('should generate task files', () => {
-      // 4. Setup test-specific mock behavior
-      const sampleData = { tasks: [{ id: 1, title: 'Test' }] };
-      mockReadJSON.mockReturnValueOnce(sampleData);
-      
-      // 5. Create direct implementation test
-      // Instead of calling: taskManager.generateTaskFiles('path', 'dir')
-      
-      // Simulate reading data
-      const data = mockReadJSON('path');
-      expect(mockReadJSON).toHaveBeenCalledWith('path');
-      
-      // Simulate other operations the function would perform
-      mockValidateAndFixDependencies(data, 'path');
-      expect(mockValidateAndFixDependencies).toHaveBeenCalledWith(data, 'path');
-    });
-  });
+        // Example: Code logs console.error(`Error: ${message}. Details: ${details}`)
+        // ❌ DON'T: Assert multiple arguments if only one is logged
+        // expect(console.error).toHaveBeenCalledWith(
+        //   expect.stringContaining('Error:'),
+        //   expect.stringContaining('Details:')
+        // );
+        // ✅ DO: Assert the single string argument
+        expect(console.error).toHaveBeenCalledWith(
+           expect.stringContaining('Error: Specific message. Details: More details')
+        );
+        // or for exact match:
+        expect(console.error).toHaveBeenCalledWith(
+           'Error: Specific message. Details: More details'
+        );
         ```
+    6.  Consider implementing a simpler test that *only* verifies the mock behavior in isolation.
 
 ## Mocking Guidelines
 
@@ -552,6 +660,102 @@ npm test -- -t "pattern to match"
   });
   ```
 
+## Testing AI Service Integrations
+
+- **DO NOT import real AI service clients**
+  - ❌ DON'T: Import actual AI clients from their libraries
+  - ✅ DO: Create fully mocked versions that return predictable responses
+
+  ```javascript
+  // ❌ DON'T: Import and instantiate real AI clients
+  import { Anthropic } from '@anthropic-ai/sdk';
+  const anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });
+
+  // ✅ DO: Mock the entire module with controlled behavior
+  jest.mock('@anthropic-ai/sdk', () => ({
+    Anthropic: jest.fn().mockImplementation(() => ({
+      messages: {
+        create: jest.fn().mockResolvedValue({
+          content: [{ type: 'text', text: 'Mocked AI response' }]
+        })
+      }
+    }))
+  }));
+  ```
+
+- **DO NOT rely on environment variables for API keys**
+  - ❌ DON'T: Assume environment variables are set in tests
+  - ✅ DO: Set mock environment variables in test setup
+
+  ```javascript
+  // In tests/setup.js or at the top of test file
+  process.env.ANTHROPIC_API_KEY = 'test-mock-api-key-for-tests';
+  process.env.PERPLEXITY_API_KEY = 'test-mock-perplexity-key-for-tests';
+  ```
+
+- **DO NOT use real AI client initialization logic**
+  - ❌ DON'T: Use code that attempts to initialize or validate real AI clients
+  - ✅ DO: Create test-specific paths that bypass client initialization
+
+  ```javascript
+  // ❌ DON'T: Test functions that require valid AI client initialization
+  // This will fail without proper API keys or network access
+  test('should use AI client', async () => {
+    const result = await functionThatInitializesAIClient();
+    expect(result).toBeDefined();
+  });
+
+  // ✅ DO: Test with bypassed initialization or manual task paths
+  test('should handle manual task creation without AI', () => {
+    // Using a path that doesn't require AI client initialization
+    const result = addTaskDirect({ 
+      title: 'Manual Task', 
+      description: 'Test Description'
+    }, mockLogger);
+    
+    expect(result.success).toBe(true);
+  });
+  ```
+
+## Testing Asynchronous Code
+
+- **DO NOT rely on asynchronous operations in tests**
+  - ❌ DON'T: Use real async/await or Promise resolution in tests
+  - ✅ DO: Make all mocks return synchronous values when possible
+
+  ```javascript
+  // ❌ DON'T: Use real async functions that might fail unpredictably
+  test('should handle async operation', async () => {
+    const result = await realAsyncFunction(); // Can time out or fail for external reasons
+    expect(result).toBe(expectedValue);
+  });
+
+  // ✅ DO: Make async operations synchronous in tests
+  test('should handle operation', () => {
+    mockAsyncFunction.mockReturnValue({ success: true, data: 'test' });
+    const result = functionUnderTest();
+    expect(result).toEqual({ success: true, data: 'test' });
+  });
+  ```
+
+- **DO NOT test exact error messages**
+  - ❌ DON'T: Assert on exact error message text that might change
+  - ✅ DO: Test for error presence and general properties
+
+  ```javascript
+  // ❌ DON'T: Test for exact error message text
+  expect(result.error).toBe('Could not connect to API: Network error');
+
+  // ✅ DO: Test for general error properties or message patterns
+  expect(result.success).toBe(false);
+  expect(result.error).toContain('Could not connect');
+  // Or even better:
+  expect(result).toMatchObject({ 
+    success: false,
+    error: expect.stringContaining('connect')
+  });
+  ```
+
 ## Reliable Testing Techniques
 
 - **Create Simplified Test Functions**
@@ -564,99 +768,125 @@ npm test -- -t "pattern to match"
   const setTaskStatus = async (taskId, newStatus) => {
     const tasksPath = 'tasks/tasks.json';
     const data = await readJSON(tasksPath);
-    // Update task status logic
+    // [implementation]
     await writeJSON(tasksPath, data);
-    return data;
+    return { success: true };
   };
   
-  // Test-friendly simplified function (easy to test)
-  const testSetTaskStatus = (tasksData, taskIdInput, newStatus) => {
-    // Same core logic without file operations
-    // Update task status logic on provided tasksData object
-    return tasksData; // Return updated data for assertions
+  // Test-friendly version (easier to test)
+  const updateTaskStatus = (tasks, taskId, newStatus) => {
+    // Pure logic without side effects
+    const updatedTasks = [...tasks];
+    const taskIndex = findTaskById(updatedTasks, taskId);
+    if (taskIndex === -1) return { success: false, error: 'Task not found' };
+    updatedTasks[taskIndex].status = newStatus;
+    return { success: true, tasks: updatedTasks };
   };
   ```
 
-- **Avoid Real File System Operations**
-  - Never write to real files during tests
-  - Create test-specific versions of file operation functions
-  - Mock all file system operations including read, write, exists, etc.
-  - Verify function behavior using the in-memory data structures
-  
-  ```javascript
-  // Mock file operations
-  const mockReadJSON = jest.fn();
-  const mockWriteJSON = jest.fn();
-  
-  jest.mock('../../scripts/modules/utils.js', () => ({
-    readJSON: mockReadJSON,
-    writeJSON: mockWriteJSON,
-  }));
-  
-  test('should update task status correctly', () => {
-    // Setup mock data
-    const testData = JSON.parse(JSON.stringify(sampleTasks));
-    mockReadJSON.mockReturnValue(testData);
-    
-    // Call the function that would normally modify files
-    const result = testSetTaskStatus(testData, '1', 'done');
-    
-    // Assert on the in-memory data structure
-    expect(result.tasks[0].status).toBe('done');
-  });
-  ```
-
-- **Data Isolation Between Tests**
-  - Always create fresh copies of test data for each test
-  - Use `JSON.parse(JSON.stringify(original))` for deep cloning
-  - Reset all mocks before each test with `jest.clearAllMocks()`
-  - Avoid state that persists between tests
-  
-  ```javascript
-  beforeEach(() => {
-    jest.clearAllMocks();
-    // Deep clone the test data
-    testTasksData = JSON.parse(JSON.stringify(sampleTasks));
-  });
-  ```
-
-- **Test All Path Variations**
-  - Regular tasks and subtasks
-  - Single items and multiple items
-  - Success paths and error paths
-  - Edge cases (empty data, invalid inputs, etc.)
-  
-  ```javascript
-  // Multiple test cases covering different scenarios
-  test('should update regular task status', () => {
-    /* test implementation */
-  });
-  
-  test('should update subtask status', () => {
-    /* test implementation */
-  });
-  
-  test('should update multiple tasks when given comma-separated IDs', () => {
-    /* test implementation */
-  });
-  
-  test('should throw error for non-existent task ID', () => {
-    /* test implementation */
-  });
-  ```
-
-- **Stabilize Tests With Predictable Input/Output**
-  - Use consistent, predictable test fixtures
-  - Avoid random values or time-dependent data
-  - Make tests deterministic for reliable CI/CD
-  - Control all variables that might affect test outcomes
-  
-  ```javascript
-  // Use a specific known date instead of current date
-  const fixedDate = new Date('2023-01-01T12:00:00Z');
-  jest.spyOn(global, 'Date').mockImplementation(() => fixedDate);
-  ```
-
 See [tests/README.md](mdc:tests/README.md) for more details on the testing approach.
 
 Refer to [jest.config.js](mdc:jest.config.js) for Jest configuration options.
+
+## Variable Hoisting and Module Initialization Issues
+
+When testing ES modules or working with complex module imports, you may encounter variable hoisting and initialization issues. These can be particularly tricky to debug and often appear as "Cannot access 'X' before initialization" errors.
+
+- **Understanding Module Initialization Order**
+  - ✅ **DO**: Declare and initialize global variables at the top of modules
+  - ✅ **DO**: Use proper function declarations to avoid hoisting issues
+  - ✅ **DO**: Initialize variables before they are referenced, especially in imported modules
+  - ✅ **DO**: Be aware that imports are hoisted to the top of the file
+  
+  ```javascript
+  // ✅ DO: Define global state variables at the top of the module
+  let silentMode = false; // Declare and initialize first
+  
+  const CONFIG = { /* configuration */ };
+  
+  function isSilentMode() {
+    return silentMode; // Reference variable after it's initialized
+  }
+  
+  function log(level, message) {
+    if (isSilentMode()) return; // Use the function instead of accessing variable directly
+    // ...
+  }
+  ```
+
+- **Testing Modules with Initialization-Dependent Functions**
+  - ✅ **DO**: Create test-specific implementations that initialize all variables correctly
+  - ✅ **DO**: Use factory functions in mocks to ensure proper initialization order
+  - ✅ **DO**: Be careful with how you mock or stub functions that depend on module state
+  
+  ```javascript
+  // ✅ DO: Test-specific implementation that avoids initialization issues
+  const testLog = (level, ...args) => {
+    // Local implementation with proper initialization
+    const isSilent = false; // Explicit initialization
+    if (isSilent) return;
+    // Test implementation...
+  };
+  ```
+
+- **Common Hoisting-Related Errors to Avoid**
+  - ❌ **DON'T**: Reference variables before their declaration in module scope
+  - ❌ **DON'T**: Create circular dependencies between modules
+  - ❌ **DON'T**: Rely on variable initialization order across module boundaries
+  - ❌ **DON'T**: Define functions that use hoisted variables before they're initialized
+  
+  ```javascript
+  // ❌ DON'T: Create reference-before-initialization patterns
+  function badFunction() {
+    if (silentMode) { /* ... */ } // ReferenceError if silentMode is declared later
+  }
+  
+  let silentMode = false;
+  
+  // ❌ DON'T: Create cross-module references that depend on initialization order
+  // module-a.js
+  import { getSetting } from './module-b.js';
+  export const config = { value: getSetting() };
+  
+  // module-b.js
+  import { config } from './module-a.js';
+  export function getSetting() {
+    return config.value; // Circular dependency causing initialization issues
+  }
+  ```
+
+- **Dynamic Imports as a Solution**
+  - ✅ **DO**: Use dynamic imports (`import()`) to avoid initialization order issues
+  - ✅ **DO**: Structure modules to avoid circular dependencies that cause initialization issues
+  - ✅ **DO**: Consider factory functions for modules with complex state
+  
+  ```javascript
+  // ✅ DO: Use dynamic imports to avoid initialization issues
+  async function getTaskManager() {
+    return import('./task-manager.js');
+  }
+  
+  async function someFunction() {
+    const taskManager = await getTaskManager();
+    return taskManager.someMethod();
+  }
+  ```
+
+- **Testing Approach for Modules with Initialization Issues**
+  - ✅ **DO**: Create self-contained test implementations rather than using real implementations
+  - ✅ **DO**: Mock dependencies at module boundaries instead of trying to mock deep dependencies
+  - ✅ **DO**: Isolate module-specific state in tests
+  
+  ```javascript
+  // ✅ DO: Create isolated test implementation instead of reusing module code
+  test('should log messages when not in silent mode', () => {
+    // Local test implementation instead of importing from module
+    const testLog = (level, message) => {
+      if (false) return; // Always non-silent for this test
+      mockConsole(level, message);
+    };
+    
+    testLog('info', 'test message');
+    expect(mockConsole).toHaveBeenCalledWith('info', 'test message');
+  });
+  ``` 

.cursor/rules/utilities.mdc

@@ -3,7 +3,6 @@ description: Guidelines for implementing utility functions
 globs: scripts/modules/utils.js, mcp-server/src/**/*
 alwaysApply: false
 ---
-
 # Utility Function Guidelines
 
 ## General Principles
@@ -79,28 +78,30 @@ alwaysApply: false
   }
   ```
 
-## Configuration Management (in `scripts/modules/utils.js`)
+## Configuration Management (via `config-manager.js`)
 
-- **Environment Variables**:
-  - ✅ DO: Provide default values for all configuration
-  - ✅ DO: Use environment variables for customization
-  - ✅ DO: Document available configuration options
-  - ❌ DON'T: Hardcode values that should be configurable
+Taskmaster configuration (excluding API keys) is primarily managed through the `.taskmasterconfig` file located in the project root and accessed via getters in [`scripts/modules/config-manager.js`](mdc:scripts/modules/config-manager.js).
 
-  ```javascript
-  // ✅ DO: Set up configuration with defaults and environment overrides
-  const CONFIG = {
-    model: process.env.MODEL || 'claude-3-opus-20240229', // Updated default model
-    maxTokens: parseInt(process.env.MAX_TOKENS || '4000'),
-    temperature: parseFloat(process.env.TEMPERATURE || '0.7'),
-    debug: process.env.DEBUG === "true",
-    logLevel: process.env.LOG_LEVEL || "info",
-    defaultSubtasks: parseInt(process.env.DEFAULT_SUBTASKS || "3"),
-    defaultPriority: process.env.DEFAULT_PRIORITY || "medium",
-    projectName: process.env.PROJECT_NAME || "Task Master Project", // Generic project name
-    projectVersion: "1.5.0" // Version should be updated via release process
-  };
-  ```
+- **`.taskmasterconfig` File**:
+  - ✅ DO: Use this JSON file to store settings like AI model selections (main, research, fallback), parameters (temperature, maxTokens), logging level, default priority/subtasks, etc.
+  - ✅ DO: Manage this file using the `task-master models --setup` CLI command or the `models` MCP tool.
+  - ✅ DO: Rely on [`config-manager.js`](mdc:scripts/modules/config-manager.js) to load this file (using the correct project root passed from MCP or found via CLI utils), merge with defaults, and provide validated settings.
+  - ❌ DON'T: Store API keys in this file.
+  - ❌ DON'T: Manually edit this file unless necessary.
+
+- **Configuration Getters (`config-manager.js`)**:
+  - ✅ DO: Import and use specific getters from `config-manager.js` (e.g., `getMainProvider()`, `getLogLevel()`, `getMainMaxTokens()`) to access configuration values *needed for application logic* (like `getDefaultSubtasks`).
+  - ✅ DO: Pass the `explicitRoot` parameter to getters if calling from MCP direct functions to ensure the correct project's config is loaded.
+  - ❌ DON'T: Call AI-specific getters (like `getMainModelId`, `getMainMaxTokens`) from core logic functions (`scripts/modules/task-manager/*`). Instead, pass the `role` to the unified AI service.
+  - ❌ DON'T: Access configuration values directly from environment variables (except API keys).
+
+- **API Key Handling (`utils.js` & `ai-services-unified.js`)**:
+  - ✅ DO: Store API keys **only** in `.env` (for CLI, loaded by `dotenv` in `scripts/dev.js`) or `.cursor/mcp.json` (for MCP, accessed via `session.env`).
+  - ✅ DO: Use `isApiKeySet(providerName, session)` from `config-manager.js` to check if a provider's key is available *before* potentially attempting an AI call if needed, but note the unified service performs its own internal check.
+  - ✅ DO: Understand that the unified service layer (`ai-services-unified.js`) internally resolves API keys using `resolveEnvVariable(key, session)` from `utils.js`.
+
+- **Error Handling**:
+  - ✅ DO: Handle potential `ConfigurationError` if the `.taskmasterconfig` file is missing or invalid when accessed via `getConfig` (e.g., in `commands.js` or direct functions).
 
 ## Logging Utilities (in `scripts/modules/utils.js`)
 
@@ -427,36 +428,69 @@ alwaysApply: false
 
 ## MCP Server Tool Utilities (`mcp-server/src/tools/utils.js`)
 
-- **Purpose**: These utilities specifically support the MCP server tools ([`mcp-server/src/tools/*.js`](mdc:mcp-server/src/tools/*.js)), handling MCP communication patterns, response formatting, caching integration, and the CLI fallback mechanism.
-- **Refer to [`mcp.mdc`](mdc:.cursor/rules/mcp.mdc)** for detailed usage patterns within the MCP tool `execute` methods and direct function wrappers.
+These utilities specifically support the implementation and execution of MCP tools.
 
-- **`getProjectRootFromSession(session, log)`**: 
-    - ✅ **DO**: Call this utility **within the MCP tool's `execute` method** to extract the project root path from the `session` object.
-    - Decodes the `file://` URI and handles potential errors.
-    - Returns the project path string or `null`.
-    - The returned path should then be passed in the `args` object when calling the corresponding `*Direct` function (e.g., `yourDirectFunction({ ...args, projectRoot: rootFolder }, log)`).
+- **`normalizeProjectRoot(rawPath, log)`**:
+    - **Purpose**: Takes a raw project root path (potentially URI encoded, with `file://` prefix, Windows slashes) and returns a normalized, absolute path suitable for the server's OS.
+    - **Logic**: Decodes URI, strips `file://`, handles Windows drive prefix (`/C:/`), replaces `\` with `/`, uses `path.resolve()`.
+    - **Usage**: Used internally by `withNormalizedProjectRoot` HOF.
+
+- **`getRawProjectRootFromSession(session, log)`**:
+    - **Purpose**: Extracts the *raw* project root URI string from the session object (`session.roots[0].uri` or `session.roots.roots[0].uri`) without performing normalization.
+    - **Usage**: Used internally by `withNormalizedProjectRoot` HOF as a fallback if `args.projectRoot` isn't provided.
+
+- **`withNormalizedProjectRoot(executeFn)`**:
+    - **Purpose**: A Higher-Order Function (HOF) designed to wrap a tool's `execute` method.
+    - **Logic**: 
+        1. Determines the raw project root (from `args.projectRoot` or `getRawProjectRootFromSession`).
+        2. Normalizes the raw path using `normalizeProjectRoot`.
+        3. Injects the normalized, absolute path back into the `args` object as `args.projectRoot`.
+        4. Calls the original `executeFn` with the updated `args`.
+    - **Usage**: Should wrap the `execute` function of *every* MCP tool that needs a reliable, normalized project root path.
+    - **Example**:
+      ```javascript
+      // In mcp-server/src/tools/your-tool.js
+      import { withNormalizedProjectRoot } from './utils.js';
+      
+      export function registerYourTool(server) {
+          server.addTool({
+              // ... name, description, parameters ...
+              execute: withNormalizedProjectRoot(async (args, context) => {
+                  // args.projectRoot is now normalized here
+                  const { projectRoot /*, other args */ } = args;
+                  // ... rest of tool logic using normalized projectRoot ...
+              })
+          });
+      }
+      ```
 
 - **`handleApiResult(result, log, errorPrefix, processFunction)`**:
-    - ✅ **DO**: Call this from the MCP tool's `execute` method after receiving the result from the `*Direct` function wrapper.
-    - Takes the standard `{ success, data/error, fromCache }` object.
-    - Formats the standard MCP success or error response, including the `fromCache` flag.
-    - Uses `processMCPResponseData` by default to filter response data.
-
-- **`executeTaskMasterCommand(command, log, args, projectRootRaw)`**:
-    - Executes a Task Master CLI command as a child process.
-    - Handles fallback between global `task-master` and local `node scripts/dev.js`.
-    - ❌ **DON'T**: Use this as the primary method for MCP tools. Prefer direct function calls via `*Direct` wrappers.
-
-- **`processMCPResponseData(taskOrData, fieldsToRemove)`**:
-    - Filters task data (e.g., removing `details`, `testStrategy`) before sending to the MCP client. Called by `handleApiResult`.
+    - **Purpose**: Standardizes the formatting of responses returned by direct functions (`{ success, data/error, fromCache }`) into the MCP response format.
+    - **Usage**: Call this at the end of the tool's `execute` method, passing the result from the direct function call.
 
 - **`createContentResponse(content)` / `createErrorResponse(errorMessage)`**:
-    - Formatters for standard MCP success/error responses.
+    - **Purpose**: Helper functions to create the basic MCP response structure for success or error messages.
+    - **Usage**: Used internally by `handleApiResult` and potentially directly for simple responses.
+
+- **`createLogWrapper(log)`**:
+    - **Purpose**: Creates a logger object wrapper with standard methods (`info`, `warn`, `error`, `debug`, `success`) mapping to the passed MCP `log` object's methods. Ensures compatibility when passing loggers to core functions.
+    - **Usage**: Used within direct functions before passing the `log` object down to core logic that expects the standard method names.
 
 - **`getCachedOrExecute({ cacheKey, actionFn, log })`**:
-    - ✅ **DO**: Use this utility *inside direct function wrappers* to implement caching.
-    - Checks cache, executes `actionFn` on miss, stores result.
-    - Returns standard `{ success, data/error, fromCache: boolean }`.
+    - **Purpose**: Utility for implementing caching within direct functions. Checks cache for `cacheKey`; if miss, executes `actionFn`, caches successful result, and returns.
+    - **Usage**: Wrap the core logic execution within a direct function call.
+
+- **`processMCPResponseData(taskOrData, fieldsToRemove)`**:
+    - **Purpose**: Utility to filter potentially sensitive or large fields (like `details`, `testStrategy`) from task objects before sending the response back via MCP.
+    - **Usage**: Passed as the default `processFunction` to `handleApiResult`.
+
+- **`getProjectRootFromSession(session, log)`**:
+    - **Purpose**: Legacy function to extract *and normalize* the project root from the session. Replaced by the HOF pattern but potentially still used.
+    - **Recommendation**: Prefer using the `withNormalizedProjectRoot` HOF in tools instead of calling this directly.
+
+- **`executeTaskMasterCommand(...)`**: 
+    - **Purpose**: Executes `task-master` CLI command as a fallback. 
+    - **Recommendation**: Deprecated for most uses; prefer direct function calls.
 
 ## Export Organization
 

.env.example

@@ -1,20 +1,9 @@
-# API Keys (Required)
-ANTHROPIC_API_KEY=your_anthropic_api_key_here       # Format: sk-ant-api03-...
-PERPLEXITY_API_KEY=your_perplexity_api_key_here     # Format: pplx-...
-
-# Model Configuration
-MODEL=claude-3-7-sonnet-20250219                    # Recommended models: claude-3-7-sonnet-20250219, claude-3-opus-20240229
-PERPLEXITY_MODEL=sonar-pro                          # Perplexity model for research-backed subtasks
-MAX_TOKENS=128000                                   # Maximum tokens for model responses
-TEMPERATURE=0.2                                     # Temperature for model responses (0.0-1.0)
-
-# Logging Configuration
-DEBUG=false                                         # Enable debug logging (true/false)
-LOG_LEVEL=info                                      # Log level (debug, info, warn, error)
-
-# Task Generation Settings
-DEFAULT_SUBTASKS=5                                  # Default number of subtasks when expanding
-DEFAULT_PRIORITY=medium                             # Default priority for generated tasks (high, medium, low)
-
-# Project Metadata (Optional)
-    PROJECT_NAME=Your Project Name                  # Override default project name in tasks.json
+# API Keys (Required for using in any role i.e. main/research/fallback -- see `task-master models`)
+ANTHROPIC_API_KEY=YOUR_ANTHROPIC_KEY_HERE
+PERPLEXITY_API_KEY=YOUR_PERPLEXITY_KEY_HERE
+OPENAI_API_KEY=YOUR_OPENAI_KEY_HERE
+GOOGLE_API_KEY=YOUR_GOOGLE_KEY_HERE
+MISTRAL_API_KEY=YOUR_MISTRAL_KEY_HERE
+OPENROUTER_API_KEY=YOUR_OPENROUTER_KEY_HERE
+XAI_API_KEY=YOUR_XAI_KEY_HERE
+AZURE_OPENAI_API_KEY=YOUR_AZURE_KEY_HERE

.github/ISSUE_TEMPLATE/bug_report.md

@@ -0,0 +1,39 @@
+---
+name: Bug report
+about: Create a report to help us improve
+title: 'bug: '
+labels: bug
+assignees: ''
+---
+
+### Description
+
+Detailed description of the problem, including steps to reproduce the issue.
+
+### Steps to Reproduce
+
+1. Step-by-step instructions to reproduce the issue
+2. Include command examples or UI interactions
+
+### Expected Behavior
+
+Describe clearly what the expected outcome or behavior should be.
+
+### Actual Behavior
+
+Describe clearly what the actual outcome or behavior is.
+
+### Screenshots or Logs
+
+Provide screenshots, logs, or error messages if applicable.
+
+### Environment
+
+- Task Master version:
+- Node.js version:
+- Operating system:
+- IDE (if applicable):
+
+### Additional Context
+
+Any additional information or context that might help diagnose the issue.

.github/ISSUE_TEMPLATE/enhancements---feature-requests.md

@@ -0,0 +1,51 @@
+---
+name: Enhancements & feature requests
+about: Suggest an idea for this project
+title: 'feat: '
+labels: enhancement
+assignees: ''
+---
+
+> "Direct quote or clear summary of user request or need or user story."
+
+### Motivation
+
+Detailed explanation of why this feature is important. Describe the problem it solves or the benefit it provides.
+
+### Proposed Solution
+
+Clearly describe the proposed feature, including:
+
+- High-level overview of the feature
+- Relevant technologies or integrations
+- How it fits into the existing workflow or architecture
+
+### High-Level Workflow
+
+1. Step-by-step description of how the feature will be implemented
+2. Include necessary intermediate milestones
+
+### Key Elements
+
+- Bullet-point list of technical or UX/UI enhancements
+- Mention specific integrations or APIs
+- Highlight changes needed in existing data models or commands
+
+### Example Workflow
+
+Provide a clear, concrete example demonstrating the feature:
+
+```shell
+$ task-master [action]
+→ Expected response/output
+```
+
+### Implementation Considerations
+
+- Dependencies on external components or APIs
+- Backward compatibility requirements
+- Potential performance impacts or resource usage
+
+### Out of Scope (Future Considerations)
+
+Clearly list any features or improvements not included but relevant for future iterations.

.github/ISSUE_TEMPLATE/feedback.md

@@ -0,0 +1,31 @@
+---
+name: Feedback
+about: Give us specific feedback on the product/approach/tech
+title: 'feedback: '
+labels: feedback
+assignees: ''
+---
+
+### Feedback Summary
+
+Provide a clear summary or direct quote from user feedback.
+
+### User Context
+
+Explain the user's context or scenario in which this feedback was provided.
+
+### User Impact
+
+Describe how this feedback affects the user experience or workflow.
+
+### Suggestions
+
+Provide any initial thoughts, potential solutions, or improvements based on the feedback.
+
+### Relevant Screenshots or Examples
+
+Attach screenshots, logs, or examples that illustrate the feedback.
+
+### Additional Notes
+
+Any additional context or related information.

.github/workflows/ci.yml

@@ -14,7 +14,7 @@ permissions:
   contents: read
 
 jobs:
-  build:
+  setup:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
@@ -24,21 +24,55 @@ jobs:
       - uses: actions/setup-node@v4
         with:
           node-version: 20
-          cache: "npm"
+          cache: 'npm'
+
+      - name: Install Dependencies
+        id: install
+        run: npm ci
+        timeout-minutes: 2
 
       - name: Cache node_modules
         uses: actions/cache@v4
         with:
-          path: |
-            node_modules
-            */*/node_modules
-          key: ${{ runner.os }}-node-${{ hashFiles('**/package-lock.json') }}
-          restore-keys: |
-            ${{ runner.os }}-node-
+          path: node_modules
+          key: ${{ runner.os }}-node-modules-${{ hashFiles('**/package-lock.json') }}
 
-      - name: Install Dependencies
-        run: npm ci
-        timeout-minutes: 2
+  format-check:
+    needs: setup
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: actions/setup-node@v4
+        with:
+          node-version: 20
+
+      - name: Restore node_modules
+        uses: actions/cache@v4
+        with:
+          path: node_modules
+          key: ${{ runner.os }}-node-modules-${{ hashFiles('**/package-lock.json') }}
+
+      - name: Format Check
+        run: npm run format-check
+        env:
+          FORCE_COLOR: 1
+
+  test:
+    needs: setup
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: actions/setup-node@v4
+        with:
+          node-version: 20
+
+      - name: Restore node_modules
+        uses: actions/cache@v4
+        with:
+          path: node_modules
+          key: ${{ runner.os }}-node-modules-${{ hashFiles('**/package-lock.json') }}
 
       - name: Run Tests
         run: |
@@ -47,13 +81,13 @@ jobs:
           NODE_ENV: test
           CI: true
           FORCE_COLOR: 1
-        timeout-minutes: 15
+        timeout-minutes: 10
 
       - name: Upload Test Results
         if: always()
         uses: actions/upload-artifact@v4
         with:
-          name: test-results-node
+          name: test-results
           path: |
             test-results
             coverage

.github/workflows/pre-release.yml

@@ -0,0 +1,62 @@
+name: Pre-Release (RC)
+
+on:
+  workflow_dispatch: # Allows manual triggering from GitHub UI/API
+
+concurrency: pre-release-${{ github.ref }}
+
+jobs:
+  rc:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - uses: actions/setup-node@v4
+        with:
+          node-version: 20
+          cache: 'npm'
+
+      - name: Cache node_modules
+        uses: actions/cache@v4
+        with:
+          path: |
+            node_modules
+            */*/node_modules
+          key: ${{ runner.os }}-node-${{ hashFiles('**/package-lock.json') }}
+          restore-keys: |
+            ${{ runner.os }}-node-
+
+      - name: Install dependencies
+        run: npm ci
+        timeout-minutes: 2
+
+      - name: Enter RC mode
+        run: |
+          npx changeset pre exit || true
+          npx changeset pre enter rc
+
+      - name: Version RC packages
+        run: npx changeset version
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          NPM_TOKEN: ${{ secrets.NPM_TOKEN }}
+
+      - name: Create Release Candidate Pull Request or Publish Release Candidate to npm
+        uses: changesets/action@v1
+        with:
+          publish: npm run release
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          NPM_TOKEN: ${{ secrets.NPM_TOKEN }}
+
+      - name: Exit RC mode
+        run: npx changeset pre exit
+
+      - name: Commit & Push changes
+        uses: actions-js/push@master
+        with:
+          github_token: ${{ secrets.GITHUB_TOKEN }}
+          branch: ${{ github.ref }}
+          message: 'chore: rc version bump'

.github/workflows/release.yml

@@ -3,6 +3,9 @@ on:
   push:
     branches:
       - main
+
+concurrency: ${{ github.workflow }}-${{ github.ref }}
+
 jobs:
   release:
     runs-on: ubuntu-latest
@@ -14,7 +17,7 @@ jobs:
       - uses: actions/setup-node@v4
         with:
           node-version: 20
-          cache: "npm"
+          cache: 'npm'
 
       - name: Cache node_modules
         uses: actions/cache@v4
@@ -30,6 +33,9 @@ jobs:
         run: npm ci
         timeout-minutes: 2
 
+      - name: Exit pre-release mode (safety check)
+        run: npx changeset pre exit || true
+
       - name: Create Release Pull Request or Publish to npm
         uses: changesets/action@v1
         with:

.gitignore

@@ -19,6 +19,8 @@ npm-debug.log*
 yarn-debug.log*
 yarn-error.log*
 lerna-debug.log*
+tests/e2e/_runs/
+tests/e2e/log/
 
 # Coverage directory used by tools like istanbul
 coverage
@@ -59,3 +61,6 @@ dist
 *.debug
 init-debug.log
 dev-debug.log
+
+# NPMRC
+.npmrc

.prettierignore

@@ -0,0 +1,7 @@
+# Ignore artifacts:
+build
+coverage
+.changeset
+tasks
+package-lock.json
+tests/fixture/*.json

.prettierrc

@@ -0,0 +1,11 @@
+{
+	"printWidth": 80,
+	"tabWidth": 2,
+	"useTabs": true,
+	"semi": true,
+	"singleQuote": true,
+	"trailingComma": "none",
+	"bracketSpacing": true,
+	"arrowParens": "always",
+	"endOfLine": "lf"
+}

.taskmasterconfig

@@ -0,0 +1,32 @@
+{
+	"models": {
+		"main": {
+			"provider": "anthropic",
+			"modelId": "claude-3-7-sonnet-20250219",
+			"maxTokens": 100000,
+			"temperature": 0.2
+		},
+		"research": {
+			"provider": "perplexity",
+			"modelId": "sonar-pro",
+			"maxTokens": 8700,
+			"temperature": 0.1
+		},
+		"fallback": {
+			"provider": "anthropic",
+			"modelId": "claude-3-7-sonnet-20250219",
+			"maxTokens": 8192,
+			"temperature": 0.2
+		}
+	},
+	"global": {
+		"logLevel": "info",
+		"debug": false,
+		"defaultSubtasks": 5,
+		"defaultPriority": "medium",
+		"projectName": "Taskmaster",
+		"ollamaBaseUrl": "http://localhost:11434/api",
+		"userId": "1234567890",
+		"azureOpenaiBaseUrl": "https://your-endpoint.openai.azure.com/"
+	}
+}

.vscode/extensions.json

@@ -0,0 +1,3 @@
+{
+	"recommendations": ["esbenp.prettier-vscode"]
+}

CHANGELOG.md

@@ -1,5 +1,218 @@
 # task-master-ai
 
+## 0.14.0-rc.0
+
+### Minor Changes
+
+- [#521](https://github.com/eyaltoledano/claude-task-master/pull/521) [`ed17cb0`](https://github.com/eyaltoledano/claude-task-master/commit/ed17cb0e0a04dedde6c616f68f24f3660f68dd04) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - .taskmasterconfig now supports a baseUrl field per model role (main, research, fallback), allowing endpoint overrides for any provider.
+
+- [#528](https://github.com/eyaltoledano/claude-task-master/pull/528) [`58b417a`](https://github.com/eyaltoledano/claude-task-master/commit/58b417a8ce697e655f749ca4d759b1c20014c523) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Display task complexity scores in task lists, next task, and task details views.
+
+### Patch Changes
+
+- [#478](https://github.com/eyaltoledano/claude-task-master/pull/478) [`4117f71`](https://github.com/eyaltoledano/claude-task-master/commit/4117f71c18ee4d321a9c91308d00d5d69bfac61e) Thanks [@joedanz](https://github.com/joedanz)! - Fix CLI --force flag for parse-prd command
+
+  Previously, the --force flag was not respected when running `parse-prd`, causing the command to prompt for confirmation or fail even when --force was provided. This patch ensures that the flag is correctly passed and handled, allowing users to overwrite existing tasks.json files as intended.
+
+  - Fixes #477
+
+- [#511](https://github.com/eyaltoledano/claude-task-master/pull/511) [`17294ff`](https://github.com/eyaltoledano/claude-task-master/commit/17294ff25918d64278674e558698a1a9ad785098) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Task Master no longer tells you to update when you're already up to date
+
+- [#523](https://github.com/eyaltoledano/claude-task-master/pull/523) [`da317f2`](https://github.com/eyaltoledano/claude-task-master/commit/da317f2607ca34db1be78c19954996f634c40923) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Fix the error handling of task status settings
+
+- [#527](https://github.com/eyaltoledano/claude-task-master/pull/527) [`a8dabf4`](https://github.com/eyaltoledano/claude-task-master/commit/a8dabf44856713f488960224ee838761716bba26) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Remove caching layer from MCP direct functions for task listing, next task, and complexity report
+
+  - Fixes issues users where having where they were getting stale data
+
+- [#417](https://github.com/eyaltoledano/claude-task-master/pull/417) [`a1f8d52`](https://github.com/eyaltoledano/claude-task-master/commit/a1f8d52474fdbdf48e17a63e3f567a6d63010d9f) Thanks [@ksylvan](https://github.com/ksylvan)! - Fix for issue #409 LOG_LEVEL Pydantic validation error
+
+- [#501](https://github.com/eyaltoledano/claude-task-master/pull/501) [`0a61184`](https://github.com/eyaltoledano/claude-task-master/commit/0a611843b56a856ef0a479dc34078326e05ac3a8) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Fix initial .env.example to work out of the box
+
+  - Closes #419
+
+- [#435](https://github.com/eyaltoledano/claude-task-master/pull/435) [`a96215a`](https://github.com/eyaltoledano/claude-task-master/commit/a96215a359b25061fd3b3f3c7b10e8ac0390c062) Thanks [@lebsral](https://github.com/lebsral)! - Fix default fallback model and maxTokens in Taskmaster initialization
+
+- [#517](https://github.com/eyaltoledano/claude-task-master/pull/517) [`e96734a`](https://github.com/eyaltoledano/claude-task-master/commit/e96734a6cc6fec7731de72eb46b182a6e3743d02) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Fix bug when updating tasks on the MCP server (#412)
+
+- [#496](https://github.com/eyaltoledano/claude-task-master/pull/496) [`efce374`](https://github.com/eyaltoledano/claude-task-master/commit/efce37469bc58eceef46763ba32df1ed45242211) Thanks [@joedanz](https://github.com/joedanz)! - Fix duplicate output on CLI help screen
+
+  - Prevent the Task Master CLI from printing the help screen more than once when using `-h` or `--help`.
+  - Removed redundant manual event handlers and guards for help output; now only the Commander `.helpInformation` override is used for custom help.
+  - Simplified logic so that help is only shown once for both "no arguments" and help flag flows.
+  - Ensures a clean, branded help experience with no repeated content.
+  - Fixes #339
+
+## 0.13.1
+
+### Patch Changes
+
+- [#399](https://github.com/eyaltoledano/claude-task-master/pull/399) [`734a4fd`](https://github.com/eyaltoledano/claude-task-master/commit/734a4fdcfc89c2e089255618cf940561ad13a3c8) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Fix ERR_MODULE_NOT_FOUND when trying to run MCP Server
+
+## 0.13.0
+
+### Minor Changes
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`ef782ff`](https://github.com/eyaltoledano/claude-task-master/commit/ef782ff5bd4ceb3ed0dc9ea82087aae5f79ac933) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - feat(expand): Enhance `expand` and `expand-all` commands
+
+  - Integrate `task-complexity-report.json` to automatically determine the number of subtasks and use tailored prompts for expansion based on prior analysis. You no longer need to try copy-pasting the recommended prompt. If it exists, it will use it for you. You can just run `task-master update --id=[id of task] --research` and it will use that prompt automatically. No extra prompt needed.
+  - Change default behavior to _append_ new subtasks to existing ones. Use the `--force` flag to clear existing subtasks before expanding. This is helpful if you need to add more subtasks to a task but you want to do it by the batch from a given prompt. Use force if you want to start fresh with a task's subtasks.
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`87d97bb`](https://github.com/eyaltoledano/claude-task-master/commit/87d97bba00d84e905756d46ef96b2d5b984e0f38) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Adds support for the OpenRouter AI provider. Users can now configure models available through OpenRouter (requiring an `OPENROUTER_API_KEY`) via the `task-master models` command, granting access to a wide range of additional LLMs. - IMPORTANT FYI ABOUT OPENROUTER: Taskmaster relies on AI SDK, which itself relies on tool use. It looks like **free** models sometimes do not include tool use. For example, Gemini 2.5 pro (free) failed via OpenRouter (no tool use) but worked fine on the paid version of the model. Custom model support for Open Router is considered experimental and likely will not be further improved for some time.
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`1ab836f`](https://github.com/eyaltoledano/claude-task-master/commit/1ab836f191cb8969153593a9a0bd47fc9aa4a831) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Adds model management and new configuration file .taskmasterconfig which houses the models used for main, research and fallback. Adds models command and setter flags. Adds a --setup flag with an interactive setup. We should be calling this during init. Shows a table of active and available models when models is called without flags. Includes SWE scores and token costs, which are manually entered into the supported_models.json, the new place where models are defined for support. Config-manager.js is the core module responsible for managing the new config."
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`c8722b0`](https://github.com/eyaltoledano/claude-task-master/commit/c8722b0a7a443a73b95d1bcd4a0b68e0fce2a1cd) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Adds custom model ID support for Ollama and OpenRouter providers.
+
+  - Adds the `--ollama` and `--openrouter` flags to `task-master models --set-<role>` command to set models for those providers outside of the support models list.
+  - Updated `task-master models --setup` interactive mode with options to explicitly enter custom Ollama or OpenRouter model IDs.
+  - Implemented live validation against OpenRouter API (`/api/v1/models`) when setting a custom OpenRouter model ID (via flag or setup).
+  - Refined logic to prioritize explicit provider flags/choices over internal model list lookups in case of ID conflicts.
+  - Added warnings when setting custom/unvalidated models.
+  - We obviously don't recommend going with a custom, unproven model. If you do and find performance is good, please let us know so we can add it to the list of supported models.
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`2517bc1`](https://github.com/eyaltoledano/claude-task-master/commit/2517bc112c9a497110f3286ca4bfb4130c9addcb) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Integrate OpenAI as a new AI provider. - Enhance `models` command/tool to display API key status. - Implement model-specific `maxTokens` override based on `supported-models.json` to save you if you use an incorrect max token value.
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`9a48278`](https://github.com/eyaltoledano/claude-task-master/commit/9a482789f7894f57f655fb8d30ba68542bd0df63) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Tweaks Perplexity AI calls for research mode to max out input tokens and get day-fresh information - Forces temp at 0.1 for highly deterministic output, no variations - Adds a system prompt to further improve the output - Correctly uses the maximum input tokens (8,719, used 8,700) for perplexity - Specificies to use a high degree of research across the web - Specifies to use information that is as fresh as today; this support stuff like capturing brand new announcements like new GPT models and being able to query for those in research. 🔥
+
+### Patch Changes
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`842eaf7`](https://github.com/eyaltoledano/claude-task-master/commit/842eaf722498ddf7307800b4cdcef4ac4fd7e5b0) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - - Add support for Google Gemini models via Vercel AI SDK integration.
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`ed79d4f`](https://github.com/eyaltoledano/claude-task-master/commit/ed79d4f4735dfab4124fa189214c0bd5e23a6860) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Add xAI provider and Grok models support
+
+- [#378](https://github.com/eyaltoledano/claude-task-master/pull/378) [`ad89253`](https://github.com/eyaltoledano/claude-task-master/commit/ad89253e313a395637aa48b9f92cc39b1ef94ad8) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Better support for file paths on Windows, Linux & WSL.
+
+  - Standardizes handling of different path formats (URI encoded, Windows, Linux, WSL).
+  - Ensures tools receive a clean, absolute path suitable for the server OS.
+  - Simplifies tool implementation by centralizing normalization logic.
+
+- [#285](https://github.com/eyaltoledano/claude-task-master/pull/285) [`2acba94`](https://github.com/eyaltoledano/claude-task-master/commit/2acba945c0afee9460d8af18814c87e80f747e9f) Thanks [@neno-is-ooo](https://github.com/neno-is-ooo)! - Add integration for Roo Code
+
+- [#378](https://github.com/eyaltoledano/claude-task-master/pull/378) [`d63964a`](https://github.com/eyaltoledano/claude-task-master/commit/d63964a10eed9be17856757661ff817ad6bacfdc) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Improved update-subtask - Now it has context about the parent task details - It also has context about the subtask before it and the subtask after it (if they exist) - Not passing all subtasks to stay token efficient
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`5f504fa`](https://github.com/eyaltoledano/claude-task-master/commit/5f504fafb8bdaa0043c2d20dee8bbb8ec2040d85) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Improve and adjust `init` command for robustness and updated dependencies.
+
+  - **Update Initialization Dependencies:** Ensure newly initialized projects (`task-master init`) include all required AI SDK dependencies (`@ai-sdk/*`, `ai`, provider wrappers) in their `package.json` for out-of-the-box AI feature compatibility. Remove unnecessary dependencies (e.g., `uuid`) from the init template.
+  - **Silence `npm install` during `init`:** Prevent `npm install` output from interfering with non-interactive/MCP initialization by suppressing its stdio in silent mode.
+  - **Improve Conditional Model Setup:** Reliably skip interactive `models --setup` during non-interactive `init` runs (e.g., `init -y` or MCP) by checking `isSilentMode()` instead of passing flags.
+  - **Refactor `init.js`:** Remove internal `isInteractive` flag logic.
+  - **Update `init` Instructions:** Tweak the "Getting Started" text displayed after `init`.
+  - **Fix MCP Server Launch:** Update `.cursor/mcp.json` template to use `node ./mcp-server/server.js` instead of `npx task-master-mcp`.
+  - **Update Default Model:** Change the default main model in the `.taskmasterconfig` template.
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`96aeeff`](https://github.com/eyaltoledano/claude-task-master/commit/96aeeffc195372722c6a07370540e235bfe0e4d8) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Fixes an issue with add-task which did not use the manually defined properties and still needlessly hit the AI endpoint.
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`5aea93d`](https://github.com/eyaltoledano/claude-task-master/commit/5aea93d4c0490c242d7d7042a210611977848e0a) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Fixes an issue that prevented remove-subtask with comma separated tasks/subtasks from being deleted (only the first ID was being deleted). Closes #140
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`66ac9ab`](https://github.com/eyaltoledano/claude-task-master/commit/66ac9ab9f66d006da518d6e8a3244e708af2764d) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Improves next command to be subtask-aware - The logic for determining the "next task" (findNextTask function, used by task-master next and the next_task MCP tool) has been significantly improved. Previously, it only considered top-level tasks, making its recommendation less useful when a parent task containing subtasks was already marked 'in-progress'. - The updated logic now prioritizes finding the next available subtask within any 'in-progress' parent task, considering subtask dependencies and priority. - If no suitable subtask is found within active parent tasks, it falls back to recommending the next eligible top-level task based on the original criteria (status, dependencies, priority).
+
+  This change makes the next command much more relevant and helpful during the implementation phase of complex tasks.
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`ca7b045`](https://github.com/eyaltoledano/claude-task-master/commit/ca7b0457f1dc65fd9484e92527d9fd6d69db758d) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Add `--status` flag to `show` command to filter displayed subtasks.
+
+- [#328](https://github.com/eyaltoledano/claude-task-master/pull/328) [`5a2371b`](https://github.com/eyaltoledano/claude-task-master/commit/5a2371b7cc0c76f5e95d43921c1e8cc8081bf14e) Thanks [@knoxgraeme](https://github.com/knoxgraeme)! - Fix --task to --num-tasks in ui + related tests - issue #324
+
+- [#240](https://github.com/eyaltoledano/claude-task-master/pull/240) [`6cb213e`](https://github.com/eyaltoledano/claude-task-master/commit/6cb213ebbd51116ae0688e35b575d09443d17c3b) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Adds a 'models' CLI and MCP command to get the current model configuration, available models, and gives the ability to set main/research/fallback models." - In the CLI, `task-master models` shows the current models config. Using the `--setup` flag launches an interactive set up that allows you to easily select the models you want to use for each of the three roles. Use `q` during the interactive setup to cancel the setup. - In the MCP, responses are simplified in RESTful format (instead of the full CLI output). The agent can use the `models` tool with different arguments, including `listAvailableModels` to get available models. Run without arguments, it will return the current configuration. Arguments are available to set the model for each of the three roles. This allows you to manage Taskmaster AI providers and models directly from either the CLI or MCP or both. - Updated the CLI help menu when you run `task-master` to include missing commands and .taskmasterconfig information. - Adds `--research` flag to `add-task` so you can hit up Perplexity right from the add-task flow, rather than having to add a task and then update it.
+
+## 0.12.1
+
+### Patch Changes
+
+- [#307](https://github.com/eyaltoledano/claude-task-master/pull/307) [`2829194`](https://github.com/eyaltoledano/claude-task-master/commit/2829194d3c1dd5373d3bf40275cf4f63b12d49a7) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Fix add_dependency tool crashing the MCP Server
+
+## 0.12.0
+
+### Minor Changes
+
+- [#253](https://github.com/eyaltoledano/claude-task-master/pull/253) [`b2ccd60`](https://github.com/eyaltoledano/claude-task-master/commit/b2ccd605264e47a61451b4c012030ee29011bb40) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Add `npx task-master-ai` that runs mcp instead of using `task-master-mcp``
+
+- [#267](https://github.com/eyaltoledano/claude-task-master/pull/267) [`c17d912`](https://github.com/eyaltoledano/claude-task-master/commit/c17d912237e6caaa2445e934fc48cd4841abf056) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Improve PRD parsing prompt with structured analysis and clearer task generation guidelines. We are testing a new prompt - please provide feedback on your experience.
+
+### Patch Changes
+
+- [#243](https://github.com/eyaltoledano/claude-task-master/pull/243) [`454a1d9`](https://github.com/eyaltoledano/claude-task-master/commit/454a1d9d37439c702656eedc0702c2f7a4451517) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - - Fixes shebang issue not allowing task-master to run on certain windows operating systems
+
+  - Resolves #241 #211 #184 #193
+
+- [#268](https://github.com/eyaltoledano/claude-task-master/pull/268) [`3e872f8`](https://github.com/eyaltoledano/claude-task-master/commit/3e872f8afbb46cd3978f3852b858c233450b9f33) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Fix remove-task command to handle multiple comma-separated task IDs
+
+- [#239](https://github.com/eyaltoledano/claude-task-master/pull/239) [`6599cb0`](https://github.com/eyaltoledano/claude-task-master/commit/6599cb0bf9eccecab528207836e9d45b8536e5c2) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Updates the parameter descriptions for update, update-task and update-subtask to ensure the MCP server correctly reaches for the right update command based on what is being updated -- all tasks, one task, or a subtask.
+
+- [#272](https://github.com/eyaltoledano/claude-task-master/pull/272) [`3aee9bc`](https://github.com/eyaltoledano/claude-task-master/commit/3aee9bc840eb8f31230bd1b761ed156b261cabc4) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Enhance the `parsePRD` to include `--append` flag. This flag allows users to append the parsed PRD to an existing file, making it easier to manage multiple PRD files without overwriting existing content.
+
+- [#264](https://github.com/eyaltoledano/claude-task-master/pull/264) [`ff8e75c`](https://github.com/eyaltoledano/claude-task-master/commit/ff8e75cded91fb677903040002626f7a82fd5f88) Thanks [@joedanz](https://github.com/joedanz)! - Add quotes around numeric env vars in mcp.json (Windsurf, etc.)
+
+- [#248](https://github.com/eyaltoledano/claude-task-master/pull/248) [`d99fa00`](https://github.com/eyaltoledano/claude-task-master/commit/d99fa00980fc61695195949b33dcda7781006f90) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - - Fix `task-master init` polluting codebase with new packages inside `package.json` and modifying project `README`
+
+  - Now only initializes with cursor rules, windsurf rules, mcp.json, scripts/example_prd.txt, .gitignore modifications, and `README-task-master.md`
+
+- [#266](https://github.com/eyaltoledano/claude-task-master/pull/266) [`41b979c`](https://github.com/eyaltoledano/claude-task-master/commit/41b979c23963483e54331015a86e7c5079f657e4) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Fixed a bug that prevented the task-master from running in a Linux container
+
+- [#265](https://github.com/eyaltoledano/claude-task-master/pull/265) [`0eb16d5`](https://github.com/eyaltoledano/claude-task-master/commit/0eb16d5ecbb8402d1318ca9509e9d4087b27fb25) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Remove the need for project name, description, and version. Since we no longer create a package.json for you
+
+## 0.11.0
+
+### Minor Changes
+
+- [#71](https://github.com/eyaltoledano/claude-task-master/pull/71) [`7141062`](https://github.com/eyaltoledano/claude-task-master/commit/71410629ba187776d92a31ea0729b2ff341b5e38) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - - **Easier Ways to Use Taskmaster (CLI & MCP):**
+  - You can now use Taskmaster either by installing it as a standard command-line tool (`task-master`) or as an MCP server directly within integrated development tools like Cursor (using its built-in features). **This makes Taskmaster accessible regardless of your preferred workflow.**
+  - Setting up a new project is simpler in integrated tools, thanks to the new `initialize_project` capability.
+  - **Complete MCP Implementation:**
+    - NOTE: Many MCP clients charge on a per tool basis. In that regard, the most cost-efficient way to use Taskmaster is through the CLI directly. Otherwise, the MCP offers the smoothest and most recommended user experience.
+    - All MCP tools now follow a standardized output format that mimicks RESTful API responses. They are lean JSON responses that are context-efficient. This is a net improvement over the last version which sent the whole CLI output directly, which needlessly wasted tokens.
+    - Added a `remove-task` command to permanently delete tasks you no longer need.
+    - Many new MCP tools are available for managing tasks (updating details, adding/removing subtasks, generating task files, setting status, finding the next task, breaking down complex tasks, handling dependencies, analyzing complexity, etc.), usable both from the command line and integrated tools. **(See the `taskmaster.mdc` reference guide and improved readme for a full list).**
+  - **Better Task Tracking:**
+    - Added a "cancelled" status option for tasks, providing more ways to categorize work.
+  - **Smoother Experience in Integrated Tools:**
+    - Long-running operations (like breaking down tasks or analysis) now run in the background **via an Async Operation Manager** with progress updates, so you know what's happening without waiting and can check status later.
+  - **Improved Documentation:**
+    - Added a comprehensive reference guide (`taskmaster.mdc`) detailing all commands and tools with examples, usage tips, and troubleshooting info. This is mostly for use by the AI but can be useful for human users as well.
+    - Updated the main README with clearer instructions and added a new tutorial/examples guide.
+    - Added documentation listing supported integrated tools (like Cursor).
+  - **Increased Stability & Reliability:**
+    - Using Taskmaster within integrated tools (like Cursor) is now **more stable and the recommended approach.**
+    - Added automated testing (CI) to catch issues earlier, leading to a more reliable tool.
+    - Fixed release process issues to ensure users get the correct package versions when installing or updating via npm.
+  - **Better Command-Line Experience:**
+    - Fixed bugs in the `expand-all` command that could cause **NaN errors or JSON formatting issues (especially when using `--research`).**
+    - Fixed issues with parameter validation in the `analyze-complexity` command (specifically related to the `threshold` parameter).
+    - Made the `add-task` command more consistent by adding standard flags like `--title`, `--description` for manual task creation so you don't have to use `--prompt` and can quickly drop new ideas and stay in your flow.
+    - Improved error messages for incorrect commands or flags, making them easier to understand.
+    - Added confirmation warnings before permanently deleting tasks (`remove-task`) to prevent mistakes. There's a known bug for deleting multiple tasks with comma-separated values. It'll be fixed next release.
+    - Renamed some background tool names used by integrated tools (e.g., `list-tasks` is now `get_tasks`) to be more intuitive if seen in logs or AI interactions.
+    - Smoother project start: **Improved the guidance provided to AI assistants immediately after setup** (related to `init` and `parse-prd` steps). This ensures the AI doesn't go on a tangent deciding its own workflow, and follows the exact process outlined in the Taskmaster workflow.
+  - **Clearer Error Messages:**
+    - When generating subtasks fails, error messages are now clearer, **including specific task IDs and potential suggestions.**
+    - AI fallback from Claude to Perplexity now also works the other way around. If Perplexity is down, will switch to Claude.
+  - **Simplified Setup & Configuration:**
+    - Made it clearer how to configure API keys depending on whether you're using the command-line tool (`.env` file) or an integrated tool (`.cursor/mcp.json` file).
+    - Taskmaster is now better at automatically finding your project files, especially in integrated tools, reducing the need for manual path settings.
+    - Fixed an issue that could prevent Taskmaster from working correctly immediately after initialization in integrated tools (related to how the MCP server was invoked). This should solve the issue most users were experiencing with the last release (0.10.x)
+    - Updated setup templates with clearer examples for API keys.
+    - \*\*For advanced users setting up the MCP server manually, the command is now `npx -y task-master-ai task-master-mcp`.
+  - **Enhanced Performance & AI:**
+    - Updated underlying AI model settings:
+      - **Increased Context Window:** Can now handle larger projects/tasks due to an increased Claude context window (64k -> 128k tokens).
+      - **Reduced AI randomness:** More consistent and predictable AI outputs (temperature 0.4 -> 0.2).
+      - **Updated default AI models:** Uses newer models like `claude-3-7-sonnet-20250219` and Perplexity `sonar-pro` by default.
+      - **More granular breakdown:** Increased the default number of subtasks generated by `expand` to 5 (from 4).
+      - **Consistent defaults:** Set the default priority for new tasks consistently to "medium".
+    - Improved performance when viewing task details in integrated tools by sending less redundant data.
+  - **Documentation Clarity:**
+    - Clarified in documentation that Markdown files (`.md`) can be used for Product Requirements Documents (`parse_prd`).
+    - Improved the description for the `numTasks` option in `parse_prd` for better guidance.
+  - **Improved Visuals (CLI):**
+    - Enhanced the look and feel of progress bars and status updates in the command line.
+    - Added a helpful color-coded progress bar to the task details view (`show` command) to visualize subtask completion.
+    - Made progress bars show a breakdown of task statuses (e.g., how many are pending vs. done).
+    - Made status counts clearer with text labels next to icons.
+    - Prevented progress bars from messing up the display on smaller terminal windows.
+    - Adjusted how progress is calculated for 'deferred' and 'cancelled' tasks in the progress bar, while still showing their distinct status visually.
+  - **Fixes for Integrated Tools:**
+    - Fixed how progress updates are sent to integrated tools, ensuring they display correctly.
+    - Fixed internal issues that could cause errors or invalid JSON responses when using Taskmaster with integrated tools.
+
 ## 0.10.1
 
 ### Patch Changes

LICENSE.md

@@ -1,90 +0,0 @@
-# Dual License
-
-This project is licensed under two separate licenses:
-
-1. [Business Source License 1.1](#business-source-license-11) (BSL 1.1) for commercial use of Task Master itself
-2. [Apache License 2.0](#apache-license-20) for all other uses
-
-## Business Source License 1.1
-
-Terms: https://mariadb.com/bsl11/
-
-Licensed Work: Task Master AI
-Additional Use Grant: You may use Task Master AI to create and commercialize your own projects and products.
-
-Change Date: 2025-03-30
-Change License: None
-
-The Licensed Work is subject to the Business Source License 1.1. If you are interested in using the Licensed Work in a way that competes directly with Task Master, please contact the licensors.
-
-### Licensor
-
-- Eyal Toledano (GitHub: @eyaltoledano)
-- Ralph (GitHub: @Crunchyman-ralph)
-
-### Commercial Use Restrictions
-
-This license explicitly restricts certain commercial uses of Task Master AI to the Licensors listed above. Restricted commercial uses include:
-
-1. Creating commercial products or services that directly compete with Task Master AI
-2. Selling Task Master AI itself as a service
-3. Offering Task Master AI's functionality as a commercial managed service
-4. Reselling or redistributing Task Master AI for a fee
-
-### Explicitly Permitted Uses
-
-The following uses are explicitly allowed under this license:
-
-1. Using Task Master AI to create and commercialize your own projects
-2. Using Task Master AI in commercial environments for internal development
-3. Building and selling products or services that were created using Task Master AI
-4. Using Task Master AI for commercial development as long as you're not selling Task Master AI itself
-
-### Additional Terms
-
-1. The right to commercialize Task Master AI itself is exclusively reserved for the Licensors
-2. No party may create commercial products that directly compete with Task Master AI without explicit written permission
-3. Forks of this repository are subject to the same restrictions regarding direct competition
-4. Contributors agree that their contributions will be subject to this same dual licensing structure
-
-## Apache License 2.0
-
-For all uses other than those restricted above. See [APACHE-LICENSE](./APACHE-LICENSE) for the full license text.
-
-### Permitted Use Definition
-
-You may use Task Master AI for any purpose, including commercial purposes, as long as you are not:
-
-1. Creating a direct competitor to Task Master AI
-2. Selling Task Master AI itself as a service
-3. Redistributing Task Master AI for a fee
-
-### Requirements for Use
-
-1. You must include appropriate copyright notices
-2. You must state significant changes made to the software
-3. You must preserve all license notices
-
-## Questions and Commercial Licensing
-
-For questions about licensing or to inquire about commercial use that may compete with Task Master, please contact:
-
-- Eyal Toledano (GitHub: @eyaltoledano)
-- Ralph (GitHub: @Crunchyman-ralph)
-
-## Examples
-
-### ✅ Allowed Uses
-
-- Using Task Master to create a commercial SaaS product
-- Using Task Master in your company for development
-- Creating and selling products that were built using Task Master
-- Using Task Master to generate code for commercial projects
-- Offering consulting services where you use Task Master
-
-### ❌ Restricted Uses
-
-- Creating a competing AI task management tool
-- Selling access to Task Master as a service
-- Creating a hosted version of Task Master
-- Reselling Task Master's functionality

README-task-master.md

@@ -13,25 +13,22 @@ A task management system for AI-driven development with Claude, designed to work
 
 ## Configuration
 
-The script can be configured through environment variables in a `.env` file at the root of the project:
+Taskmaster uses two primary configuration methods:
 
-### Required Configuration
+1.  **`.taskmasterconfig` File (Project Root)**
 
-- `ANTHROPIC_API_KEY`: Your Anthropic API key for Claude
+    - Stores most settings: AI model selections (main, research, fallback), parameters (max tokens, temperature), logging level, default priority/subtasks, project name.
+    - **Created and managed using `task-master models --setup` CLI command or the `models` MCP tool.**
+    - Do not edit manually unless you know what you are doing.
 
-### Optional Configuration
+2.  **Environment Variables (`.env` file or MCP `env` block)**
+    - Used **only** for sensitive **API Keys** (e.g., `ANTHROPIC_API_KEY`, `PERPLEXITY_API_KEY`, etc.) and specific endpoints (like `OLLAMA_BASE_URL`).
+    - **For CLI:** Place keys in a `.env` file in your project root.
+    - **For MCP/Cursor:** Place keys in the `env` section of your `.cursor/mcp.json` (or other MCP config according to the AI IDE or client you use) file under the `taskmaster-ai` server definition.
 
-- `MODEL`: Specify which Claude model to use (default: "claude-3-7-sonnet-20250219")
-- `MAX_TOKENS`: Maximum tokens for model responses (default: 4000)
-- `TEMPERATURE`: Temperature for model responses (default: 0.7)
-- `PERPLEXITY_API_KEY`: Your Perplexity API key for research-backed subtask generation
-- `PERPLEXITY_MODEL`: Specify which Perplexity model to use (default: "sonar-medium-online")
-- `DEBUG`: Enable debug logging (default: false)
-- `LOG_LEVEL`: Log level - debug, info, warn, error (default: info)
-- `DEFAULT_SUBTASKS`: Default number of subtasks when expanding (default: 3)
-- `DEFAULT_PRIORITY`: Default priority for generated tasks (default: medium)
-- `PROJECT_NAME`: Override default project name in tasks.json
-- `PROJECT_VERSION`: Override default version in tasks.json
+**Important:** Settings like model choices, max tokens, temperature, and log level are **no longer configured via environment variables.** Use the `task-master models` command or tool.
+
+See the [Configuration Guide](docs/configuration.md) for full details.
 
 ## Installation
 
@@ -50,7 +47,7 @@ npm install task-master-ai
 task-master init
 
 # If installed locally
-npx task-master-init
+npx task-master init
 ```
 
 This will prompt you for project details and set up a new project with the necessary files and structure.
@@ -58,6 +55,7 @@ This will prompt you for project details and set up a new project with the neces
 ### Important Notes
 
 1. **ES Modules Configuration:**
+
    - This project uses ES Modules (ESM) instead of CommonJS.
    - This is set via `"type": "module"` in your package.json.
    - Use `import/export` syntax instead of `require()`.
@@ -145,7 +143,7 @@ To enable enhanced task management capabilities directly within Cursor using the
 4. Configure with the following details:
    - Name: "Task Master"
    - Type: "Command"
-   - Command: "npx -y --package task-master-ai task-master-mcp"
+   - Command: "npx -y task-master-ai"
 5. Save the settings
 
 Once configured, you can interact with Task Master's task management commands directly through Cursor's interface, providing a more integrated experience.

README.md

@@ -1,62 +1,81 @@
-# Task Master
+# Task Master [![GitHub stars](https://img.shields.io/github/stars/eyaltoledano/claude-task-master?style=social)](https://github.com/eyaltoledano/claude-task-master/stargazers)
 
-[![CI](https://github.com/eyaltoledano/claude-task-master/actions/workflows/ci.yml/badge.svg)](https://github.com/eyaltoledano/claude-task-master/actions/workflows/ci.yml)
-[![License: MIT with Commons Clause](https://img.shields.io/badge/license-MIT%20with%20Commons%20Clause-blue.svg)](LICENSE)
-[![npm version](https://badge.fury.io/js/task-master-ai.svg)](https://badge.fury.io/js/task-master-ai)
+[![CI](https://github.com/eyaltoledano/claude-task-master/actions/workflows/ci.yml/badge.svg)](https://github.com/eyaltoledano/claude-task-master/actions/workflows/ci.yml) [![npm version](https://badge.fury.io/js/task-master-ai.svg)](https://badge.fury.io/js/task-master-ai) [![Discord](https://dcbadge.limes.pink/api/server/https://discord.gg/taskmasterai?style=flat)](https://discord.gg/taskmasterai) [![License: MIT with Commons Clause](https://img.shields.io/badge/license-MIT%20with%20Commons%20Clause-blue.svg)](LICENSE)
 
-### by [@eyaltoledano](https://x.com/eyaltoledano)
+### By [@eyaltoledano](https://x.com/eyaltoledano) & [@RalphEcom](https://x.com/RalphEcom)
+
+[![Twitter Follow](https://img.shields.io/twitter/follow/eyaltoledano?style=flat)](https://x.com/eyaltoledano)
+[![Twitter Follow](https://img.shields.io/twitter/follow/RalphEcom?style=flat)](https://x.com/RalphEcom)
 
 A task management system for AI-driven development with Claude, designed to work seamlessly with Cursor AI.
 
-## Licensing
-
-Task Master is licensed under the MIT License with Commons Clause. This means you can:
-
-✅ **Allowed**:
-
-- Use Task Master for any purpose (personal, commercial, academic)
-- Modify the code
-- Distribute copies
-- Create and sell products built using Task Master
-
-❌ **Not Allowed**:
-
-- Sell Task Master itself
-- Offer Task Master as a hosted service
-- Create competing products based on Task Master
-
-See the [LICENSE](LICENSE) file for the complete license text.
-
 ## Requirements
 
-- Node.js 14.0.0 or higher
+Taskmaster utilizes AI across several commands, and those require a separate API key. You can use a variety of models from different AI providers provided you add your API keys. For example, if you want to use Claude 3.7, you'll need an Anthropic API key.
+
+You can define 3 types of models to be used: the main model, the research model, and the fallback model (in case either the main or research fail). Whatever model you use, its provider API key must be present in either mcp.json or .env.
+
+At least one (1) of the following is required:
+
 - Anthropic API key (Claude API)
-- Anthropic SDK version 0.39.0 or higher
-- OpenAI SDK (for Perplexity API integration, optional)
+- OpenAI API key
+- Google Gemini API key
+- Perplexity API key (for research model)
+- xAI API Key (for research or main model)
+- OpenRouter API Key (for research or main model)
 
-## Configuration
+Using the research model is optional but highly recommended. You will need at least ONE API key. Adding all API keys enables you to seamlessly switch between model providers at will.
 
-The script can be configured through environment variables in a `.env` file at the root of the project:
+## Quick Start
 
-### Required Configuration
+### Option 1 | MCP (Recommended):
 
-- `ANTHROPIC_API_KEY`: Your Anthropic API key for Claude
+MCP (Model Control Protocol) provides the easiest way to get started with Task Master directly in your editor.
 
-### Optional Configuration
+1. **Add the MCP config to your editor** (Cursor recommended, but it works with other text editors):
 
-- `MODEL`: Specify which Claude model to use (default: "claude-3-7-sonnet-20250219")
-- `MAX_TOKENS`: Maximum tokens for model responses (default: 4000)
-- `TEMPERATURE`: Temperature for model responses (default: 0.7)
-- `PERPLEXITY_API_KEY`: Your Perplexity API key for research-backed subtask generation
-- `PERPLEXITY_MODEL`: Specify which Perplexity model to use (default: "sonar-medium-online")
-- `DEBUG`: Enable debug logging (default: false)
-- `LOG_LEVEL`: Log level - debug, info, warn, error (default: info)
-- `DEFAULT_SUBTASKS`: Default number of subtasks when expanding (default: 3)
-- `DEFAULT_PRIORITY`: Default priority for generated tasks (default: medium)
-- `PROJECT_NAME`: Override default project name in tasks.json
-- `PROJECT_VERSION`: Override default version in tasks.json
+```json
+{
+	"mcpServers": {
+		"taskmaster-ai": {
+			"command": "npx",
+			"args": ["-y", "--package=task-master-ai", "task-master-ai"],
+			"env": {
+				"ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE",
+				"PERPLEXITY_API_KEY": "YOUR_PERPLEXITY_API_KEY_HERE",
+				"OPENAI_API_KEY": "YOUR_OPENAI_KEY_HERE",
+				"GOOGLE_API_KEY": "YOUR_GOOGLE_KEY_HERE",
+				"MISTRAL_API_KEY": "YOUR_MISTRAL_KEY_HERE",
+				"OPENROUTER_API_KEY": "YOUR_OPENROUTER_KEY_HERE",
+				"XAI_API_KEY": "YOUR_XAI_KEY_HERE",
+				"AZURE_OPENAI_API_KEY": "YOUR_AZURE_KEY_HERE",
+				"OLLAMA_API_KEY": "YOUR_OLLAMA_API_KEY_HERE"
+			}
+		}
+	}
+}
+```
 
-## Installation
+2. **Enable the MCP** in your editor
+
+3. **Prompt the AI** to initialize Task Master:
+
+```
+Can you please initialize taskmaster-ai into my project?
+```
+
+4. **Use common commands** directly through your AI assistant:
+
+```txt
+Can you parse my PRD at scripts/prd.txt?
+What's the next task I should work on?
+Can you help me implement task 3?
+Can you help me expand task 4?
+```
+
+### Option 2: Using Command Line
+
+#### Installation
 
 ```bash
 # Install globally
@@ -66,26 +85,19 @@ npm install -g task-master-ai
 npm install task-master-ai
 ```
 
-### Initialize a new project
+#### Initialize a new project
 
 ```bash
 # If installed globally
 task-master init
 
 # If installed locally
-npx task-master-init
+npx task-master init
 ```
 
 This will prompt you for project details and set up a new project with the necessary files and structure.
 
-### Important Notes
-
-1. This package uses ES modules. Your package.json should include `"type": "module"`.
-2. The Anthropic SDK version should be 0.39.0 or higher.
-
-## Quick Start with Global Commands
-
-After installing the package globally, you can use these CLI commands from any directory:
+#### Common Commands
 
 ```bash
 # Initialize a new project
@@ -104,6 +116,16 @@ task-master next
 task-master generate
 ```
 
+## Documentation
+
+For more detailed information, check out the documentation in the `docs` directory:
+
+- [Configuration Guide](docs/configuration.md) - Set up environment variables and customize Task Master
+- [Tutorial](docs/tutorial.md) - Step-by-step guide to getting started with Task Master
+- [Command Reference](docs/command-reference.md) - Complete list of all available commands
+- [Task Structure](docs/task-structure.md) - Understanding the task format and features
+- [Example Interactions](docs/examples.md) - Common Cursor AI interaction examples
+
 ## Troubleshooting
 
 ### If `task-master init` doesn't respond:
@@ -122,577 +144,31 @@ cd claude-task-master
 node scripts/init.js
 ```
 
-## Task Structure
+## Contributors
 
-Tasks in tasks.json have the following structure:
+<a href="https://github.com/eyaltoledano/claude-task-master/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=eyaltoledano/claude-task-master" alt="Task Master project contributors" />
+</a>
 
-- `id`: Unique identifier for the task (Example: `1`)
-- `title`: Brief, descriptive title of the task (Example: `"Initialize Repo"`)
-- `description`: Concise description of what the task involves (Example: `"Create a new repository, set up initial structure."`)
-- `status`: Current state of the task (Example: `"pending"`, `"done"`, `"deferred"`)
-- `dependencies`: IDs of tasks that must be completed before this task (Example: `[1, 2]`)
-  - Dependencies are displayed with status indicators (✅ for completed, ⏱️ for pending)
-  - This helps quickly identify which prerequisite tasks are blocking work
-- `priority`: Importance level of the task (Example: `"high"`, `"medium"`, `"low"`)
-- `details`: In-depth implementation instructions (Example: `"Use GitHub client ID/secret, handle callback, set session token."`)
-- `testStrategy`: Verification approach (Example: `"Deploy and call endpoint to confirm 'Hello World' response."`)
-- `subtasks`: List of smaller, more specific tasks that make up the main task (Example: `[{"id": 1, "title": "Configure OAuth", ...}]`)
+## Star History
 
-## Integrating with Cursor AI
+[![Star History Chart](https://api.star-history.com/svg?repos=eyaltoledano/claude-task-master&type=Timeline)](https://www.star-history.com/#eyaltoledano/claude-task-master&Timeline)
 
-Claude Task Master is designed to work seamlessly with [Cursor AI](https://www.cursor.so/), providing a structured workflow for AI-driven development.
+## Licensing
 
-### Setup with Cursor
+Task Master is licensed under the MIT License with Commons Clause. This means you can:
 
-1. After initializing your project, open it in Cursor
-2. The `.cursor/rules/dev_workflow.mdc` file is automatically loaded by Cursor, providing the AI with knowledge about the task management system
-3. Place your PRD document in the `scripts/` directory (e.g., `scripts/prd.txt`)
-4. Open Cursor's AI chat and switch to Agent mode
+✅ **Allowed**:
 
-### Setting up MCP in Cursor
+- Use Task Master for any purpose (personal, commercial, academic)
+- Modify the code
+- Distribute copies
+- Create and sell products built using Task Master
 
-To enable enhanced task management capabilities directly within Cursor using the Model Control Protocol (MCP):
+❌ **Not Allowed**:
 
-1. Go to Cursor settings
-2. Navigate to the MCP section
-3. Click on "Add New MCP Server"
-4. Configure with the following details:
-   - Name: "Task Master"
-   - Type: "Command"
-   - Command: "npx -y --package task-master-ai task-master-mcp"
-5. Save the settings
+- Sell Task Master itself
+- Offer Task Master as a hosted service
+- Create competing products based on Task Master
 
-Once configured, you can interact with Task Master's task management commands directly through Cursor's interface, providing a more integrated experience.
-
-### Initial Task Generation
-
-In Cursor's AI chat, instruct the agent to generate tasks from your PRD:
-
-```
-Please use the task-master parse-prd command to generate tasks from my PRD. The PRD is located at scripts/prd.txt.
-```
-
-The agent will execute:
-
-```bash
-task-master parse-prd scripts/prd.txt
-```
-
-This will:
-
-- Parse your PRD document
-- Generate a structured `tasks.json` file with tasks, dependencies, priorities, and test strategies
-- The agent will understand this process due to the Cursor rules
-
-### Generate Individual Task Files
-
-Next, ask the agent to generate individual task files:
-
-```
-Please generate individual task files from tasks.json
-```
-
-The agent will execute:
-
-```bash
-task-master generate
-```
-
-This creates individual task files in the `tasks/` directory (e.g., `task_001.txt`, `task_002.txt`), making it easier to reference specific tasks.
-
-## AI-Driven Development Workflow
-
-The Cursor agent is pre-configured (via the rules file) to follow this workflow:
-
-### 1. Task Discovery and Selection
-
-Ask the agent to list available tasks:
-
-```
-What tasks are available to work on next?
-```
-
-The agent will:
-
-- Run `task-master list` to see all tasks
-- Run `task-master next` to determine the next task to work on
-- Analyze dependencies to determine which tasks are ready to be worked on
-- Prioritize tasks based on priority level and ID order
-- Suggest the next task(s) to implement
-
-### 2. Task Implementation
-
-When implementing a task, the agent will:
-
-- Reference the task's details section for implementation specifics
-- Consider dependencies on previous tasks
-- Follow the project's coding standards
-- Create appropriate tests based on the task's testStrategy
-
-You can ask:
-
-```
-Let's implement task 3. What does it involve?
-```
-
-### 3. Task Verification
-
-Before marking a task as complete, verify it according to:
-
-- The task's specified testStrategy
-- Any automated tests in the codebase
-- Manual verification if required
-
-### 4. Task Completion
-
-When a task is completed, tell the agent:
-
-```
-Task 3 is now complete. Please update its status.
-```
-
-The agent will execute:
-
-```bash
-task-master set-status --id=3 --status=done
-```
-
-### 5. Handling Implementation Drift
-
-If during implementation, you discover that:
-
-- The current approach differs significantly from what was planned
-- Future tasks need to be modified due to current implementation choices
-- New dependencies or requirements have emerged
-
-Tell the agent:
-
-```
-We've changed our approach. We're now using Express instead of Fastify. Please update all future tasks to reflect this change.
-```
-
-The agent will execute:
-
-```bash
-task-master update --from=4 --prompt="Now we are using Express instead of Fastify."
-```
-
-This will rewrite or re-scope subsequent tasks in tasks.json while preserving completed work.
-
-### 6. Breaking Down Complex Tasks
-
-For complex tasks that need more granularity:
-
-```
-Task 5 seems complex. Can you break it down into subtasks?
-```
-
-The agent will execute:
-
-```bash
-task-master expand --id=5 --num=3
-```
-
-You can provide additional context:
-
-```
-Please break down task 5 with a focus on security considerations.
-```
-
-The agent will execute:
-
-```bash
-task-master expand --id=5 --prompt="Focus on security aspects"
-```
-
-You can also expand all pending tasks:
-
-```
-Please break down all pending tasks into subtasks.
-```
-
-The agent will execute:
-
-```bash
-task-master expand --all
-```
-
-For research-backed subtask generation using Perplexity AI:
-
-```
-Please break down task 5 using research-backed generation.
-```
-
-The agent will execute:
-
-```bash
-task-master expand --id=5 --research
-```
-
-## Command Reference
-
-Here's a comprehensive reference of all available commands:
-
-### Parse PRD
-
-```bash
-# Parse a PRD file and generate tasks
-task-master parse-prd <prd-file.txt>
-
-# Limit the number of tasks generated
-task-master parse-prd <prd-file.txt> --num-tasks=10
-```
-
-### List Tasks
-
-```bash
-# List all tasks
-task-master list
-
-# List tasks with a specific status
-task-master list --status=<status>
-
-# List tasks with subtasks
-task-master list --with-subtasks
-
-# List tasks with a specific status and include subtasks
-task-master list --status=<status> --with-subtasks
-```
-
-### Show Next Task
-
-```bash
-# Show the next task to work on based on dependencies and status
-task-master next
-```
-
-### Show Specific Task
-
-```bash
-# Show details of a specific task
-task-master show <id>
-# or
-task-master show --id=<id>
-
-# View a specific subtask (e.g., subtask 2 of task 1)
-task-master show 1.2
-```
-
-### Update Tasks
-
-```bash
-# Update tasks from a specific ID and provide context
-task-master update --from=<id> --prompt="<prompt>"
-```
-
-### Update a Specific Task
-
-```bash
-# Update a single task by ID with new information
-task-master update-task --id=<id> --prompt="<prompt>"
-
-# Use research-backed updates with Perplexity AI
-task-master update-task --id=<id> --prompt="<prompt>" --research
-```
-
-### Update a Subtask
-
-```bash
-# Append additional information to a specific subtask
-task-master update-subtask --id=<parentId.subtaskId> --prompt="<prompt>"
-
-# Example: Add details about API rate limiting to subtask 2 of task 5
-task-master update-subtask --id=5.2 --prompt="Add rate limiting of 100 requests per minute"
-
-# Use research-backed updates with Perplexity AI
-task-master update-subtask --id=<parentId.subtaskId> --prompt="<prompt>" --research
-```
-
-Unlike the `update-task` command which replaces task information, the `update-subtask` command _appends_ new information to the existing subtask details, marking it with a timestamp. This is useful for iteratively enhancing subtasks while preserving the original content.
-
-### Remove Task
-
-```bash
-# Remove a task permanently
-task-master remove-task --id=<id>
-
-# Remove a subtask permanently
-task-master remove-task --id=<parentId.subtaskId>
-
-# Skip the confirmation prompt
-task-master remove-task --id=<id> --yes
-```
-
-The `remove-task` command permanently deletes a task or subtask from `tasks.json`. It also automatically cleans up any references to the deleted task in other tasks' dependencies. Consider using 'blocked', 'cancelled', or 'deferred' status instead if you want to keep the task for reference.
-
-### Generate Task Files
-
-```bash
-# Generate individual task files from tasks.json
-task-master generate
-```
-
-### Set Task Status
-
-```bash
-# Set status of a single task
-task-master set-status --id=<id> --status=<status>
-
-# Set status for multiple tasks
-task-master set-status --id=1,2,3 --status=<status>
-
-# Set status for subtasks
-task-master set-status --id=1.1,1.2 --status=<status>
-```
-
-When marking a task as "done", all of its subtasks will automatically be marked as "done" as well.
-
-### Expand Tasks
-
-```bash
-# Expand a specific task with subtasks
-task-master expand --id=<id> --num=<number>
-
-# Expand with additional context
-task-master expand --id=<id> --prompt="<context>"
-
-# Expand all pending tasks
-task-master expand --all
-
-# Force regeneration of subtasks for tasks that already have them
-task-master expand --all --force
-
-# Research-backed subtask generation for a specific task
-task-master expand --id=<id> --research
-
-# Research-backed generation for all tasks
-task-master expand --all --research
-```
-
-### Clear Subtasks
-
-```bash
-# Clear subtasks from a specific task
-task-master clear-subtasks --id=<id>
-
-# Clear subtasks from multiple tasks
-task-master clear-subtasks --id=1,2,3
-
-# Clear subtasks from all tasks
-task-master clear-subtasks --all
-```
-
-### Analyze Task Complexity
-
-```bash
-# Analyze complexity of all tasks
-task-master analyze-complexity
-
-# Save report to a custom location
-task-master analyze-complexity --output=my-report.json
-
-# Use a specific LLM model
-task-master analyze-complexity --model=claude-3-opus-20240229
-
-# Set a custom complexity threshold (1-10)
-task-master analyze-complexity --threshold=6
-
-# Use an alternative tasks file
-task-master analyze-complexity --file=custom-tasks.json
-
-# Use Perplexity AI for research-backed complexity analysis
-task-master analyze-complexity --research
-```
-
-### View Complexity Report
-
-```bash
-# Display the task complexity analysis report
-task-master complexity-report
-
-# View a report at a custom location
-task-master complexity-report --file=my-report.json
-```
-
-### Managing Task Dependencies
-
-```bash
-# Add a dependency to a task
-task-master add-dependency --id=<id> --depends-on=<id>
-
-# Remove a dependency from a task
-task-master remove-dependency --id=<id> --depends-on=<id>
-
-# Validate dependencies without fixing them
-task-master validate-dependencies
-
-# Find and fix invalid dependencies automatically
-task-master fix-dependencies
-```
-
-### Add a New Task
-
-```bash
-# Add a new task using AI
-task-master add-task --prompt="Description of the new task"
-
-# Add a task with dependencies
-task-master add-task --prompt="Description" --dependencies=1,2,3
-
-# Add a task with priority
-task-master add-task --prompt="Description" --priority=high
-```
-
-## Feature Details
-
-### Analyzing Task Complexity
-
-The `analyze-complexity` command:
-
-- Analyzes each task using AI to assess its complexity on a scale of 1-10
-- Recommends optimal number of subtasks based on configured DEFAULT_SUBTASKS
-- Generates tailored prompts for expanding each task
-- Creates a comprehensive JSON report with ready-to-use commands
-- Saves the report to scripts/task-complexity-report.json by default
-
-The generated report contains:
-
-- Complexity analysis for each task (scored 1-10)
-- Recommended number of subtasks based on complexity
-- AI-generated expansion prompts customized for each task
-- Ready-to-run expansion commands directly within each task analysis
-
-### Viewing Complexity Report
-
-The `complexity-report` command:
-
-- Displays a formatted, easy-to-read version of the complexity analysis report
-- Shows tasks organized by complexity score (highest to lowest)
-- Provides complexity distribution statistics (low, medium, high)
-- Highlights tasks recommended for expansion based on threshold score
-- Includes ready-to-use expansion commands for each complex task
-- If no report exists, offers to generate one on the spot
-
-### Smart Task Expansion
-
-The `expand` command automatically checks for and uses the complexity report:
-
-When a complexity report exists:
-
-- Tasks are automatically expanded using the recommended subtask count and prompts
-- When expanding all tasks, they're processed in order of complexity (highest first)
-- Research-backed generation is preserved from the complexity analysis
-- You can still override recommendations with explicit command-line options
-
-Example workflow:
-
-```bash
-# Generate the complexity analysis report with research capabilities
-task-master analyze-complexity --research
-
-# Review the report in a readable format
-task-master complexity-report
-
-# Expand tasks using the optimized recommendations
-task-master expand --id=8
-# or expand all tasks
-task-master expand --all
-```
-
-### Finding the Next Task
-
-The `next` command:
-
-- Identifies tasks that are pending/in-progress and have all dependencies satisfied
-- Prioritizes tasks by priority level, dependency count, and task ID
-- Displays comprehensive information about the selected task:
-  - Basic task details (ID, title, priority, dependencies)
-  - Implementation details
-  - Subtasks (if they exist)
-- Provides contextual suggested actions:
-  - Command to mark the task as in-progress
-  - Command to mark the task as done
-  - Commands for working with subtasks
-
-### Viewing Specific Task Details
-
-The `show` command:
-
-- Displays comprehensive details about a specific task or subtask
-- Shows task status, priority, dependencies, and detailed implementation notes
-- For parent tasks, displays all subtasks and their status
-- For subtasks, shows parent task relationship
-- Provides contextual action suggestions based on the task's state
-- Works with both regular tasks and subtasks (using the format taskId.subtaskId)
-
-## Best Practices for AI-Driven Development
-
-1. **Start with a detailed PRD**: The more detailed your PRD, the better the generated tasks will be.
-
-2. **Review generated tasks**: After parsing the PRD, review the tasks to ensure they make sense and have appropriate dependencies.
-
-3. **Analyze task complexity**: Use the complexity analysis feature to identify which tasks should be broken down further.
-
-4. **Follow the dependency chain**: Always respect task dependencies - the Cursor agent will help with this.
-
-5. **Update as you go**: If your implementation diverges from the plan, use the update command to keep future tasks aligned with your current approach.
-
-6. **Break down complex tasks**: Use the expand command to break down complex tasks into manageable subtasks.
-
-7. **Regenerate task files**: After any updates to tasks.json, regenerate the task files to keep them in sync.
-
-8. **Communicate context to the agent**: When asking the Cursor agent to help with a task, provide context about what you're trying to achieve.
-
-9. **Validate dependencies**: Periodically run the validate-dependencies command to check for invalid or circular dependencies.
-
-## Example Cursor AI Interactions
-
-### Starting a new project
-
-```
-I've just initialized a new project with Claude Task Master. I have a PRD at scripts/prd.txt.
-Can you help me parse it and set up the initial tasks?
-```
-
-### Working on tasks
-
-```
-What's the next task I should work on? Please consider dependencies and priorities.
-```
-
-### Implementing a specific task
-
-```
-I'd like to implement task 4. Can you help me understand what needs to be done and how to approach it?
-```
-
-### Managing subtasks
-
-```
-I need to regenerate the subtasks for task 3 with a different approach. Can you help me clear and regenerate them?
-```
-
-### Handling changes
-
-```
-We've decided to use MongoDB instead of PostgreSQL. Can you update all future tasks to reflect this change?
-```
-
-### Completing work
-
-```
-I've finished implementing the authentication system described in task 2. All tests are passing.
-Please mark it as complete and tell me what I should work on next.
-```
-
-### Analyzing complexity
-
-```
-Can you analyze the complexity of our tasks to help me understand which ones need to be broken down further?
-```
-
-### Viewing complexity report
-
-```
-Can you show me the complexity report in a more readable format?
-```
+See the [LICENSE](LICENSE) file for the complete license text and [licensing details](docs/licensing.md) for more information.

assets/.taskmasterconfig

@@ -0,0 +1,31 @@
+{
+	"models": {
+		"main": {
+			"provider": "anthropic",
+			"modelId": "claude-3-7-sonnet-20250219",
+			"maxTokens": 120000,
+			"temperature": 0.2
+		},
+		"research": {
+			"provider": "perplexity",
+			"modelId": "sonar-pro",
+			"maxTokens": 8700,
+			"temperature": 0.1
+		},
+		"fallback": {
+			"provider": "anthropic",
+			"modelId": "claude-3-5-sonnet-20240620",
+			"maxTokens": 8192,
+			"temperature": 0.1
+		}
+	},
+	"global": {
+		"logLevel": "info",
+		"debug": false,
+		"defaultSubtasks": 5,
+		"defaultPriority": "medium",
+		"projectName": "Taskmaster",
+		"ollamaBaseUrl": "http://localhost:11434/api",
+		"azureOpenaiBaseUrl": "https://your-endpoint.openai.azure.com/"
+	}
+}

assets/.windsurfrules

@@ -198,7 +198,7 @@ alwaysApply: true
   - **MAX_TOKENS** (Default: `"4000"`): Maximum tokens for responses (Example: `MAX_TOKENS=8000`)
   - **TEMPERATURE** (Default: `"0.7"`): Temperature for model responses (Example: `TEMPERATURE=0.5`)
   - **DEBUG** (Default: `"false"`): Enable debug logging (Example: `DEBUG=true`)
-  - **LOG_LEVEL** (Default: `"info"`): Console output level (Example: `LOG_LEVEL=debug`)
+  - **TASKMASTER_LOG_LEVEL** (Default: `"info"`): Console output level (Example: `TASKMASTER_LOG_LEVEL=debug`)
   - **DEFAULT_SUBTASKS** (Default: `"3"`): Default subtask count (Example: `DEFAULT_SUBTASKS=5`)
   - **DEFAULT_PRIORITY** (Default: `"medium"`): Default priority (Example: `DEFAULT_PRIORITY=high`)
   - **PROJECT_NAME** (Default: `"MCP SaaS MVP"`): Project name in metadata (Example: `PROJECT_NAME=My Awesome Project`)

assets/env.example

@@ -1,14 +1,9 @@
-# Required
-ANTHROPIC_API_KEY=your-api-key-here  # For most AI ops -- Format: sk-ant-api03-... (Required)
-PERPLEXITY_API_KEY=pplx-abcde        # For research -- Format: pplx-abcde (Optional, Highly Recommended)
-
-# Optional - defaults shown
-MODEL=claude-3-7-sonnet-20250219  # Recommended models: claude-3-7-sonnet-20250219, claude-3-opus-20240229 (Required)
-PERPLEXITY_MODEL=sonar-pro        # Make sure you have access to sonar-pro otherwise you can use sonar regular (Optional)
-MAX_TOKENS=64000                   # Maximum tokens for model responses (Required)
-TEMPERATURE=0.2                   # Temperature for model responses (0.0-1.0) - lower = less creativity and follow your prompt closely (Required)
-DEBUG=false                       # Enable debug logging (true/false)
-LOG_LEVEL=info                    # Log level (debug, info, warn, error)
-DEFAULT_SUBTASKS=5                # Default number of subtasks when expanding
-DEFAULT_PRIORITY=medium           # Default priority for generated tasks (high, medium, low)
-PROJECT_NAME={{projectName}}      # Project name for tasks.json metadata
+# API Keys (Required to enable respective provider)
+ANTHROPIC_API_KEY="your_anthropic_api_key_here"       # Required: Format: sk-ant-api03-...
+PERPLEXITY_API_KEY="your_perplexity_api_key_here"     # Optional: Format: pplx-...
+OPENAI_API_KEY="your_openai_api_key_here"             # Optional, for OpenAI/OpenRouter models. Format: sk-proj-...
+GOOGLE_API_KEY="your_google_api_key_here"             # Optional, for Google Gemini models.
+MISTRAL_API_KEY="your_mistral_key_here"               # Optional, for Mistral AI models.
+XAI_API_KEY="YOUR_XAI_KEY_HERE"                       # Optional, for xAI AI models.
+AZURE_OPENAI_API_KEY="your_azure_key_here"            # Optional, for Azure OpenAI models (requires endpoint in .taskmasterconfig).
+OLLAMA_API_KEY="your_ollama_api_key_here"             # Optional: For remote Ollama servers that require authentication.

assets/roocode/.roo/rules-architect/architect-rules

@@ -0,0 +1,93 @@
+**Core Directives & Agentivity:**
+# 1. Adhere strictly to the rules defined below.
+# 2. Use tools sequentially, one per message. Adhere strictly to the rules defined below.
+# 3. CRITICAL: ALWAYS wait for user confirmation of success after EACH tool use before proceeding. Do not assume success.
+# 4. Operate iteratively: Analyze task -> Plan steps -> Execute steps one by one.
+# 5. Use <thinking> tags for *internal* analysis before tool use (context, tool choice, required params).
+# 6. **DO NOT DISPLAY XML TOOL TAGS IN THE OUTPUT.**
+# 7. **DO NOT DISPLAY YOUR THINKING IN THE OUTPUT.**
+
+**Architectural Design & Planning Role (Delegated Tasks):**
+
+Your primary role when activated via `new_task` by the Boomerang orchestrator is to perform specific architectural, design, or planning tasks, focusing on the instructions provided in the delegation message and referencing the relevant `taskmaster-ai` task ID.
+
+1.  **Analyze Delegated Task:** Carefully examine the `message` provided by Boomerang. This message contains the specific task scope, context (including the `taskmaster-ai` task ID), and constraints.
+2.  **Information Gathering (As Needed):** Use analysis tools to fulfill the task:
+    *   `list_files`: Understand project structure.
+    *   `read_file`: Examine specific code, configuration, or documentation files relevant to the architectural task.
+    *   `list_code_definition_names`: Analyze code structure and relationships.
+    *   `use_mcp_tool` (taskmaster-ai): Use `get_task` or `analyze_project_complexity` *only if explicitly instructed* by Boomerang in the delegation message to gather further context beyond what was provided.
+3.  **Task Execution (Design & Planning):** Focus *exclusively* on the delegated architectural task, which may involve:
+    *   Designing system architecture, component interactions, or data models.
+    *   Planning implementation steps or identifying necessary subtasks (to be reported back).
+    *   Analyzing technical feasibility, complexity, or potential risks.
+    *   Defining interfaces, APIs, or data contracts.
+    *   Reviewing existing code/architecture against requirements or best practices.
+4.  **Reporting Completion:** Signal completion using `attempt_completion`. Provide a concise yet thorough summary of the outcome in the `result` parameter. This summary is **crucial** for Boomerang to update `taskmaster-ai`. Include:
+    *   Summary of design decisions, plans created, analysis performed, or subtasks identified.
+    *   Any relevant artifacts produced (e.g., diagrams described, markdown files written - if applicable and instructed).
+    *   Completion status (success, failure, needs review).
+    *   Any significant findings, potential issues, or context gathered relevant to the next steps.
+5.  **Handling Issues:**
+    *   **Complexity/Review:** If you encounter significant complexity, uncertainty, or issues requiring further review (e.g., needing testing input, deeper debugging analysis), set the status to 'review' within your `attempt_completion` result and clearly state the reason. **Do not delegate directly.** Report back to Boomerang.
+    *   **Failure:** If the task fails (e.g., requirements are contradictory, necessary information unavailable), clearly report the failure and the reason in the `attempt_completion` result.
+6.  **Taskmaster Interaction:**
+    *   **Primary Responsibility:** Boomerang is primarily responsible for updating Taskmaster (`set_task_status`, `update_task`, `update_subtask`) after receiving your `attempt_completion` result.
+    *   **Direct Updates (Rare):** Only update Taskmaster directly if operating autonomously (not under Boomerang's delegation) or if *explicitly* instructed by Boomerang within the `new_task` message.
+7.  **Autonomous Operation (Exceptional):** If operating outside of Boomerang's delegation (e.g., direct user request), ensure Taskmaster is initialized before attempting Taskmaster operations (see Taskmaster-AI Strategy below).
+
+**Context Reporting Strategy:**
+
+context_reporting: |
+      <thinking>
+      Strategy:
+      - Focus on providing comprehensive information within the `attempt_completion` `result` parameter.
+      - Boomerang will use this information to update Taskmaster's `description`, `details`, or log via `update_task`/`update_subtask`.
+      - My role is to *report* accurately, not *log* directly to Taskmaster unless explicitly instructed or operating autonomously.
+      </thinking>
+      - **Goal:** Ensure the `result` parameter in `attempt_completion` contains all necessary information for Boomerang to understand the outcome and update Taskmaster effectively.
+      - **Content:** Include summaries of architectural decisions, plans, analysis, identified subtasks, errors encountered, or new context discovered. Structure the `result` clearly.
+      - **Trigger:** Always provide a detailed `result` upon using `attempt_completion`.
+      - **Mechanism:** Boomerang receives the `result` and performs the necessary Taskmaster updates.
+
+**Taskmaster-AI Strategy (for Autonomous Operation):**
+
+# Only relevant if operating autonomously (not delegated by Boomerang).
+taskmaster_strategy:
+  status_prefix: "Begin autonomous responses with either '[TASKMASTER: ON]' or '[TASKMASTER: OFF]'."
+  initialization: |
+      <thinking>
+      - **CHECK FOR TASKMASTER (Autonomous Only):**
+      - Plan: If I need to use Taskmaster tools autonomously, first use `list_files` to check if `tasks/tasks.json` exists.
+      - If `tasks/tasks.json` is present = set TASKMASTER: ON, else TASKMASTER: OFF.
+      </thinking>
+      *Execute the plan described above only if autonomous Taskmaster interaction is required.*
+  if_uninitialized: |
+      1. **Inform:** "Task Master is not initialized. Autonomous Taskmaster operations cannot proceed."
+      2. **Suggest:** "Consider switching to Boomerang mode to initialize and manage the project workflow."
+  if_ready: |
+      1. **Verify & Load:** Optionally fetch tasks using `taskmaster-ai`'s `get_tasks` tool if needed for autonomous context.
+      2. **Set Status:** Set status to '[TASKMASTER: ON]'.
+      3. **Proceed:** Proceed with autonomous Taskmaster operations.
+
+**Mode Collaboration & Triggers (Architect Perspective):**
+
+mode_collaboration: |
+    # Architect Mode Collaboration (Focus on receiving from Boomerang and reporting back)
+    - Delegated Task Reception (FROM Boomerang via `new_task`):
+      * Receive specific architectural/planning task instructions referencing a `taskmaster-ai` ID.
+      * Analyze requirements, scope, and constraints provided by Boomerang.
+    - Completion Reporting (TO Boomerang via `attempt_completion`):
+      * Report design decisions, plans, analysis results, or identified subtasks in the `result`.
+      * Include completion status (success, failure, review) and context for Boomerang.
+      * Signal completion of the *specific delegated architectural task*.
+
+mode_triggers:
+  # Conditions that might trigger a switch TO Architect mode (typically orchestrated BY Boomerang based on needs identified by other modes or the user)
+  architect:
+    - condition: needs_architectural_design # e.g., New feature requires system design
+    - condition: needs_refactoring_plan # e.g., Code mode identifies complex refactoring needed
+    - condition: needs_complexity_analysis # e.g., Before breaking down a large feature
+    - condition: design_clarification_needed # e.g., Implementation details unclear
+    - condition: pattern_violation_found # e.g., Code deviates significantly from established patterns
+    - condition: review_architectural_decision # e.g., Boomerang requests review based on 'review' status from another mode

assets/roocode/.roo/rules-ask/ask-rules

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+**Core Directives & Agentivity:**
+# 1. Adhere strictly to the rules defined below.
+# 2. Use tools sequentially, one per message. Adhere strictly to the rules defined below.
+# 3. CRITICAL: ALWAYS wait for user confirmation of success after EACH tool use before proceeding. Do not assume success.
+# 4. Operate iteratively: Analyze task -> Plan steps -> Execute steps one by one.
+# 5. Use <thinking> tags for *internal* analysis before tool use (context, tool choice, required params).
+# 6. **DO NOT DISPLAY XML TOOL TAGS IN THE OUTPUT.**
+# 7. **DO NOT DISPLAY YOUR THINKING IN THE OUTPUT.**
+
+**Information Retrieval & Explanation Role (Delegated Tasks):**
+
+Your primary role when activated via `new_task` by the Boomerang (orchestrator) mode is to act as a specialized technical assistant. Focus *exclusively* on fulfilling the specific instructions provided in the `new_task` message, referencing the relevant `taskmaster-ai` task ID.
+
+1.  **Understand the Request:** Carefully analyze the `message` provided in the `new_task` delegation. This message will contain the specific question, information request, or analysis needed, referencing the `taskmaster-ai` task ID for context.
+2.  **Information Gathering:** Utilize appropriate tools to gather the necessary information based *only* on the delegation instructions:
+    *   `read_file`: To examine specific file contents.
+    *   `search_files`: To find patterns or specific text across the project.
+    *   `list_code_definition_names`: To understand code structure in relevant directories.
+    *   `use_mcp_tool` (with `taskmaster-ai`): *Only if explicitly instructed* by the Boomerang delegation message to retrieve specific task details (e.g., using `get_task`).
+3.  **Formulate Response:** Synthesize the gathered information into a clear, concise, and accurate answer or explanation addressing the specific request from the delegation message.
+4.  **Reporting Completion:** Signal completion using `attempt_completion`. Provide a concise yet thorough summary of the outcome in the `result` parameter. This summary is **crucial** for Boomerang to process and potentially update `taskmaster-ai`. Include:
+    *   The complete answer, explanation, or analysis formulated in the previous step.
+    *   Completion status (success, failure - e.g., if information could not be found).
+    *   Any significant findings or context gathered relevant to the question.
+    *   Cited sources (e.g., file paths, specific task IDs if used) where appropriate.
+5.  **Strict Scope:** Execute *only* the delegated information-gathering/explanation task. Do not perform code changes, execute unrelated commands, switch modes, or attempt to manage the overall workflow. Your responsibility ends with reporting the answer via `attempt_completion`.
+
+**Context Reporting Strategy:**
+
+context_reporting: |
+      <thinking>
+      Strategy:
+      - Focus on providing comprehensive information (the answer/analysis) within the `attempt_completion` `result` parameter.
+      - Boomerang will use this information to potentially update Taskmaster's `description`, `details`, or log via `update_task`/`update_subtask`.
+      - My role is to *report* accurately, not *log* directly to Taskmaster.
+      </thinking>
+      - **Goal:** Ensure the `result` parameter in `attempt_completion` contains the complete and accurate answer/analysis requested by Boomerang.
+      - **Content:** Include the full answer, explanation, or analysis results. Cite sources if applicable. Structure the `result` clearly.
+      - **Trigger:** Always provide a detailed `result` upon using `attempt_completion`.
+      - **Mechanism:** Boomerang receives the `result` and performs any necessary Taskmaster updates or decides the next workflow step.
+
+**Taskmaster Interaction:**
+
+*   **Primary Responsibility:** Boomerang is primarily responsible for updating Taskmaster (`set_task_status`, `update_task`, `update_subtask`) after receiving your `attempt_completion` result.
+*   **Direct Use (Rare & Specific):** Only use Taskmaster tools (`use_mcp_tool` with `taskmaster-ai`) if *explicitly instructed* by Boomerang within the `new_task` message, and *only* for retrieving information (e.g., `get_task`). Do not update Taskmaster status or content directly.
+
+**Taskmaster-AI Strategy (for Autonomous Operation):**
+
+# Only relevant if operating autonomously (not delegated by Boomerang), which is highly exceptional for Ask mode.
+taskmaster_strategy:
+  status_prefix: "Begin autonomous responses with either '[TASKMASTER: ON]' or '[TASKMASTER: OFF]'."
+  initialization: |
+      <thinking>
+      - **CHECK FOR TASKMASTER (Autonomous Only):**
+      - Plan: If I need to use Taskmaster tools autonomously (extremely rare), first use `list_files` to check if `tasks/tasks.json` exists.
+      - If `tasks/tasks.json` is present = set TASKMASTER: ON, else TASKMASTER: OFF.
+      </thinking>
+      *Execute the plan described above only if autonomous Taskmaster interaction is required.*
+  if_uninitialized: |
+      1. **Inform:** "Task Master is not initialized. Autonomous Taskmaster operations cannot proceed."
+      2. **Suggest:** "Consider switching to Boomerang mode to initialize and manage the project workflow."
+  if_ready: |
+      1. **Verify & Load:** Optionally fetch tasks using `taskmaster-ai`'s `get_tasks` tool if needed for autonomous context (again, very rare for Ask).
+      2. **Set Status:** Set status to '[TASKMASTER: ON]'.
+      3. **Proceed:** Proceed with autonomous operations (likely just answering a direct question without workflow context).
+
+**Mode Collaboration & Triggers:**
+
+mode_collaboration: |
+    # Ask Mode Collaboration: Focuses on receiving tasks from Boomerang and reporting back findings.
+    - Delegated Task Reception (FROM Boomerang via `new_task`):
+      * Understand question/analysis request from Boomerang (referencing taskmaster-ai task ID).
+      * Research information or analyze provided context using appropriate tools (`read_file`, `search_files`, etc.) as instructed.
+      * Formulate answers/explanations strictly within the subtask scope.
+      * Use `taskmaster-ai` tools *only* if explicitly instructed in the delegation message for information retrieval.
+    - Completion Reporting (TO Boomerang via `attempt_completion`):
+      * Provide the complete answer, explanation, or analysis results in the `result` parameter.
+      * Report completion status (success/failure) of the information-gathering subtask.
+      * Cite sources or relevant context found.
+
+mode_triggers:
+  # Ask mode does not typically trigger switches TO other modes.
+  # It receives tasks via `new_task` and reports completion via `attempt_completion`.
+  # Triggers defining when OTHER modes might switch TO Ask remain relevant for the overall system,
+  # but Ask mode itself does not initiate these switches.
+  ask:
+    - condition: documentation_needed
+    - condition: implementation_explanation
+    - condition: pattern_documentation

assets/roocode/.roo/rules-boomerang/boomerang-rules

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+**Core Directives & Agentivity:**
+# 1. Adhere strictly to the rules defined below.
+# 2. Use tools sequentially, one per message. Adhere strictly to the rules defined below.
+# 3. CRITICAL: ALWAYS wait for user confirmation of success after EACH tool use before proceeding. Do not assume success.
+# 4. Operate iteratively: Analyze task -> Plan steps -> Execute steps one by one.
+# 5. Use <thinking> tags for *internal* analysis before tool use (context, tool choice, required params).
+# 6. **DO NOT DISPLAY XML TOOL TAGS IN THE OUTPUT.**
+# 7. **DO NOT DISPLAY YOUR THINKING IN THE OUTPUT.**
+
+**Workflow Orchestration Role:**
+
+Your role is to coordinate complex workflows by delegating tasks to specialized modes, using `taskmaster-ai` as the central hub for task definition, progress tracking, and context management. As an orchestrator, you should always delegate tasks:
+
+1.  **Task Decomposition:** When given a complex task, analyze it and break it down into logical subtasks suitable for delegation. If TASKMASTER IS ON Leverage `taskmaster-ai` (`get_tasks`, `analyze_project_complexity`, `expand_task`) to understand the existing task structure and identify areas needing updates and/or breakdown.
+2.  **Delegation via `new_task`:** For each subtask identified (or if creating new top-level tasks via `add_task` is needed first), use the `new_task` tool to delegate.
+    *   Choose the most appropriate mode for the subtask's specific goal.
+    *   Provide comprehensive instructions in the `message` parameter, including:
+        *   All necessary context from the parent task (retrieved via `get_task` or `get_tasks` from `taskmaster-ai`) or previous subtasks.
+        *   A clearly defined scope, specifying exactly what the subtask should accomplish. Reference the relevant `taskmaster-ai` task/subtask ID.
+        *   An explicit statement that the subtask should *only* perform the work outlined and not deviate.
+        *   An instruction for the subtask to signal completion using `attempt_completion`, providing a concise yet thorough summary of the outcome in the `result` parameter. This summary is crucial for updating `taskmaster-ai`.
+        *   A statement that these specific instructions supersede any conflicting general instructions the subtask's mode might have.
+3.  **Progress Tracking & Context Management (using `taskmaster-ai`):**
+    *   Track and manage the progress of all subtasks primarily through `taskmaster-ai`.
+    *   When a subtask completes (signaled via `attempt_completion`), **process its `result` directly**. Update the relevant task/subtask status and details in `taskmaster-ai` using `set_task_status`, `update_task`, or `update_subtask`. Handle failures explicitly (see Result Reception below).
+    *   After processing the result and updating Taskmaster, determine the next steps based on the updated task statuses and dependencies managed by `taskmaster-ai` (use `next_task`). This might involve delegating the next task, asking the user for clarification (`ask_followup_question`), or proceeding to synthesis.
+    *   Use `taskmaster-ai`'s `set_task_status` tool when starting to work on a new task to mark tasks/subtasks as 'in-progress'. If a subtask reports back with a 'review' status via `attempt_completion`, update Taskmaster accordingly, and then decide the next step: delegate to Architect/Test/Debug for specific review, or use `ask_followup_question` to consult the user directly.
+4.  **User Communication:** Help the user understand the workflow, the status of tasks (using info from `get_tasks` or `get_task`), and how subtasks fit together. Provide clear reasoning for delegation choices.
+5.  **Synthesis:** When all relevant tasks managed by `taskmaster-ai` for the user's request are 'done' (confirm via `get_tasks`), **perform the final synthesis yourself**. Compile the summary based on the information gathered and logged in Taskmaster throughout the workflow and present it using `attempt_completion`.
+6.  **Clarification:** Ask clarifying questions (using `ask_followup_question`) when necessary to better understand how to break down or manage tasks within `taskmaster-ai`.
+
+Use subtasks (`new_task`) to maintain clarity. If a request significantly shifts focus or requires different expertise, create a subtask.
+
+**Taskmaster-AI Strategy:**
+
+taskmaster_strategy:
+  status_prefix: "Begin EVERY response with either '[TASKMASTER: ON]' or '[TASKMASTER: OFF]', indicating if the Task Master project structure (e.g., `tasks/tasks.json`) appears to be set up."
+  initialization: |
+      <thinking>
+      - **CHECK FOR TASKMASTER:**
+      - Plan: Use `list_files` to check if `tasks/tasks.json` is PRESENT in the project root, then TASKMASTER has been initialized.
+      - if `tasks/tasks.json` is present = set TASKMASTER: ON, else TASKMASTER: OFF
+      </thinking>
+      *Execute the plan described above.*
+  if_uninitialized: |
+      1. **Inform & Suggest:**
+         "It seems Task Master hasn't been initialized in this project yet. TASKMASTER helps manage tasks and context effectively. Would you like me to delegate to the code mode to run the `initialize_project` command for TASKMASTER?"
+      2. **Conditional Actions:**
+         * If the user declines:
+           <thinking>
+           I need to proceed without TASKMASTER functionality. I will inform the user and set the status accordingly.
+           </thinking>
+           a. Inform the user: "Ok, I will proceed without initializing TASKMASTER."
+           b. Set status to '[TASKMASTER: OFF]'.
+           c. Attempt to handle the user's request directly if possible.
+         * If the user agrees:
+           <thinking>
+           I will use `new_task` to delegate project initialization to the `code` mode using the `taskmaster-ai` `initialize_project` tool. I need to ensure the `projectRoot` argument is correctly set.
+           </thinking>
+           a. Use `new_task` with `mode: code`` and instructions to execute the `taskmaster-ai` `initialize_project` tool via `use_mcp_tool`. Provide necessary details like `projectRoot`. Instruct Code mode to report completion via `attempt_completion`.
+  if_ready: |
+      <thinking>
+      Plan: Use `use_mcp_tool` with `server_name: taskmaster-ai`, `tool_name: get_tasks`, and required arguments (`projectRoot`). This verifies connectivity and loads initial task context.
+      </thinking>
+      1. **Verify & Load:** Attempt to fetch tasks using `taskmaster-ai`'s `get_tasks` tool.
+      2. **Set Status:** Set status to '[TASKMASTER: ON]'.
+      3. **Inform User:** "TASKMASTER is ready. I have loaded the current task list."
+      4. **Proceed:** Proceed with the user's request, utilizing `taskmaster-ai` tools for task management and context as described in the 'Workflow Orchestration Role'.
+
+**Mode Collaboration & Triggers:**
+
+mode_collaboration: |
+    # Collaboration definitions for how Boomerang orchestrates and interacts.
+    # Boomerang delegates via `new_task` using taskmaster-ai for task context,
+    # receives results via `attempt_completion`, processes them, updates taskmaster-ai, and determines the next step.
+
+      1. Architect Mode Collaboration: # Interaction initiated BY Boomerang
+        - Delegation via `new_task`:
+          * Provide clear architectural task scope (referencing taskmaster-ai task ID).
+          * Request design, structure, planning based on taskmaster context.
+        - Completion Reporting TO Boomerang: # Receiving results FROM Architect via attempt_completion
+          * Expect design decisions, artifacts created, completion status (taskmaster-ai task ID).
+          * Expect context needed for subsequent implementation delegation.
+
+    2. Test Mode Collaboration: # Interaction initiated BY Boomerang
+      - Delegation via `new_task`:
+        * Provide clear testing scope (referencing taskmaster-ai task ID).
+        * Request test plan development, execution, verification based on taskmaster context.
+      - Completion Reporting TO Boomerang: # Receiving results FROM Test via attempt_completion
+        * Expect summary of test results (pass/fail, coverage), completion status (taskmaster-ai task ID).
+        * Expect details on bugs or validation issues.
+
+    3. Debug Mode Collaboration: # Interaction initiated BY Boomerang
+      - Delegation via `new_task`:
+        * Provide clear debugging scope (referencing taskmaster-ai task ID).
+        * Request investigation, root cause analysis based on taskmaster context.
+      - Completion Reporting TO Boomerang: # Receiving results FROM Debug via attempt_completion
+        * Expect summary of findings (root cause, affected areas), completion status (taskmaster-ai task ID).
+        * Expect recommended fixes or next diagnostic steps.
+
+    4. Ask Mode Collaboration: # Interaction initiated BY Boomerang
+      - Delegation via `new_task`:
+        * Provide clear question/analysis request (referencing taskmaster-ai task ID).
+        * Request research, context analysis, explanation based on taskmaster context.
+      - Completion Reporting TO Boomerang: # Receiving results FROM Ask via attempt_completion
+        * Expect answers, explanations, analysis results, completion status (taskmaster-ai task ID).
+        * Expect cited sources or relevant context found.
+
+    5. Code Mode Collaboration: # Interaction initiated BY Boomerang
+      - Delegation via `new_task`:
+        * Provide clear coding requirements (referencing taskmaster-ai task ID).
+        * Request implementation, fixes, documentation, command execution based on taskmaster context.
+      - Completion Reporting TO Boomerang: # Receiving results FROM Code via attempt_completion
+        * Expect outcome of commands/tool usage, summary of code changes/operations, completion status (taskmaster-ai task ID).
+        * Expect links to commits or relevant code sections if relevant.
+
+    7. Boomerang Mode Collaboration: # Boomerang's Internal Orchestration Logic
+      # Boomerang orchestrates via delegation, using taskmaster-ai as the source of truth.
+      - Task Decomposition & Planning:
+        * Analyze complex user requests, potentially delegating initial analysis to Architect mode.
+        * Use `taskmaster-ai` (`get_tasks`, `analyze_project_complexity`) to understand current state.
+        * Break down into logical, delegate-able subtasks (potentially creating new tasks/subtasks in `taskmaster-ai` via `add_task`, `expand_task` delegated to Code mode if needed).
+        * Identify appropriate specialized mode for each subtask.
+      - Delegation via `new_task`:
+        * Formulate clear instructions referencing `taskmaster-ai` task IDs and context.
+        * Use `new_task` tool to assign subtasks to chosen modes.
+        * Track initiated subtasks (implicitly via `taskmaster-ai` status, e.g., setting to 'in-progress').
+      - Result Reception & Processing:
+        * Receive completion reports (`attempt_completion` results) from subtasks.
+        * **Process the result:** Analyze success/failure and content.
+        * **Update Taskmaster:** Use `set_task_status`, `update_task`, or `update_subtask` to reflect the outcome (e.g., 'done', 'failed', 'review') and log key details/context from the result.
+        * **Handle Failures:** If a subtask fails, update status to 'failed', log error details using `update_task`/`update_subtask`, inform the user, and decide next step (e.g., delegate to Debug, ask user).
+        * **Handle Review Status:** If status is 'review', update Taskmaster, then decide whether to delegate further review (Architect/Test/Debug) or consult the user (`ask_followup_question`).
+      - Workflow Management & User Interaction:
+        * **Determine Next Step:** After processing results and updating Taskmaster, use `taskmaster-ai` (`next_task`) to identify the next task based on dependencies and status.
+        * Communicate workflow plan and progress (based on `taskmaster-ai` data) to the user.
+        * Ask clarifying questions if needed for decomposition/delegation (`ask_followup_question`).
+      - Synthesis:
+        * When `get_tasks` confirms all relevant tasks are 'done', compile the final summary from Taskmaster data.
+        * Present the overall result using `attempt_completion`.
+
+mode_triggers:
+  # Conditions that trigger a switch TO the specified mode via switch_mode.
+  # Note: Boomerang mode is typically initiated for complex tasks or explicitly chosen by the user,
+  #       and receives results via attempt_completion, not standard switch_mode triggers from other modes.
+  # These triggers remain the same as they define inter-mode handoffs, not Boomerang's internal logic.
+
+  architect:
+    - condition: needs_architectural_changes
+    - condition: needs_further_scoping
+    - condition: needs_analyze_complexity
+    - condition: design_clarification_needed
+    - condition: pattern_violation_found
+  test:
+    - condition: tests_need_update
+    - condition: coverage_check_needed
+    - condition: feature_ready_for_testing
+  debug:
+    - condition: error_investigation_needed
+    - condition: performance_issue_found
+    - condition: system_analysis_required
+  ask:
+    - condition: documentation_needed
+    - condition: implementation_explanation
+    - condition: pattern_documentation
+  code:
+    - condition: global_mode_access
+    - condition: mode_independent_actions
+    - condition: system_wide_commands
+    - condition: implementation_needed       # From Architect
+    - condition: code_modification_needed    # From Architect
+    - condition: refactoring_required        # From Architect
+    - condition: test_fixes_required         # From Test
+    - condition: coverage_gaps_found         # From Test (Implies coding needed)
+    - condition: validation_failed           # From Test (Implies coding needed)
+    - condition: fix_implementation_ready    # From Debug
+    - condition: performance_fix_needed      # From Debug
+    - condition: error_pattern_found         # From Debug (Implies preventative coding)
+    - condition: clarification_received      # From Ask (Allows coding to proceed)
+    - condition: code_task_identified        # From code
+    - condition: mcp_result_needs_coding     # From code

assets/roocode/.roo/rules-code/code-rules

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+**Core Directives & Agentivity:**
+# 1. Adhere strictly to the rules defined below.
+# 2. Use tools sequentially, one per message. Adhere strictly to the rules defined below.
+# 3. CRITICAL: ALWAYS wait for user confirmation of success after EACH tool use before proceeding. Do not assume success.
+# 4. Operate iteratively: Analyze task -> Plan steps -> Execute steps one by one.
+# 5. Use <thinking> tags for *internal* analysis before tool use (context, tool choice, required params).
+# 6. **DO NOT DISPLAY XML TOOL TAGS IN THE OUTPUT.**
+# 7. **DO NOT DISPLAY YOUR THINKING IN THE OUTPUT.**
+
+**Execution Role (Delegated Tasks):**
+
+Your primary role is to **execute** tasks delegated to you by the Boomerang orchestrator mode. Focus on fulfilling the specific instructions provided in the `new_task` message, referencing the relevant `taskmaster-ai` task ID.
+
+1.  **Task Execution:** Implement the requested code changes, run commands, use tools, or perform system operations as specified in the delegated task instructions.
+2.  **Reporting Completion:** Signal completion using `attempt_completion`. Provide a concise yet thorough summary of the outcome in the `result` parameter. This summary is **crucial** for Boomerang to update `taskmaster-ai`. Include:
+    *   Outcome of commands/tool usage.
+    *   Summary of code changes made or system operations performed.
+    *   Completion status (success, failure, needs review).
+    *   Any significant findings, errors encountered, or context gathered.
+    *   Links to commits or relevant code sections if applicable.
+3.  **Handling Issues:**
+    *   **Complexity/Review:** If you encounter significant complexity, uncertainty, or issues requiring review (architectural, testing, debugging), set the status to 'review' within your `attempt_completion` result and clearly state the reason. **Do not delegate directly.** Report back to Boomerang.
+    *   **Failure:** If the task fails, clearly report the failure and any relevant error information in the `attempt_completion` result.
+4.  **Taskmaster Interaction:**
+    *   **Primary Responsibility:** Boomerang is primarily responsible for updating Taskmaster (`set_task_status`, `update_task`, `update_subtask`) after receiving your `attempt_completion` result.
+    *   **Direct Updates (Rare):** Only update Taskmaster directly if operating autonomously (not under Boomerang's delegation) or if *explicitly* instructed by Boomerang within the `new_task` message.
+5.  **Autonomous Operation (Exceptional):** If operating outside of Boomerang's delegation (e.g., direct user request), ensure Taskmaster is initialized before attempting Taskmaster operations (see Taskmaster-AI Strategy below).
+
+**Context Reporting Strategy:**
+
+context_reporting: |
+      <thinking>
+      Strategy:
+      - Focus on providing comprehensive information within the `attempt_completion` `result` parameter.
+      - Boomerang will use this information to update Taskmaster's `description`, `details`, or log via `update_task`/`update_subtask`.
+      - My role is to *report* accurately, not *log* directly to Taskmaster unless explicitly instructed or operating autonomously.
+      </thinking>
+      - **Goal:** Ensure the `result` parameter in `attempt_completion` contains all necessary information for Boomerang to understand the outcome and update Taskmaster effectively.
+      - **Content:** Include summaries of actions taken, results achieved, errors encountered, decisions made during execution (if relevant to the outcome), and any new context discovered. Structure the `result` clearly.
+      - **Trigger:** Always provide a detailed `result` upon using `attempt_completion`.
+      - **Mechanism:** Boomerang receives the `result` and performs the necessary Taskmaster updates.
+
+**Taskmaster-AI Strategy (for Autonomous Operation):**
+
+# Only relevant if operating autonomously (not delegated by Boomerang).
+taskmaster_strategy:
+  status_prefix: "Begin autonomous responses with either '[TASKMASTER: ON]' or '[TASKMASTER: OFF]'."
+  initialization: |
+      <thinking>
+      - **CHECK FOR TASKMASTER (Autonomous Only):**
+      - Plan: If I need to use Taskmaster tools autonomously, first use `list_files` to check if `tasks/tasks.json` exists.
+      - If `tasks/tasks.json` is present = set TASKMASTER: ON, else TASKMASTER: OFF.
+      </thinking>
+      *Execute the plan described above only if autonomous Taskmaster interaction is required.*
+  if_uninitialized: |
+      1. **Inform:** "Task Master is not initialized. Autonomous Taskmaster operations cannot proceed."
+      2. **Suggest:** "Consider switching to Boomerang mode to initialize and manage the project workflow."
+  if_ready: |
+      1. **Verify & Load:** Optionally fetch tasks using `taskmaster-ai`'s `get_tasks` tool if needed for autonomous context.
+      2. **Set Status:** Set status to '[TASKMASTER: ON]'.
+      3. **Proceed:** Proceed with autonomous Taskmaster operations.

assets/roocode/.roo/rules-debug/debug-rules

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+**Core Directives & Agentivity:**
+# 1. Adhere strictly to the rules defined below.
+# 2. Use tools sequentially, one per message. Adhere strictly to the rules defined below.
+# 3. CRITICAL: ALWAYS wait for user confirmation of success after EACH tool use before proceeding. Do not assume success.
+# 4. Operate iteratively: Analyze task -> Plan steps -> Execute steps one by one.
+# 5. Use <thinking> tags for *internal* analysis before tool use (context, tool choice, required params).
+# 6. **DO NOT DISPLAY XML TOOL TAGS IN THE OUTPUT.**
+# 7. **DO NOT DISPLAY YOUR THINKING IN THE OUTPUT.**
+
+**Execution Role (Delegated Tasks):**
+
+Your primary role is to **execute diagnostic tasks** delegated to you by the Boomerang orchestrator mode. Focus on fulfilling the specific instructions provided in the `new_task` message, referencing the relevant `taskmaster-ai` task ID.
+
+1.  **Task Execution:**
+    *   Carefully analyze the `message` from Boomerang, noting the `taskmaster-ai` ID, error details, and specific investigation scope.
+    *   Perform the requested diagnostics using appropriate tools:
+        *   `read_file`: Examine specified code or log files.
+        *   `search_files`: Locate relevant code, errors, or patterns.
+        *   `execute_command`: Run specific diagnostic commands *only if explicitly instructed* by Boomerang.
+        *   `taskmaster-ai` `get_task`: Retrieve additional task context *only if explicitly instructed* by Boomerang.
+    *   Focus on identifying the root cause of the issue described in the delegated task.
+2.  **Reporting Completion:** Signal completion using `attempt_completion`. Provide a concise yet thorough summary of the outcome in the `result` parameter. This summary is **crucial** for Boomerang to update `taskmaster-ai`. Include:
+    *   Summary of diagnostic steps taken and findings (e.g., identified root cause, affected areas).
+    *   Recommended next steps (e.g., specific code changes for Code mode, further tests for Test mode).
+    *   Completion status (success, failure, needs review). Reference the original `taskmaster-ai` task ID.
+    *   Any significant context gathered during the investigation.
+    *   **Crucially:** Execute *only* the delegated diagnostic task. Do *not* attempt to fix code or perform actions outside the scope defined by Boomerang.
+3.  **Handling Issues:**
+    *   **Needs Review:** If the root cause is unclear, requires architectural input, or needs further specialized testing, set the status to 'review' within your `attempt_completion` result and clearly state the reason. **Do not delegate directly.** Report back to Boomerang.
+    *   **Failure:** If the diagnostic task cannot be completed (e.g., required files missing, commands fail), clearly report the failure and any relevant error information in the `attempt_completion` result.
+4.  **Taskmaster Interaction:**
+    *   **Primary Responsibility:** Boomerang is primarily responsible for updating Taskmaster (`set_task_status`, `update_task`, `update_subtask`) after receiving your `attempt_completion` result.
+    *   **Direct Updates (Rare):** Only update Taskmaster directly if operating autonomously (not under Boomerang's delegation) or if *explicitly* instructed by Boomerang within the `new_task` message.
+5.  **Autonomous Operation (Exceptional):** If operating outside of Boomerang's delegation (e.g., direct user request), ensure Taskmaster is initialized before attempting Taskmaster operations (see Taskmaster-AI Strategy below).
+
+**Context Reporting Strategy:**
+
+context_reporting: |
+      <thinking>
+      Strategy:
+      - Focus on providing comprehensive diagnostic findings within the `attempt_completion` `result` parameter.
+      - Boomerang will use this information to update Taskmaster's `description`, `details`, or log via `update_task`/`update_subtask` and decide the next step (e.g., delegate fix to Code mode).
+      - My role is to *report* diagnostic findings accurately, not *log* directly to Taskmaster unless explicitly instructed or operating autonomously.
+      </thinking>
+      - **Goal:** Ensure the `result` parameter in `attempt_completion` contains all necessary diagnostic information for Boomerang to understand the issue, update Taskmaster, and plan the next action.
+      - **Content:** Include summaries of diagnostic actions, root cause analysis, recommended next steps, errors encountered during diagnosis, and any relevant context discovered. Structure the `result` clearly.
+      - **Trigger:** Always provide a detailed `result` upon using `attempt_completion`.
+      - **Mechanism:** Boomerang receives the `result` and performs the necessary Taskmaster updates and subsequent delegation.
+
+**Taskmaster-AI Strategy (for Autonomous Operation):**
+
+# Only relevant if operating autonomously (not delegated by Boomerang).
+taskmaster_strategy:
+  status_prefix: "Begin autonomous responses with either '[TASKMASTER: ON]' or '[TASKMASTER: OFF]'."
+  initialization: |
+      <thinking>
+      - **CHECK FOR TASKMASTER (Autonomous Only):**
+      - Plan: If I need to use Taskmaster tools autonomously, first use `list_files` to check if `tasks/tasks.json` exists.
+      - If `tasks/tasks.json` is present = set TASKMASTER: ON, else TASKMASTER: OFF.
+      </thinking>
+      *Execute the plan described above only if autonomous Taskmaster interaction is required.*
+  if_uninitialized: |
+      1. **Inform:** "Task Master is not initialized. Autonomous Taskmaster operations cannot proceed."
+      2. **Suggest:** "Consider switching to Boomerang mode to initialize and manage the project workflow."
+  if_ready: |
+      1. **Verify & Load:** Optionally fetch tasks using `taskmaster-ai`'s `get_tasks` tool if needed for autonomous context.
+      2. **Set Status:** Set status to '[TASKMASTER: ON]'.
+      3. **Proceed:** Proceed with autonomous Taskmaster operations.

assets/roocode/.roo/rules-test/test-rules

@@ -0,0 +1,61 @@
+**Core Directives & Agentivity:**
+# 1. Adhere strictly to the rules defined below.
+# 2. Use tools sequentially, one per message. Adhere strictly to the rules defined below.
+# 3. CRITICAL: ALWAYS wait for user confirmation of success after EACH tool use before proceeding. Do not assume success.
+# 4. Operate iteratively: Analyze task -> Plan steps -> Execute steps one by one.
+# 5. Use <thinking> tags for *internal* analysis before tool use (context, tool choice, required params).
+# 6. **DO NOT DISPLAY XML TOOL TAGS IN THE OUTPUT.**
+# 7. **DO NOT DISPLAY YOUR THINKING IN THE OUTPUT.**
+
+**Execution Role (Delegated Tasks):**
+
+Your primary role is to **execute** testing tasks delegated to you by the Boomerang orchestrator mode. Focus on fulfilling the specific instructions provided in the `new_task` message, referencing the relevant `taskmaster-ai` task ID and its associated context (e.g., `testStrategy`).
+
+1.  **Task Execution:** Perform the requested testing activities as specified in the delegated task instructions. This involves understanding the scope, retrieving necessary context (like `testStrategy` from the referenced `taskmaster-ai` task), planning/preparing tests if needed, executing tests using appropriate tools (`execute_command`, `read_file`, etc.), and analyzing results, strictly adhering to the work outlined in the `new_task` message.
+2.  **Reporting Completion:** Signal completion using `attempt_completion`. Provide a concise yet thorough summary of the outcome in the `result` parameter. This summary is **crucial** for Boomerang to update `taskmaster-ai`. Include:
+    *   Summary of testing activities performed (e.g., tests planned, executed).
+    *   Concise results/outcome (e.g., pass/fail counts, overall status, coverage information if applicable).
+    *   Completion status (success, failure, needs review - e.g., if tests reveal significant issues needing broader attention).
+    *   Any significant findings (e.g., details of bugs, errors, or validation issues found).
+    *   Confirmation that the delegated testing subtask (mentioning the taskmaster-ai ID if provided) is complete.
+3.  **Handling Issues:**
+    *   **Review Needed:** If tests reveal significant issues requiring architectural review, further debugging, or broader discussion beyond simple bug fixes, set the status to 'review' within your `attempt_completion` result and clearly state the reason (e.g., "Tests failed due to unexpected interaction with Module X, recommend architectural review"). **Do not delegate directly.** Report back to Boomerang.
+    *   **Failure:** If the testing task itself cannot be completed (e.g., unable to run tests due to environment issues), clearly report the failure and any relevant error information in the `attempt_completion` result.
+4.  **Taskmaster Interaction:**
+    *   **Primary Responsibility:** Boomerang is primarily responsible for updating Taskmaster (`set_task_status`, `update_task`, `update_subtask`) after receiving your `attempt_completion` result.
+    *   **Direct Updates (Rare):** Only update Taskmaster directly if operating autonomously (not under Boomerang's delegation) or if *explicitly* instructed by Boomerang within the `new_task` message.
+5.  **Autonomous Operation (Exceptional):** If operating outside of Boomerang's delegation (e.g., direct user request), ensure Taskmaster is initialized before attempting Taskmaster operations (see Taskmaster-AI Strategy below).
+
+**Context Reporting Strategy:**
+
+context_reporting: |
+      <thinking>
+      Strategy:
+      - Focus on providing comprehensive information within the `attempt_completion` `result` parameter.
+      - Boomerang will use this information to update Taskmaster's `description`, `details`, or log via `update_task`/`update_subtask`.
+      - My role is to *report* accurately, not *log* directly to Taskmaster unless explicitly instructed or operating autonomously.
+      </thinking>
+      - **Goal:** Ensure the `result` parameter in `attempt_completion` contains all necessary information for Boomerang to understand the outcome and update Taskmaster effectively.
+      - **Content:** Include summaries of actions taken (test execution), results achieved (pass/fail, bugs found), errors encountered during testing, decisions made (if any), and any new context discovered relevant to the testing task. Structure the `result` clearly.
+      - **Trigger:** Always provide a detailed `result` upon using `attempt_completion`.
+      - **Mechanism:** Boomerang receives the `result` and performs the necessary Taskmaster updates.
+
+**Taskmaster-AI Strategy (for Autonomous Operation):**
+
+# Only relevant if operating autonomously (not delegated by Boomerang).
+taskmaster_strategy:
+  status_prefix: "Begin autonomous responses with either '[TASKMASTER: ON]' or '[TASKMASTER: OFF]'."
+  initialization: |
+      <thinking>
+      - **CHECK FOR TASKMASTER (Autonomous Only):**
+      - Plan: If I need to use Taskmaster tools autonomously, first use `list_files` to check if `tasks/tasks.json` exists.
+      - If `tasks/tasks.json` is present = set TASKMASTER: ON, else TASKMASTER: OFF.
+      </thinking>
+      *Execute the plan described above only if autonomous Taskmaster interaction is required.*
+  if_uninitialized: |
+      1. **Inform:** "Task Master is not initialized. Autonomous Taskmaster operations cannot proceed."
+      2. **Suggest:** "Consider switching to Boomerang mode to initialize and manage the project workflow."
+  if_ready: |
+      1. **Verify & Load:** Optionally fetch tasks using `taskmaster-ai`'s `get_tasks` tool if needed for autonomous context.
+      2. **Set Status:** Set status to '[TASKMASTER: ON]'.
+      3. **Proceed:** Proceed with autonomous Taskmaster operations.

assets/roocode/.roomodes

@@ -0,0 +1,63 @@
+{
+  "customModes": [
+    {
+      "slug": "boomerang",
+      "name": "Boomerang",
+      "roleDefinition": "You are Roo, a strategic workflow orchestrator who coordinates complex tasks by delegating them to appropriate specialized modes. You have a comprehensive understanding of each mode's capabilities and limitations, also your own, and with the information given by the user and other modes in shared context you are enabled to effectively break down complex problems into discrete tasks that can be solved by different specialists using the `taskmaster-ai` system for task and context management.",
+      "customInstructions": "Your role is to coordinate complex workflows by delegating tasks to specialized modes, using `taskmaster-ai` as the central hub for task definition, progress tracking, and context management. \nAs an orchestrator, you should:\nn1. When given a complex task, use contextual information (which gets updated frequently) to break it down into logical subtasks that can be delegated to appropriate specialized modes.\nn2. For each subtask, use the `new_task` tool to delegate. Choose the most appropriate mode for the subtask's specific goal and provide comprehensive instructions in the `message` parameter. \nThese instructions must include:\n*   All necessary context from the parent task or previous subtasks required to complete the work.\n*   A clearly defined scope, specifying exactly what the subtask should accomplish.\n*   An explicit statement that the subtask should *only* perform the work outlined in these instructions and not deviate.\n*   An instruction for the subtask to signal completion by using the `attempt_completion` tool, providing a thorough summary of the outcome in the `result` parameter, keeping in mind that this summary will be the source of truth used to further relay this information to other tasks and for you to keep track of what was completed on this project.\nn3. Track and manage the progress of all subtasks. When a subtask is completed, acknowledge its results and determine the next steps.\nn4. Help the user understand how the different subtasks fit together in the overall workflow. Provide clear reasoning about why you're delegating specific tasks to specific modes.\nn5. Ask clarifying questions when necessary to better understand how to break down complex tasks effectively. If it seems complex delegate to architect to accomplish that \nn6. Use subtasks to maintain clarity. If a request significantly shifts focus or requires a different expertise (mode), consider creating a subtask rather than overloading the current one.",
+      "groups": [
+        "read",
+        "edit",
+        "browser",
+        "command",
+        "mcp"
+      ]
+    },
+    {
+      "slug": "architect",
+      "name": "Architect",
+      "roleDefinition": "You are Roo, an expert technical leader operating in Architect mode. When activated via a delegated task, your focus is solely on analyzing requirements, designing system architecture, planning implementation steps, and performing technical analysis as specified in the task message. You utilize analysis tools as needed and report your findings and designs back using `attempt_completion`. You do not deviate from the delegated task scope.",
+      "customInstructions": "1. Do some information gathering (for example using read_file or search_files) to get more context about the task.\n\n2. You should also ask the user clarifying questions to get a better understanding of the task.\n\n3. Once you've gained more context about the user's request, you should create a detailed plan for how to accomplish the task. Include Mermaid diagrams if they help make your plan clearer.\n\n4. Ask the user if they are pleased with this plan, or if they would like to make any changes. Think of this as a brainstorming session where you can discuss the task and plan the best way to accomplish it.\n\n5. Once the user confirms the plan, ask them if they'd like you to write it to a markdown file.\n\n6. Use the switch_mode tool to request that the user switch to another mode to implement the solution.",
+      "groups": [
+        "read",
+        ["edit", { "fileRegex": "\\.md$", "description": "Markdown files only" }],
+        "command",
+        "mcp"
+      ]
+    },
+    {
+      "slug": "ask",
+      "name": "Ask",
+      "roleDefinition": "You are Roo, a knowledgeable technical assistant.\nWhen activated by another mode via a delegated task, your focus is to research, analyze, and provide clear, concise answers or explanations based *only* on the specific information requested in the delegation message. Use available tools for information gathering and report your findings back using `attempt_completion`.",
+      "customInstructions": "You can analyze code, explain concepts, and access external resources. Make sure to answer the user's questions and don't rush to switch to implementing code. Include Mermaid diagrams if they help make your response clearer.",
+      "groups": [
+        "read",
+        "browser",
+        "mcp"
+      ]
+    },
+    {
+      "slug": "debug",
+      "name": "Debug",
+      "roleDefinition": "You are Roo, an expert software debugger specializing in systematic problem diagnosis and resolution. When activated by another mdode, your task is to meticulously analyze the provided debugging request (potentially referencing Taskmaster tasks, logs, or metrics), use diagnostic tools as instructed to investigate the issue, identify the root cause, and report your findings and recommended next steps back via `attempt_completion`. You focus solely on diagnostics within the scope defined by the delegated task.",
+      "customInstructions": "Reflect on 5-7 different possible sources of the problem, distill those down to 1-2 most likely sources, and then add logs to validate your assumptions. Explicitly ask the user to confirm the diagnosis before fixing the problem.",
+      "groups": [
+        "read",
+        "edit",
+        "command",
+        "mcp"
+      ]
+    },
+    {
+      "slug": "test",
+      "name": "Test",
+      "roleDefinition": "You are Roo, an expert software tester. Your primary focus is executing testing tasks delegated to you by other modes.\nAnalyze the provided scope and context (often referencing a Taskmaster task ID and its `testStrategy`), develop test plans if needed, execute tests diligently, and report comprehensive results (pass/fail, bugs, coverage) back using `attempt_completion`. You operate strictly within the delegated task's boundaries.",
+      "customInstructions": "Focus on the `testStrategy` defined in the Taskmaster task. Develop and execute test plans accordingly. Report results clearly, including pass/fail status, bug details, and coverage information.",
+      "groups": [
+        "read",
+        "command",
+        "mcp"
+      ]
+    }
+  ]
+}

assets/scripts_README.md

@@ -16,29 +16,27 @@ In an AI-driven development process—particularly with tools like [Cursor](http
 8. **Clear subtasks**—remove subtasks from specified tasks to allow regeneration or restructuring.
 9. **Show task details**—display detailed information about a specific task and its subtasks.
 
-## Configuration
+## Configuration (Updated)
 
-The script can be configured through environment variables in a `.env` file at the root of the project:
+Task Master configuration is now managed through two primary methods:
 
-### Required Configuration
-- `ANTHROPIC_API_KEY`: Your Anthropic API key for Claude
+1.  **`.taskmasterconfig` File (Project Root - Primary)**
 
-### Optional Configuration
-- `MODEL`: Specify which Claude model to use (default: "claude-3-7-sonnet-20250219")
-- `MAX_TOKENS`: Maximum tokens for model responses (default: 4000)
-- `TEMPERATURE`: Temperature for model responses (default: 0.7)
-- `PERPLEXITY_API_KEY`: Your Perplexity API key for research-backed subtask generation
-- `PERPLEXITY_MODEL`: Specify which Perplexity model to use (default: "sonar-medium-online")
-- `DEBUG`: Enable debug logging (default: false)
-- `LOG_LEVEL`: Log level - debug, info, warn, error (default: info)
-- `DEFAULT_SUBTASKS`: Default number of subtasks when expanding (default: 3)
-- `DEFAULT_PRIORITY`: Default priority for generated tasks (default: medium)
-- `PROJECT_NAME`: Override default project name in tasks.json
-- `PROJECT_VERSION`: Override default version in tasks.json
+    - Stores AI model selections (`main`, `research`, `fallback`), model parameters (`maxTokens`, `temperature`), `logLevel`, `defaultSubtasks`, `defaultPriority`, `projectName`, etc.
+    - Managed using the `task-master models --setup` command or the `models` MCP tool.
+    - This is the main configuration file for most settings.
+
+2.  **Environment Variables (`.env` File - API Keys Only)**
+    - Used **only** for sensitive **API Keys** (e.g., `ANTHROPIC_API_KEY`, `PERPLEXITY_API_KEY`).
+    - Create a `.env` file in your project root for CLI usage.
+    - See `assets/env.example` for required key names.
+
+**Important:** Settings like `MODEL`, `MAX_TOKENS`, `TEMPERATURE`, `TASKMASTER_LOG_LEVEL`, etc., are **no longer set via `.env`**. Use `task-master models --setup` instead.
 
 ## How It Works
 
 1. **`tasks.json`**:
+
    - A JSON file at the project root containing an array of tasks (each with `id`, `title`, `description`, `status`, etc.).
    - The `meta` field can store additional info like the project's name, version, or reference to the PRD.
    - Tasks can have `subtasks` for more detailed implementation steps.
@@ -111,6 +109,7 @@ task-master update --file=custom-tasks.json --from=5 --prompt="Change database f
 ```
 
 Notes:
+
 - The `--prompt` parameter is required and should explain the changes or new context
 - Only tasks that aren't marked as 'done' will be updated
 - Tasks with ID >= the specified --from value will be updated
@@ -134,6 +133,7 @@ task-master set-status --id=1,2,3 --status=done
 ```
 
 Notes:
+
 - When marking a parent task as "done", all of its subtasks will automatically be marked as "done" as well
 - Common status values are 'done', 'pending', and 'deferred', but any string is accepted
 - You can specify multiple task IDs by separating them with commas
@@ -183,29 +183,25 @@ task-master clear-subtasks --all
 ```
 
 Notes:
+
 - After clearing subtasks, task files are automatically regenerated
 - This is useful when you want to regenerate subtasks with a different approach
 - Can be combined with the `expand` command to immediately generate new subtasks
 - Works with both parent tasks and individual subtasks
 
-## AI Integration
+## AI Integration (Updated)
 
-The script integrates with two AI services:
-
-1. **Anthropic Claude**: Used for parsing PRDs, generating tasks, and creating subtasks.
-2. **Perplexity AI**: Used for research-backed subtask generation when the `--research` flag is specified.
-
-The Perplexity integration uses the OpenAI client to connect to Perplexity's API, which provides enhanced research capabilities for generating more informed subtasks. If the Perplexity API is unavailable or encounters an error, the script will automatically fall back to using Anthropic's Claude.
-
-To use the Perplexity integration:
-1. Obtain a Perplexity API key
-2. Add `PERPLEXITY_API_KEY` to your `.env` file
-3. Optionally specify `PERPLEXITY_MODEL` in your `.env` file (default: "sonar-medium-online")
-4. Use the `--research` flag with the `expand` command
+- The script now uses a unified AI service layer (`ai-services-unified.js`).
+- Model selection (e.g., Claude vs. Perplexity for `--research`) is determined by the configuration in `.taskmasterconfig` based on the requested `role` (`main` or `research`).
+- API keys are automatically resolved from your `.env` file (for CLI) or MCP session environment.
+- To use the research capabilities (e.g., `expand --research`), ensure you have:
+  1.  Configured a model for the `research` role using `task-master models --setup` (Perplexity models are recommended).
+  2.  Added the corresponding API key (e.g., `PERPLEXITY_API_KEY`) to your `.env` file.
 
 ## Logging
 
-The script supports different logging levels controlled by the `LOG_LEVEL` environment variable:
+The script supports different logging levels controlled by the `TASKMASTER_LOG_LEVEL` environment variable:
+
 - `debug`: Detailed information, typically useful for troubleshooting
 - `info`: Confirmation that things are working as expected (default)
 - `warn`: Warning messages that don't prevent execution
@@ -228,17 +224,20 @@ task-master remove-dependency --id=<id> --depends-on=<id>
 These commands:
 
 1. **Allow precise dependency management**:
+
    - Add dependencies between tasks with automatic validation
    - Remove dependencies when they're no longer needed
    - Update task files automatically after changes
 
 2. **Include validation checks**:
+
    - Prevent circular dependencies (a task depending on itself)
    - Prevent duplicate dependencies
    - Verify that both tasks exist before adding/removing dependencies
    - Check if dependencies exist before attempting to remove them
 
 3. **Provide clear feedback**:
+
    - Success messages confirm when dependencies are added/removed
    - Error messages explain why operations failed (if applicable)
 
@@ -263,6 +262,7 @@ task-master validate-dependencies --file=custom-tasks.json
 ```
 
 This command:
+
 - Scans all tasks and subtasks for non-existent dependencies
 - Identifies potential self-dependencies (tasks referencing themselves)
 - Reports all found issues without modifying files
@@ -284,6 +284,7 @@ task-master fix-dependencies --file=custom-tasks.json
 ```
 
 This command:
+
 1. **Validates all dependencies** across tasks and subtasks
 2. **Automatically removes**:
    - References to non-existent tasks and subtasks
@@ -321,6 +322,7 @@ task-master analyze-complexity --research
 ```
 
 Notes:
+
 - The command uses Claude to analyze each task's complexity (or Perplexity with --research flag)
 - Tasks are scored on a scale of 1-10
 - Each task receives a recommended number of subtasks based on DEFAULT_SUBTASKS configuration
@@ -345,12 +347,14 @@ task-master expand --id=8 --num=5 --prompt="Custom prompt"
 ```
 
 When a complexity report exists:
+
 - The `expand` command will use the recommended subtask count from the report (unless overridden)
 - It will use the tailored expansion prompt from the report (unless a custom prompt is provided)
 - When using `--all`, tasks are sorted by complexity score (highest first)
 - The `--research` flag is preserved from the complexity analysis to expansion
 
 The output report structure is:
+
 ```json
 {
 	"meta": {
@@ -369,7 +373,7 @@ The output report structure is:
 			"expansionPrompt": "Create subtasks that handle detecting...",
 			"reasoning": "This task requires sophisticated logic...",
 			"expansionCommand": "task-master expand --id=8 --num=6 --prompt=\"Create subtasks...\" --research"
-    },
+		}
 		// More tasks sorted by complexity score (highest first)
 	]
 }

bin/task-master-init.js

@@ -1,30 +0,0 @@
-#!/usr/bin/env node
-
-/**
- * Claude Task Master Init
- * Direct executable for the init command
- */
-
-import { spawn } from 'child_process';
-import { fileURLToPath } from 'url';
-import { dirname, resolve } from 'path';
-
-const __filename = fileURLToPath(import.meta.url);
-const __dirname = dirname(__filename);
-
-// Get the path to the init script
-const initScriptPath = resolve(__dirname, '../scripts/init.js');
-
-// Pass through all arguments
-const args = process.argv.slice(2);
-
-// Spawn the init script with all arguments
-const child = spawn('node', [initScriptPath, ...args], {
-  stdio: 'inherit',
-  cwd: process.cwd()
-});
-
-// Handle exit
-child.on('close', (code) => {
-  process.exit(code);
-}); 

bin/task-master.js

@@ -49,7 +49,13 @@ function runDevScript(args) {
 		console.error('\nDEBUG - CLI Wrapper Analysis:');
 		console.error('- Original command: ' + process.argv.join(' '));
 		console.error('- Transformed args: ' + args.join(' '));
-    console.error('- dev.js will receive: node ' + devScriptPath + ' ' + args.join(' ') + '\n');
+		console.error(
+			'- dev.js will receive: node ' +
+				devScriptPath +
+				' ' +
+				args.join(' ') +
+				'\n'
+		);
 	}
 
 	// For testing: If TEST_MODE is set, just print args and exit
@@ -86,11 +92,13 @@ function createDevScriptAction(commandName) {
 		// If camelCase flags were found, show error and exit
 		if (camelCaseFlags.length > 0) {
 			console.error('\nError: Please use kebab-case for CLI flags:');
-      camelCaseFlags.forEach(flag => {
+			camelCaseFlags.forEach((flag) => {
 				console.error(`  Instead of: --${flag.original}`);
 				console.error(`  Use:        --${flag.kebabCase}`);
 			});
-      console.error('\nExample: task-master parse-prd --num-tasks=5 instead of --numTasks=5\n');
+			console.error(
+				'\nExample: task-master parse-prd --num-tasks=5 instead of --numTasks=5\n'
+			);
 			process.exit(1);
 		}
 
@@ -113,9 +121,11 @@ function createDevScriptAction(commandName) {
 					// It's a flag - pass through as is
 					commandArgs.push(arg);
 					// Skip the next arg if this is a flag with a value (not --flag=value format)
-          if (!arg.includes('=') && 
+					if (
+						!arg.includes('=') &&
 						i + 1 < process.argv.length &&
-              !process.argv[i+1].startsWith('--')) {
+						!process.argv[i + 1].startsWith('--')
+					) {
 						commandArgs.push(process.argv[++i]);
 					}
 				} else if (!positionals.has(arg)) {
@@ -143,7 +153,9 @@ function createDevScriptAction(commandName) {
 				userOptions.add(kebabName);
 
 				// Add the camelCase version as well
-        const camelName = kebabName.replace(/-([a-z])/g, (_, letter) => letter.toUpperCase());
+				const camelName = kebabName.replace(/-([a-z])/g, (_, letter) =>
+					letter.toUpperCase()
+				);
 				userOptions.add(camelName);
 			}
 		}
@@ -167,7 +179,10 @@ function createDevScriptAction(commandName) {
 			}
 
 			// Skip built-in Commander properties and options the user provided
-      if (['parent', 'commands', 'options', 'rawArgs'].includes(key) || userOptions.has(key)) {
+			if (
+				['parent', 'commands', 'options', 'rawArgs'].includes(key) ||
+				userOptions.has(key)
+			) {
 				return;
 			}
 
@@ -210,39 +225,47 @@ function createDevScriptAction(commandName) {
 	};
 }
 
-// Special case for the 'init' command which uses a different script
-function registerInitCommand(program) {
-  program
-    .command('init')
-    .description('Initialize a new project')
-    .option('-y, --yes', 'Skip prompts and use default values')
-    .option('-n, --name <name>', 'Project name')
-    .option('-d, --description <description>', 'Project description')
-    .option('-v, --version <version>', 'Project version')
-    .option('-a, --author <author>', 'Author name')
-    .option('--skip-install', 'Skip installing dependencies')
-    .option('--dry-run', 'Show what would be done without making changes')
-    .action((options) => {
-      // Pass through any options to the init script
-      const args = ['--yes', 'name', 'description', 'version', 'author', 'skip-install', 'dry-run']
-        .filter(opt => options[opt])
-        .map(opt => {
-          if (opt === 'yes' || opt === 'skip-install' || opt === 'dry-run') {
-            return `--${opt}`;
-          }
-          return `--${opt}=${options[opt]}`;
-        });
+// // Special case for the 'init' command which uses a different script
+// function registerInitCommand(program) {
+// 	program
+// 		.command('init')
+// 		.description('Initialize a new project')
+// 		.option('-y, --yes', 'Skip prompts and use default values')
+// 		.option('-n, --name <name>', 'Project name')
+// 		.option('-d, --description <description>', 'Project description')
+// 		.option('-v, --version <version>', 'Project version')
+// 		.option('-a, --author <author>', 'Author name')
+// 		.option('--skip-install', 'Skip installing dependencies')
+// 		.option('--dry-run', 'Show what would be done without making changes')
+// 		.action((options) => {
+// 			// Pass through any options to the init script
+// 			const args = [
+// 				'--yes',
+// 				'name',
+// 				'description',
+// 				'version',
+// 				'author',
+// 				'skip-install',
+// 				'dry-run'
+// 			]
+// 				.filter((opt) => options[opt])
+// 				.map((opt) => {
+// 					if (opt === 'yes' || opt === 'skip-install' || opt === 'dry-run') {
+// 						return `--${opt}`;
+// 					}
+// 					return `--${opt}=${options[opt]}`;
+// 				});
 
-      const child = spawn('node', [initScriptPath, ...args], {
-        stdio: 'inherit',
-        cwd: process.cwd()
-      });
+// 			const child = spawn('node', [initScriptPath, ...args], {
+// 				stdio: 'inherit',
+// 				cwd: process.cwd()
+// 			});
 
-      child.on('close', (code) => {
-        process.exit(code);
-      });
-    });
-}
+// 			child.on('close', (code) => {
+// 				process.exit(code);
+// 			});
+// 		});
+// }
 
 // Set up the command-line interface
 const program = new Command();
@@ -263,8 +286,8 @@ program.on('--help', () => {
 	displayHelp();
 });
 
-// Add special case commands
-registerInitCommand(program);
+// // Add special case commands
+// registerInitCommand(program);
 
 program
 	.command('dev')
@@ -279,24 +302,18 @@ const tempProgram = new Command();
 registerCommands(tempProgram);
 
 // For each command in the temp instance, add a modified version to our actual program
-tempProgram.commands.forEach(cmd => {
-  if (['init', 'dev'].includes(cmd.name())) {
+tempProgram.commands.forEach((cmd) => {
+	if (['dev'].includes(cmd.name())) {
 		// Skip commands we've already defined specially
 		return;
 	}
 
 	// Create a new command with the same name and description
-  const newCmd = program
-    .command(cmd.name())
-    .description(cmd.description());
+	const newCmd = program.command(cmd.name()).description(cmd.description());
 
 	// Copy all options
-  cmd.options.forEach(opt => {
-    newCmd.option(
-      opt.flags,
-      opt.description,
-      opt.defaultValue
-    );
+	cmd.options.forEach((opt) => {
+		newCmd.option(opt.flags, opt.description, opt.defaultValue);
 	});
 
 	// Set the action to proxy to dev.js
@@ -311,14 +328,21 @@ process.on('uncaughtException', (err) => {
 	// Check if this is a commander.js unknown option error
 	if (err.code === 'commander.unknownOption') {
 		const option = err.message.match(/'([^']+)'/)?.[1];
-    const commandArg = process.argv.find(arg => !arg.startsWith('-') && 
+		const commandArg = process.argv.find(
+			(arg) =>
+				!arg.startsWith('-') &&
 				arg !== 'task-master' &&
 				!arg.includes('/') &&
-                                            arg !== 'node');
+				arg !== 'node'
+		);
 		const command = commandArg || 'unknown';
 
 		console.error(chalk.red(`Error: Unknown option '${option}'`));
-    console.error(chalk.yellow(`Run 'task-master ${command} --help' to see available options for this command`));
+		console.error(
+			chalk.yellow(
+				`Run 'task-master ${command} --help' to see available options for this command`
+			)
+		);
 		process.exit(1);
 	}
 
@@ -327,7 +351,9 @@ process.on('uncaughtException', (err) => {
 		const command = err.message.match(/'([^']+)'/)?.[1];
 
 		console.error(chalk.red(`Error: Unknown command '${command}'`));
-    console.error(chalk.yellow(`Run 'task-master --help' to see available commands`));
+		console.error(
+			chalk.yellow(`Run 'task-master --help' to see available commands`)
+		);
 		process.exit(1);
 	}
 

context/MCP_INTEGRATION.md

@@ -90,13 +90,13 @@ export const simpleFunction = adaptForMcp(originalFunction);
 // Split implementation - completely different code paths for CLI vs MCP
 export const complexFunction = sourceSplitFunction(
 	// CLI version with UI
-  function(param1, param2) {
+	function (param1, param2) {
 		displayBanner();
 		console.log(`Processing ${param1}...`);
 		// ... CLI implementation
 	},
 	// MCP version with structured return
-  function(param1, param2, options = {}) {
+	function (param1, param2, options = {}) {
 		// ... MCP implementation
 		return { success: true, data };
 	}
@@ -186,22 +186,22 @@ const commandMap = {
 
 ```javascript
 // In mcp-server/src/tools/newFeature.js
-import { z } from "zod";
+import { z } from 'zod';
 import {
 	executeTaskMasterCommand,
 	createContentResponse,
-  createErrorResponse,
-} from "./utils.js";
+	createErrorResponse
+} from './utils.js';
 
 export function registerNewFeatureTool(server) {
 	server.addTool({
-    name: "newFeature",
-    description: "Run the new feature",
+		name: 'newFeature',
+		description: 'Run the new feature',
 		parameters: z.object({
-      param1: z.string().describe("First parameter"),
-      param2: z.number().optional().describe("Second parameter"),
-      file: z.string().optional().describe("Path to the tasks file"),
-      projectRoot: z.string().describe("Root directory of the project")
+			param1: z.string().describe('First parameter'),
+			param2: z.number().optional().describe('Second parameter'),
+			file: z.string().optional().describe('Path to the tasks file'),
+			projectRoot: z.string().describe('Root directory of the project')
 		}),
 		execute: async (args, { log }) => {
 			try {
@@ -216,7 +216,7 @@ export function registerNewFeatureTool(server) {
 
 				// Execute the command
 				const result = await executeTaskMasterCommand(
-          "new-feature",
+					'new-feature',
 					log,
 					cmdArgs,
 					projectRoot
@@ -231,7 +231,7 @@ export function registerNewFeatureTool(server) {
 				log.error(`Error in new feature: ${error.message}`);
 				return createErrorResponse(`Error in new feature: ${error.message}`);
 			}
-    },
+		}
 	});
 }
 ```
@@ -240,7 +240,7 @@ export function registerNewFeatureTool(server) {
 
 ```javascript
 // In mcp-server/src/tools/index.js
-import { registerNewFeatureTool } from "./newFeature.js";
+import { registerNewFeatureTool } from './newFeature.js';
 
 export function registerTaskMasterTools(server) {
 	// ... existing registrations

context/chats/max-min-tokens.txt.md

@@ -0,0 +1,368 @@
+We want to refine how Task Master handles AI model token limits to be more precise, by:
+
+1.  Distinguishing between `maxInputTokens` and `maxOutputTokens` in the configuration.
+2.  Dynamically adjusting the `maxOutputTokens` for an API call based on the actual prompt length to stay within the model's total context window (or respecting separate input/output limits if the API and model support that).
+3.  Ensuring that `ai-services-unified.js` uses these more granular limits.
+
+This is a good improvement for both cost control and preventing errors.
+
+Here's a plan:
+
+**Phase 1: Configuration and Core Logic Updates**
+
+1.  **Update `.taskmasterconfig` Structure:**
+    - I'll modify the `models` section in your `.taskmasterconfig`. For each role (`main`, `research`, `fallback`), `maxTokens` will be replaced with `maxInputTokens` and `maxOutputTokens`.
+      - We'll need to decide on reasonable default values for these new fields. We can look at the current `maxTokens` and the model's known limits to make an initial guess.
+2.  **Update `MODEL_MAP` in `ai-services-unified.js`:**
+    - This array already stores cost data. We need to ensure it also stores the _absolute_ maximum input and output tokens for each model listed (e.g., `model_max_input_tokens`, `model_max_output_tokens`). If these fields are not present, they will need to be added. The values in `.taskmasterconfig` will then represent user-defined operational limits, which should ideally be validated against these absolute maximums.
+3.  **Update `config-manager.js`:**
+    - Getter functions like `getParametersForRole` will be updated to fetch `maxInputTokens` and `maxOutputTokens` instead of the singular `maxTokens`.
+    - New getters might be needed if we want to access the model's absolute limits directly from `MODEL_MAP` via `config-manager.js`.
+4.  **Update `ai-services-unified.js` (`_unifiedServiceRunner`):**
+    - **Token Counting:** This is a crucial step. Before an API call, we need to estimate the token count of the combined `systemPrompt` and `userPrompt`.
+      - The Vercel AI SDK or the individual provider SDKs might offer utilities for this. For example, some SDKs expose a `tokenizer` or a way to count tokens for a given string.
+      - If a direct utility isn't available through the Vercel SDK for the specific provider, we might need to use a library like `tiktoken` for OpenAI/Anthropic models or investigate provider-specific tokenization. This could be complex as tokenization varies between models.
+      - For now, let's assume we can get a reasonable estimate.
+    - **Dynamic Output Token Calculation & Validation:**
+      - Retrieve `configured_max_input_tokens` and `configured_max_output_tokens` from `config-manager.js` for the current role.
+      - Retrieve `model_absolute_max_input_tokens` and `model_absolute_max_output_tokens` from `MODEL_MAP`.
+      - Let `prompt_tokens = countTokens(systemPrompt + userPrompt)`.
+      - **Input Validation:** If `prompt_tokens > configured_max_input_tokens` OR `prompt_tokens > model_absolute_max_input_tokens`, throw an error. (We might also consider auto-truncation strategies in the future, but an error is safer to start).
+      - **Output Calculation:** The `max_tokens` parameter sent to the API (which typically refers to the _max number of tokens to generate_) should be `configured_max_output_tokens`. We also need to ensure this doesn't violate the model's absolute output limit.
+      - Some models have a _total_ context window (input + output). If this is the case for a model, the `max_tokens` parameter for the API call might need to be `min(configured_max_output_tokens, model_absolute_total_tokens - prompt_tokens)`. However, many modern APIs handle separate input and output limits, simplifying this. We'll aim to pass `configured_max_output_tokens` as the API's `max_tokens` parameter, assuming the input validation has passed.
+    - **API Call Parameter:** Update the `callParams` to use the correctly determined `max_tokens` for generation (which will be our `configured_max_output_tokens`).
+
+**Phase 2: Error Handling and Refinements**
+
+1.  **Enhanced Error Handling:** Provide clear error messages if prompt tokens exceed input limits, or if API calls fail due to token issues despite our calculations.
+2.  **Validation:** Add validation (perhaps in `config-manager.js` or when `task-master models --setup` is run) to ensure `configured_max_input_tokens` and `configured_max_output_tokens` in `.taskmasterconfig` do not exceed the `model_absolute_max_input_tokens` and `model_absolute_max_output_tokens` from `MODEL_MAP`.
+
+Let's start by inspecting `scripts/modules/config-manager.js` to see how parameters and `MODEL_MAP` are currently handled. This will inform the changes needed for `.taskmasterconfig` and `ai-services-unified.js`.
+
+I will now read `scripts/modules/config-manager.js`.
+
+Okay, I've reviewed `scripts/modules/config-manager.js`. Here's what I've gathered and how it impacts the plan:
+
+- **`MODEL_MAP` Source:** `MODEL_MAP` is loaded from `supported-models.json`. This is excellent, as it means we can update the model capabilities (including new token limits) in a structured JSON file.
+- **Configuration Loading:** `_loadAndValidateConfig` handles loading `.taskmasterconfig` and merging it with `DEFAULTS`.
+- **Getters:** There are specific getters for `maxTokens` for each role (e.g., `getMainMaxTokens`). We will need to update these.
+- **`getParametersForRole`:** This function already exists and is a good candidate for returning the new `maxInputTokens` and `maxOutputTokens`.
+
+Here's the refined plan:
+
+**Phase 1: Configuration and Data Structures**
+
+1.  **Update `supported-models.json`:**
+
+    - For each model entry in `supported-models.json`, we need to add `maxInputTokens` and `maxOutputTokens` fields. These should reflect the _absolute maximums_ for that specific model.
+    - Example entry change:
+
+      ```json
+      // Before
+      {
+          "id": "claude-3-7-sonnet-20250219",
+          "name": "Claude 3.7 Sonnet (Preview)",
+          "context_window": 200000, // This might be total context
+          "cost_per_1m_tokens": { "input": 3, "output": 15, "currency": "USD" }
+      }
+
+      // After (assuming 200k is total, and we make a reasonable split or find official numbers)
+      {
+          "id": "claude-3-7-sonnet-20250219",
+          "name": "Claude 3.7 Sonnet (Preview)",
+          "maxInputTokens": 190000, // Example
+          "maxOutputTokens": 8192,  // Example, often smaller for generation
+          "cost_per_1m_tokens": { "input": 3, "output": 15, "currency": "USD" }
+      }
+      ```
+
+    - I will need to find the official input/output token limits for the models currently in your `MODEL_MAP`. If you have this information handy, it would speed things up. Otherwise, I can make educated guesses or search for them.
+
+2.  **Update `.taskmasterconfig` (Defaults and User File):**
+    - In `scripts/modules/config-manager.js`, modify the `DEFAULTS` object. For each role (`main`, `research`, `fallback`), replace `maxTokens` with:
+      - `maxInputTokens`: A sensible default (e.g., a large portion of the model's capability, but user-configurable).
+      - `maxOutputTokens`: A sensible default for generation (e.g., 4096 or 8192).
+    - You will then need to manually update your existing `.taskmasterconfig` file to reflect this new structure. I can provide the snippet for you to paste.
+3.  **Update `config-manager.js`:**
+    - Modify `getParametersForRole(role, explicitRoot = null)`:
+      - It currently fetches `maxTokens` and `temperature`.
+      - Update it to fetch `maxInputTokens`, `maxOutputTokens`, and `temperature` from the loaded config for the given role.
+    - Remove the role-specific `getMaxTokens` functions (e.g., `getMainMaxTokens`, `getResearchMaxTokens`, `getFallbackMaxTokens`). The `getParametersForRole` will be the central way to get these.
+    - (Optional, for later validation) Consider adding a new function `getModelCapabilities(providerName, modelId)` that reads from `MODEL_MAP` to return the absolute `maxInputTokens` and `maxOutputTokens` for a given model. This would be useful for validating the user's settings in `.taskmasterconfig`.
+
+**Phase 2: Core Logic in `ai-services-unified.js`**
+
+1.  **Token Counting (`_unifiedServiceRunner`):**
+
+    - This is the most complex part. We need a reliable way to count tokens for the prompts.
+      - **Strategy 1 (Ideal):** Leverage Vercel AI SDK. The SDK might provide a way to get a tokenizer for the active model or a utility function. We'll need to investigate its capabilities.
+      - **Strategy 2 (Fallback):** Use a library like `tiktoken` for models compatible with OpenAI's tokenization (many are, including some Anthropic models). For other models, we might need provider-specific tokenizers or make estimations (less ideal).
+      - **Initial Approach:** Let's try to find a Vercel AI SDK utility first. If not, we'll start with `tiktoken` as a common case and acknowledge that other models might need specific handling later.
+    - The function `_unifiedServiceRunner` will call this token counting utility:
+
+      ```javascript
+      // Placeholder for token counting
+      function countTokens(text, modelId /* or providerName */) {
+      	// ... implementation using SDK or library ...
+      	// This is a simplification; actual tokenization is model-specific.
+      	// For now, a rough estimate might be (text.length / 4) as a placeholder
+      	// if a proper tokenizer isn't immediately available.
+      	if (!text) return 0;
+      	return Math.ceil(text.length / 3.5); // Very rough general estimate
+      }
+
+      const promptTokens = countTokens(systemPrompt) + countTokens(prompt);
+      ```
+
+2.  **Dynamic Output Token Calculation & Validation (`_unifiedServiceRunner`):**
+
+    - Fetch parameters using the updated `getParametersForRole` from `config-manager.js`:
+      ```javascript
+      const roleParams = getParametersForRole(
+      	currentRole,
+      	effectiveProjectRoot
+      );
+      // roleParams will now contain { maxInputTokens, maxOutputTokens, temperature }
+      ```
+    - Fetch model's absolute limits from `MODEL_MAP` (we'll need a helper in `config-manager.js` or do it directly in `ai-services-unified.js` for now):
+      ```javascript
+      // Simplified; ideally use a robust getter from config-manager
+      const modelInfo = MODEL_MAP[providerName?.toLowerCase()]?.find(
+      	(m) => m.id === modelId
+      );
+      const modelAbsoluteMaxInput = modelInfo?.maxInputTokens || Infinity;
+      const modelAbsoluteMaxOutput =
+      	modelInfo?.maxOutputTokens || roleParams.maxOutputTokens; // Fallback to configured if not in map
+      ```
+    - **Input Validation:**
+      ```javascript
+      if (promptTokens > roleParams.maxInputTokens) {
+      	throw new Error(
+      		`Prompt (${promptTokens} tokens) exceeds configured max input tokens (${roleParams.maxInputTokens}) for role '${currentRole}'.`
+      	);
+      }
+      if (promptTokens > modelAbsoluteMaxInput) {
+      	throw new Error(
+      		`Prompt (${promptTokens} tokens) exceeds model's absolute max input tokens (${modelAbsoluteMaxInput}) for ${modelId}.`
+      	);
+      }
+      ```
+    - **API Call Parameter (`max_tokens` for generation):**
+      The `max_tokens` parameter passed to the provider's API call should be `roleParams.maxOutputTokens`. We must also ensure this doesn't exceed the model's absolute output capability.
+
+      ```javascript
+      const apiMaxOutputTokens = Math.min(
+      	roleParams.maxOutputTokens,
+      	modelAbsoluteMaxOutput
+      );
+
+      const callParams = {
+      	apiKey,
+      	modelId,
+      	// Use apiMaxOutputTokens for the actual API call
+      	maxTokens: apiMaxOutputTokens, // This usually means max tokens to GENERATE
+      	temperature: roleParams.temperature,
+      	messages,
+      	baseUrl,
+      	...(serviceType === 'generateObject' && { schema, objectName }),
+      	...restApiParams
+      };
+      ```
+
+3.  **Update `logAiUsage`:**
+    - The cost calculation in `logAiUsage` seems correct as it already uses `inputCost` and `outputCost` per 1M tokens. This part should remain compatible.
+
+**Next Steps:**
+
+1.  **Modify `supported-models.json`:** I need the content of this file to propose the new `maxInputTokens` and `maxOutputTokens` fields. Please provide it.
+2.  **Decide on Tokenizer Strategy:** What are your thoughts on the token counting? Are you aware of any utilities within Vercel AI SDK for this, or should we plan to integrate `tiktoken` initially?
+
+Once I have the content of `supported-models.json`, I can draft the changes for it and then proceed to `config-manager.js` and `.taskmasterconfig`.
+
+```json
+        // Before
+        {
+            "id": "claude-3-7-sonnet-20250219",
+            "name": "Claude 3.7 Sonnet (Preview)",
+            "context_window": 200000, // This might be total context
+            "cost_per_1m_tokens": { "input": 3, "output": 15, "currency": "USD" }
+        }
+
+        // After (assuming 200k is total, and we make a reasonable split or find official numbers)
+        {
+            "id": "claude-3-7-sonnet-20250219",
+            "name": "Claude 3.7 Sonnet (Preview)",
+            "maxInputTokens": 190000, // Example
+            "maxOutputTokens": 8192,  // Example, often smaller for generation
+            "cost_per_1m_tokens": { "input": 3, "output": 15, "currency": "USD" }
+        }
+```
+
+```javascript
+// Placeholder for token counting
+function countTokens(text, modelId /* or providerName */) {
+	// ... implementation using SDK or library ...
+	// This is a simplification; actual tokenization is model-specific.
+	// For now, a rough estimate might be (text.length / 4) as a placeholder
+	// if a proper tokenizer isn't immediately available.
+	if (!text) return 0;
+	return Math.ceil(text.length / 3.5); // Very rough general estimate
+}
+
+const promptTokens = countTokens(systemPrompt) + countTokens(prompt);
+```
+
+```javascript
+const roleParams = getParametersForRole(currentRole, effectiveProjectRoot);
+// roleParams will now contain { maxInputTokens, maxOutputTokens, temperature }
+```
+
+```javascript
+// Simplified; ideally use a robust getter from config-manager
+const modelInfo = MODEL_MAP[providerName?.toLowerCase()]?.find(
+	(m) => m.id === modelId
+);
+const modelAbsoluteMaxInput = modelInfo?.maxInputTokens || Infinity;
+const modelAbsoluteMaxOutput =
+	modelInfo?.maxOutputTokens || roleParams.maxOutputTokens; // Fallback to configured if not in map
+```
+
+```javascript
+if (promptTokens > roleParams.maxInputTokens) {
+	throw new Error(
+		`Prompt (${promptTokens} tokens) exceeds configured max input tokens (${roleParams.maxInputTokens}) for role '${currentRole}'.`
+	);
+}
+if (promptTokens > modelAbsoluteMaxInput) {
+	throw new Error(
+		`Prompt (${promptTokens} tokens) exceeds model's absolute max input tokens (${modelAbsoluteMaxInput}) for ${modelId}.`
+	);
+}
+```
+
+```javascript
+const apiMaxOutputTokens = Math.min(
+	roleParams.maxOutputTokens,
+	modelAbsoluteMaxOutput
+);
+
+const callParams = {
+	apiKey,
+	modelId,
+	// Use apiMaxOutputTokens for the actual API call
+	maxTokens: apiMaxOutputTokens, // This usually means max tokens to GENERATE
+	temperature: roleParams.temperature,
+	messages,
+	baseUrl,
+	...(serviceType === 'generateObject' && { schema, objectName }),
+	...restApiParams
+};
+```
+
+Okay, I have the contents of `supported-models.json`.
+
+It seems many models have a `max_tokens` field, which I assume is the _total context window_. Some don't have it, and for others (like OpenAI `gpt-4o`), the listed `max_tokens` (16384) is known to be its _output_ token limit when using the Chat Completions API, while the context window is much larger (128k). This highlights the complexity: `max_tokens` in `supported-models.json` is used inconsistently.
+
+**Revised Plan for `supported-models.json` and Token Definitions:**
+
+To bring clarity, we'll introduce two new fields and ensure their meaning is consistent:
+
+- `contextWindowTokens`: The total number of tokens the model can process (input + output). This would replace the current ambiguous `max_tokens`.
+- `maxOutputTokens`: The maximum number of tokens the model can _generate_ in a single response. This is often smaller than the total context window, especially for larger models.
+
+If a model _only_ specifies a total context window, we'll have to make a reasonable assumption for `maxOutputTokens` (e.g., 4096 or 8192, or a fraction of the total context window). If it only specifies an output token limit (like some OpenAI models in certain API modes), we'll need to find its total context window.
+
+**Updated `supported-models.json` Structure (Example):**
+
+```json
+// For a model like Anthropic Claude 3.7 Sonnet (Preview)
+{
+    "id": "claude-3-7-sonnet-20250219",
+    "swe_score": 0.623,
+    "cost_per_1m_tokens": { "input": 3.0, "output": 15.0 },
+    "allowed_roles": ["main", "fallback"],
+    "contextWindowTokens": 200000, // From Anthropic's documentation
+    "maxOutputTokens": 8192     // Anthropic default, user can override in .taskmasterconfig
+}
+
+// For a model like OpenAI GPT-4o
+{
+    "id": "gpt-4o",
+    "swe_score": 0.332,
+    "cost_per_1m_tokens": { "input": 2.5, "output": 10.0 },
+    "allowed_roles": ["main", "fallback"],
+    "contextWindowTokens": 128000, // Official context window
+    "maxOutputTokens": 16384    // Max output for chat completions is 16k for gpt-4o (used to be 4k/8k for older gpt-4)
+                                // but the model card mentions 128k total. The API call parameter for `max_tokens` sets this output cap.
+}
+```
+
+I will proceed to generate the updated `supported-models.json` content. This will be a significant change. I will make my best effort to find the correct `contextWindowTokens` and `maxOutputTokens` for each model. If official numbers are ambiguous or not readily available, I'll use sensible defaults and add a comment.
+
+**Regarding Tokenizer Strategy:**
+
+- **Vercel AI SDK:** The `ai` package (Vercel AI SDK) itself is a lightweight wrapper. Tokenization is usually handled by the underlying provider-specific SDKs (e.g., `@anthropic-ai/sdk`, `openai`). The Vercel SDK doesn't provide a universal tokenizer.
+- **Provider SDKs:**
+  - `@anthropic-ai/sdk`: Does not expose a public tokenizer directly. Anthropic recommends counting based on their guidelines (roughly 3.5 chars/token for English).
+  - `openai` (for Node.js): The `gpt-3-encoder` or `tiktoken` libraries are commonly used. `tiktoken` is more current.
+- **`tiktoken`:** This is a good general-purpose library for OpenAI models and those that use compatible tokenization (many models fine-tuned from Llama, etc., might be close). It supports various encodings.
+- **Recommendation:**
+  1.  Start by integrating `tiktoken`. We can select the encoding based on the provider or even specific model if needed (e.g., `cl100k_base` for gpt-4, gpt-3.5-turbo, DALL-E models).
+  2.  For providers where `tiktoken` is not accurate (e.g., Google's Gemini, Perplexity if they have proprietary tokenizers), we might have to rely on character-based estimations (e.g., `length / N`) as a rougher guide or investigate if their specific SDKs offer token counting.
+  3.  The Vercel AI SDK's `experimental_streamObject` and other functions _might_ internally handle some aspects of token counting for request preparation, but we need explicit counting for our logic _before_ the call.
+
+For now, let's assume we'll add a `countTokens` utility that uses `tiktoken` for OpenAI and Anthropic (as Anthropic's guidance is character-based but `cl100k_base` is often a decent proxy for their tokenization for rough estimates, though not perfect), and a character-based fallback for others.
+
+I will now generate the proposed changes for `scripts/modules/supported-models.json`. This will be a large diff.
+
+After this, we'll move to:
+
+1.  Updating `.taskmasterconfig` defaults in `config-manager.js` and providing you the snippet for your user file.
+2.  Updating `config-manager.js` getters.
+3.  Implementing the logic in `ai-services-unified.js`.
+
+```json
+// For a model like Anthropic Claude 3.7 Sonnet (Preview)
+{
+    "id": "claude-3-7-sonnet-20250219",
+    "swe_score": 0.623,
+    "cost_per_1m_tokens": { "input": 3.0, "output": 15.0 },
+    "allowed_roles": ["main", "fallback"],
+    "contextWindowTokens": 200000, // From Anthropic's documentation
+    "maxOutputTokens": 8192     // Anthropic default, user can override in .taskmasterconfig
+}
+
+// For a model like OpenAI GPT-4o
+{
+    "id": "gpt-4o",
+    "swe_score": 0.332,
+    "cost_per_1m_tokens": { "input": 2.5, "output": 10.0 },
+    "allowed_roles": ["main", "fallback"],
+    "contextWindowTokens": 128000, // Official context window
+    "maxOutputTokens": 16384    // Max output for chat completions is 16k for gpt-4o (used to be 4k/8k for older gpt-4)
+                                // but the model card mentions 128k total. The API call parameter for `max_tokens` sets this output cap.
+}
+```
+
+```json
+// For a model like Anthropic Claude 3.7 Sonnet (Preview)
+{
+    "id": "claude-3-7-sonnet-20250219",
+    "swe_score": 0.623,
+    "cost_per_1m_tokens": { "input": 3.0, "output": 15.0 },
+    "allowed_roles": ["main", "fallback"],
+    "contextWindowTokens": 200000, // From Anthropic's documentation
+    "maxOutputTokens": 8192     // Anthropic default, user can override in .taskmasterconfig
+}
+
+// For a model like OpenAI GPT-4o
+{
+    "id": "gpt-4o",
+    "swe_score": 0.332,
+    "cost_per_1m_tokens": { "input": 2.5, "output": 10.0 },
+    "allowed_roles": ["main", "fallback"],
+    "contextWindowTokens": 128000, // Official context window
+    "maxOutputTokens": 16384    // Max output for chat completions is 16k for gpt-4o (used to be 4k/8k for older gpt-4)
+                                // but the model card mentions 128k total. The API call parameter for `max_tokens` sets this output cap.
+}
+```

docs/README.md

@@ -0,0 +1,22 @@
+# Task Master Documentation
+
+Welcome to the Task Master documentation. Use the links below to navigate to the information you need:
+
+## Getting Started
+
+- [Configuration Guide](configuration.md) - Set up environment variables and customize Task Master
+- [Tutorial](tutorial.md) - Step-by-step guide to getting started with Task Master
+
+## Reference
+
+- [Command Reference](command-reference.md) - Complete list of all available commands
+- [Task Structure](task-structure.md) - Understanding the task format and features
+
+## Examples & Licensing
+
+- [Example Interactions](examples.md) - Common Cursor AI interaction examples
+- [Licensing Information](licensing.md) - Detailed information about the license
+
+## Need More Help?
+
+If you can't find what you're looking for in these docs, please check the [main README](../README.md) or visit our [GitHub repository](https://github.com/eyaltoledano/claude-task-master).

docs/ai-client-utils-example.md

@@ -1,258 +0,0 @@
-# AI Client Utilities for MCP Tools
-
-This document provides examples of how to use the new AI client utilities with AsyncOperationManager in MCP tools.
-
-## Basic Usage with Direct Functions
-
-```javascript
-// In your direct function implementation:
-import { 
-  getAnthropicClientForMCP, 
-  getModelConfig, 
-  handleClaudeError 
-} from '../utils/ai-client-utils.js';
-
-export async function someAiOperationDirect(args, log, context) {
-  try {
-    // Initialize Anthropic client with session from context
-    const client = getAnthropicClientForMCP(context.session, log);
-    
-    // Get model configuration with defaults or session overrides
-    const modelConfig = getModelConfig(context.session);
-    
-    // Make API call with proper error handling
-    try {
-      const response = await client.messages.create({
-        model: modelConfig.model,
-        max_tokens: modelConfig.maxTokens,
-        temperature: modelConfig.temperature,
-        messages: [
-          { role: 'user', content: 'Your prompt here' }
-        ]
-      });
-      
-      return {
-        success: true,
-        data: response
-      };
-    } catch (apiError) {
-      // Use helper to get user-friendly error message
-      const friendlyMessage = handleClaudeError(apiError);
-      
-      return {
-        success: false,
-        error: {
-          code: 'AI_API_ERROR',
-          message: friendlyMessage
-        }
-      };
-    }
-  } catch (error) {
-    // Handle client initialization errors
-    return {
-      success: false,
-      error: {
-        code: 'AI_CLIENT_ERROR',
-        message: error.message
-      }
-    };
-  }
-}
-```
-
-## Integration with AsyncOperationManager
-
-```javascript
-// In your MCP tool implementation:
-import { AsyncOperationManager, StatusCodes } from '../../utils/async-operation-manager.js';
-import { someAiOperationDirect } from '../../core/direct-functions/some-ai-operation.js';
-
-export async function someAiOperation(args, context) {
-  const { session, mcpLog } = context;
-  const log = mcpLog || console;
-  
-  try {
-    // Create operation description
-    const operationDescription = `AI operation: ${args.someParam}`;
-    
-    // Start async operation
-    const operation = AsyncOperationManager.createOperation(
-      operationDescription,
-      async (reportProgress) => {
-        try {
-          // Initial progress report
-          reportProgress({
-            progress: 0,
-            status: 'Starting AI operation...'
-          });
-          
-          // Call direct function with session and progress reporting
-          const result = await someAiOperationDirect(
-            args, 
-            log, 
-            {
-              reportProgress,
-              mcpLog: log,
-              session
-            }
-          );
-          
-          // Final progress update
-          reportProgress({
-            progress: 100,
-            status: result.success ? 'Operation completed' : 'Operation failed',
-            result: result.data,
-            error: result.error
-          });
-          
-          return result;
-        } catch (error) {
-          // Handle errors in the operation
-          reportProgress({
-            progress: 100,
-            status: 'Operation failed',
-            error: {
-              message: error.message,
-              code: error.code || 'OPERATION_FAILED'
-            }
-          });
-          throw error;
-        }
-      }
-    );
-    
-    // Return immediate response with operation ID
-    return {
-      status: StatusCodes.ACCEPTED,
-      body: {
-        success: true,
-        message: 'Operation started',
-        operationId: operation.id
-      }
-    };
-  } catch (error) {
-    // Handle errors in the MCP tool
-    log.error(`Error in someAiOperation: ${error.message}`);
-    return {
-      status: StatusCodes.INTERNAL_SERVER_ERROR,
-      body: {
-        success: false,
-        error: {
-          code: 'OPERATION_FAILED',
-          message: error.message
-        }
-      }
-    };
-  }
-}
-```
-
-## Using Research Capabilities with Perplexity
-
-```javascript
-// In your direct function:
-import { 
-  getPerplexityClientForMCP, 
-  getBestAvailableAIModel 
-} from '../utils/ai-client-utils.js';
-
-export async function researchOperationDirect(args, log, context) {
-  try {
-    // Get the best AI model for this operation based on needs
-    const { type, client } = await getBestAvailableAIModel(
-      context.session, 
-      { requiresResearch: true },
-      log
-    );
-    
-    // Report which model we're using
-    if (context.reportProgress) {
-      await context.reportProgress({
-        progress: 10,
-        status: `Using ${type} model for research...`
-      });
-    }
-    
-    // Make API call based on the model type
-    if (type === 'perplexity') {
-      // Call Perplexity
-      const response = await client.chat.completions.create({
-        model: context.session?.env?.PERPLEXITY_MODEL || 'sonar-medium-online',
-        messages: [
-          { role: 'user', content: args.researchQuery }
-        ],
-        temperature: 0.1
-      });
-      
-      return {
-        success: true,
-        data: response.choices[0].message.content
-      };
-    } else {
-      // Call Claude as fallback
-      // (Implementation depends on specific needs)
-      // ...
-    }
-  } catch (error) {
-    // Handle errors
-    return {
-      success: false,
-      error: {
-        code: 'RESEARCH_ERROR',
-        message: error.message
-      }
-    };
-  }
-}
-```
-
-## Model Configuration Override Example
-
-```javascript
-// In your direct function:
-import { getModelConfig } from '../utils/ai-client-utils.js';
-
-// Using custom defaults for a specific operation
-const operationDefaults = {
-  model: 'claude-3-haiku-20240307',  // Faster, smaller model
-  maxTokens: 1000,                  // Lower token limit
-  temperature: 0.2                  // Lower temperature for more deterministic output
-};
-
-// Get model config with operation-specific defaults
-const modelConfig = getModelConfig(context.session, operationDefaults);
-
-// Now use modelConfig in your API calls
-const response = await client.messages.create({
-  model: modelConfig.model,
-  max_tokens: modelConfig.maxTokens,
-  temperature: modelConfig.temperature,
-  // Other parameters...
-});
-```
-
-## Best Practices
-
-1. **Error Handling**:
-   - Always use try/catch blocks around both client initialization and API calls
-   - Use `handleClaudeError` to provide user-friendly error messages
-   - Return standardized error objects with code and message
-
-2. **Progress Reporting**:
-   - Report progress at key points (starting, processing, completing)
-   - Include meaningful status messages
-   - Include error details in progress reports when failures occur
-
-3. **Session Handling**:
-   - Always pass the session from the context to the AI client getters
-   - Use `getModelConfig` to respect user settings from session
-
-4. **Model Selection**:
-   - Use `getBestAvailableAIModel` when you need to select between different models
-   - Set `requiresResearch: true` when you need Perplexity capabilities
-
-5. **AsyncOperationManager Integration**:
-   - Create descriptive operation names
-   - Handle all errors within the operation function
-   - Return standardized results from direct functions
-   - Return immediate responses with operation IDs 

docs/command-reference.md

@@ -0,0 +1,238 @@
+# Task Master Command Reference
+
+Here's a comprehensive reference of all available commands:
+
+## Parse PRD
+
+```bash
+# Parse a PRD file and generate tasks
+task-master parse-prd <prd-file.txt>
+
+# Limit the number of tasks generated
+task-master parse-prd <prd-file.txt> --num-tasks=10
+```
+
+## List Tasks
+
+```bash
+# List all tasks
+task-master list
+
+# List tasks with a specific status
+task-master list --status=<status>
+
+# List tasks with subtasks
+task-master list --with-subtasks
+
+# List tasks with a specific status and include subtasks
+task-master list --status=<status> --with-subtasks
+```
+
+## Show Next Task
+
+```bash
+# Show the next task to work on based on dependencies and status
+task-master next
+```
+
+## Show Specific Task
+
+```bash
+# Show details of a specific task
+task-master show <id>
+# or
+task-master show --id=<id>
+
+# View a specific subtask (e.g., subtask 2 of task 1)
+task-master show 1.2
+```
+
+## Update Tasks
+
+```bash
+# Update tasks from a specific ID and provide context
+task-master update --from=<id> --prompt="<prompt>"
+
+# Update tasks using research role
+task-master update --from=<id> --prompt="<prompt>" --research
+```
+
+## Update a Specific Task
+
+```bash
+# Update a single task by ID with new information
+task-master update-task --id=<id> --prompt="<prompt>"
+
+# Use research-backed updates
+task-master update-task --id=<id> --prompt="<prompt>" --research
+```
+
+## Update a Subtask
+
+```bash
+# Append additional information to a specific subtask
+task-master update-subtask --id=<parentId.subtaskId> --prompt="<prompt>"
+
+# Example: Add details about API rate limiting to subtask 2 of task 5
+task-master update-subtask --id=5.2 --prompt="Add rate limiting of 100 requests per minute"
+
+# Use research-backed updates
+task-master update-subtask --id=<parentId.subtaskId> --prompt="<prompt>" --research
+```
+
+Unlike the `update-task` command which replaces task information, the `update-subtask` command _appends_ new information to the existing subtask details, marking it with a timestamp. This is useful for iteratively enhancing subtasks while preserving the original content.
+
+## Generate Task Files
+
+```bash
+# Generate individual task files from tasks.json
+task-master generate
+```
+
+## Set Task Status
+
+```bash
+# Set status of a single task
+task-master set-status --id=<id> --status=<status>
+
+# Set status for multiple tasks
+task-master set-status --id=1,2,3 --status=<status>
+
+# Set status for subtasks
+task-master set-status --id=1.1,1.2 --status=<status>
+```
+
+When marking a task as "done", all of its subtasks will automatically be marked as "done" as well.
+
+## Expand Tasks
+
+```bash
+# Expand a specific task with subtasks
+task-master expand --id=<id> --num=<number>
+
+# Expand with additional context
+task-master expand --id=<id> --prompt="<context>"
+
+# Expand all pending tasks
+task-master expand --all
+
+# Force regeneration of subtasks for tasks that already have them
+task-master expand --all --force
+
+# Research-backed subtask generation for a specific task
+task-master expand --id=<id> --research
+
+# Research-backed generation for all tasks
+task-master expand --all --research
+```
+
+## Clear Subtasks
+
+```bash
+# Clear subtasks from a specific task
+task-master clear-subtasks --id=<id>
+
+# Clear subtasks from multiple tasks
+task-master clear-subtasks --id=1,2,3
+
+# Clear subtasks from all tasks
+task-master clear-subtasks --all
+```
+
+## Analyze Task Complexity
+
+```bash
+# Analyze complexity of all tasks
+task-master analyze-complexity
+
+# Save report to a custom location
+task-master analyze-complexity --output=my-report.json
+
+# Use a specific LLM model
+task-master analyze-complexity --model=claude-3-opus-20240229
+
+# Set a custom complexity threshold (1-10)
+task-master analyze-complexity --threshold=6
+
+# Use an alternative tasks file
+task-master analyze-complexity --file=custom-tasks.json
+
+# Use Perplexity AI for research-backed complexity analysis
+task-master analyze-complexity --research
+```
+
+## View Complexity Report
+
+```bash
+# Display the task complexity analysis report
+task-master complexity-report
+
+# View a report at a custom location
+task-master complexity-report --file=my-report.json
+```
+
+## Managing Task Dependencies
+
+```bash
+# Add a dependency to a task
+task-master add-dependency --id=<id> --depends-on=<id>
+
+# Remove a dependency from a task
+task-master remove-dependency --id=<id> --depends-on=<id>
+
+# Validate dependencies without fixing them
+task-master validate-dependencies
+
+# Find and fix invalid dependencies automatically
+task-master fix-dependencies
+```
+
+## Add a New Task
+
+```bash
+# Add a new task using AI (main role)
+task-master add-task --prompt="Description of the new task"
+
+# Add a new task using AI (research role)
+task-master add-task --prompt="Description of the new task" --research
+
+# Add a task with dependencies
+task-master add-task --prompt="Description" --dependencies=1,2,3
+
+# Add a task with priority
+task-master add-task --prompt="Description" --priority=high
+```
+
+## Initialize a Project
+
+```bash
+# Initialize a new project with Task Master structure
+task-master init
+```
+
+## Configure AI Models
+
+```bash
+# View current AI model configuration and API key status
+task-master models
+
+# Set the primary model for generation/updates (provider inferred if known)
+task-master models --set-main=claude-3-opus-20240229
+
+# Set the research model
+task-master models --set-research=sonar-pro
+
+# Set the fallback model
+task-master models --set-fallback=claude-3-haiku-20240307
+
+# Set a custom Ollama model for the main role
+task-master models --set-main=my-local-llama --ollama
+
+# Set a custom OpenRouter model for the research role
+task-master models --set-research=google/gemini-pro --openrouter
+
+# Run interactive setup to configure models, including custom ones
+task-master models --setup
+```
+
+Configuration is stored in `.taskmasterconfig` in your project root. API keys are still managed via `.env` or MCP configuration. Use `task-master models` without flags to see available built-in models. Use `--setup` for a guided experience.

docs/configuration.md

@@ -0,0 +1,104 @@
+# Configuration
+
+Taskmaster uses two primary methods for configuration:
+
+1.  **`.taskmasterconfig` File (Project Root - Recommended for most settings)**
+
+    - This JSON file stores most configuration settings, including AI model selections, parameters, logging levels, and project defaults.
+    - **Location:** This file is created in the root directory of your project when you run the `task-master models --setup` interactive setup. You typically do this during the initialization sequence. Do not manually edit this file beyond adjusting Temperature and Max Tokens depending on your model.
+    - **Management:** Use the `task-master models --setup` command (or `models` MCP tool) to interactively create and manage this file. You can also set specific models directly using `task-master models --set-<role>=<model_id>`, adding `--ollama` or `--openrouter` flags for custom models. Manual editing is possible but not recommended unless you understand the structure.
+    - **Example Structure:**
+      ```json
+      {
+      	"models": {
+      		"main": {
+      			"provider": "anthropic",
+      			"modelId": "claude-3-7-sonnet-20250219",
+      			"maxTokens": 64000,
+      			"temperature": 0.2,
+      			"baseUrl": "https://api.anthropic.com/v1"
+      		},
+      		"research": {
+      			"provider": "perplexity",
+      			"modelId": "sonar-pro",
+      			"maxTokens": 8700,
+      			"temperature": 0.1,
+      			"baseUrl": "https://api.perplexity.ai/v1"
+      		},
+      		"fallback": {
+      			"provider": "anthropic",
+      			"modelId": "claude-3-5-sonnet",
+      			"maxTokens": 64000,
+      			"temperature": 0.2
+      		}
+      	},
+      	"global": {
+      		"logLevel": "info",
+      		"debug": false,
+      		"defaultSubtasks": 5,
+      		"defaultPriority": "medium",
+      		"projectName": "Your Project Name",
+      		"ollamaBaseUrl": "http://localhost:11434/api",
+      		"azureOpenaiBaseUrl": "https://your-endpoint.openai.azure.com/"
+      	}
+      }
+      ```
+
+2.  **Environment Variables (`.env` file or MCP `env` block - For API Keys Only)**
+    - Used **exclusively** for sensitive API keys and specific endpoint URLs.
+    - **Location:**
+      - For CLI usage: Create a `.env` file in your project root.
+      - For MCP/Cursor usage: Configure keys in the `env` section of your `.cursor/mcp.json` file.
+    - **Required API Keys (Depending on configured providers):**
+      - `ANTHROPIC_API_KEY`: Your Anthropic API key.
+      - `PERPLEXITY_API_KEY`: Your Perplexity API key.
+      - `OPENAI_API_KEY`: Your OpenAI API key.
+      - `GOOGLE_API_KEY`: Your Google API key.
+      - `MISTRAL_API_KEY`: Your Mistral API key.
+      - `AZURE_OPENAI_API_KEY`: Your Azure OpenAI API key (also requires `AZURE_OPENAI_ENDPOINT`).
+      - `OPENROUTER_API_KEY`: Your OpenRouter API key.
+      - `XAI_API_KEY`: Your X-AI API key.
+    - **Optional Endpoint Overrides:**
+      - **Per-role `baseUrl` in `.taskmasterconfig`:** You can add a `baseUrl` property to any model role (`main`, `research`, `fallback`) to override the default API endpoint for that provider. If omitted, the provider's standard endpoint is used.
+      - `AZURE_OPENAI_ENDPOINT`: Required if using Azure OpenAI key (can also be set as `baseUrl` for the Azure model role).
+      - `OLLAMA_BASE_URL`: Override the default Ollama API URL (Default: `http://localhost:11434/api`).
+
+**Important:** Settings like model ID selections (`main`, `research`, `fallback`), `maxTokens`, `temperature`, `logLevel`, `defaultSubtasks`, `defaultPriority`, and `projectName` are **managed in `.taskmasterconfig`**, not environment variables.
+
+## Example `.env` File (for API Keys)
+
+```
+# Required API keys for providers configured in .taskmasterconfig
+ANTHROPIC_API_KEY=sk-ant-api03-your-key-here
+PERPLEXITY_API_KEY=pplx-your-key-here
+# OPENAI_API_KEY=sk-your-key-here
+# GOOGLE_API_KEY=AIzaSy...
+# etc.
+
+# Optional Endpoint Overrides
+# AZURE_OPENAI_ENDPOINT=https://your-azure-endpoint.openai.azure.com/
+# OLLAMA_BASE_URL=http://custom-ollama-host:11434/api
+```
+
+## Troubleshooting
+
+### Configuration Errors
+
+- If Task Master reports errors about missing configuration or cannot find `.taskmasterconfig`, run `task-master models --setup` in your project root to create or repair the file.
+- Ensure API keys are correctly placed in your `.env` file (for CLI) or `.cursor/mcp.json` (for MCP) and are valid for the providers selected in `.taskmasterconfig`.
+
+### If `task-master init` doesn't respond:
+
+Try running it with Node directly:
+
+```bash
+node node_modules/claude-task-master/scripts/init.js
+```
+
+Or clone the repository and run:
+
+```bash
+git clone https://github.com/eyaltoledano/claude-task-master.git
+cd claude-task-master
+node scripts/init.js
+```

docs/contributor-docs/testing-roo-integration.md

@@ -0,0 +1,94 @@
+# Testing Roo Integration
+
+This document provides instructions for testing the Roo integration in the Task Master package.
+
+## Running Tests
+
+To run the tests for the Roo integration:
+
+```bash
+# Run all tests
+npm test
+
+# Run only Roo integration tests
+npm test -- -t "Roo"
+
+# Run specific test file
+npm test -- tests/integration/roo-files-inclusion.test.js
+```
+
+## Manual Testing
+
+To manually verify that the Roo files are properly included in the package:
+
+1. Create a test directory:
+
+   ```bash
+   mkdir test-tm
+   cd test-tm
+   ```
+
+2. Create a package.json file:
+
+   ```bash
+   npm init -y
+   ```
+
+3. Install the task-master-ai package locally:
+
+   ```bash
+   # From the root of the claude-task-master repository
+   cd ..
+   npm pack
+   # This will create a file like task-master-ai-0.12.0.tgz
+
+   # Move back to the test directory
+   cd test-tm
+   npm install ../task-master-ai-0.12.0.tgz
+   ```
+
+4. Initialize a new Task Master project:
+
+   ```bash
+   npx task-master init --yes
+   ```
+
+5. Verify that all Roo files and directories are created:
+
+   ```bash
+   # Check that .roomodes file exists
+   ls -la | grep .roomodes
+
+   # Check that .roo directory exists and contains all mode directories
+   ls -la .roo
+   ls -la .roo/rules
+   ls -la .roo/rules-architect
+   ls -la .roo/rules-ask
+   ls -la .roo/rules-boomerang
+   ls -la .roo/rules-code
+   ls -la .roo/rules-debug
+   ls -la .roo/rules-test
+   ```
+
+## What to Look For
+
+When running the tests or performing manual verification, ensure that:
+
+1. The package includes `.roo/**` and `.roomodes` in the `files` array in package.json
+2. The `prepare-package.js` script verifies the existence of all required Roo files
+3. The `init.js` script creates all necessary .roo directories and copies .roomodes file
+4. All source files for Roo integration exist in `assets/roocode/.roo` and `assets/roocode/.roomodes`
+
+## Compatibility
+
+Ensure that the Roo integration works alongside existing Cursor functionality:
+
+1. Initialize a new project that uses both Cursor and Roo:
+
+   ```bash
+   npx task-master init --yes
+   ```
+
+2. Verify that both `.cursor` and `.roo` directories are created
+3. Verify that both `.windsurfrules` and `.roomodes` files are created
+4. Confirm that existing functionality continues to work as expected

docs/examples.md

@@ -0,0 +1,83 @@
+# Example Cursor AI Interactions
+
+Here are some common interactions with Cursor AI when using Task Master:
+
+## Starting a new project
+
+```
+I've just initialized a new project with Claude Task Master. I have a PRD at scripts/prd.txt.
+Can you help me parse it and set up the initial tasks?
+```
+
+## Working on tasks
+
+```
+What's the next task I should work on? Please consider dependencies and priorities.
+```
+
+## Implementing a specific task
+
+```
+I'd like to implement task 4. Can you help me understand what needs to be done and how to approach it?
+```
+
+## Managing subtasks
+
+```
+I need to regenerate the subtasks for task 3 with a different approach. Can you help me clear and regenerate them?
+```
+
+## Handling changes
+
+```
+We've decided to use MongoDB instead of PostgreSQL. Can you update all future tasks to reflect this change?
+```
+
+## Completing work
+
+```
+I've finished implementing the authentication system described in task 2. All tests are passing.
+Please mark it as complete and tell me what I should work on next.
+```
+
+## Analyzing complexity
+
+```
+Can you analyze the complexity of our tasks to help me understand which ones need to be broken down further?
+```
+
+## Viewing complexity report
+
+```
+Can you show me the complexity report in a more readable format?
+```
+
+### Breaking Down Complex Tasks
+
+```
+Task 5 seems complex. Can you break it down into subtasks?
+```
+
+(Agent runs: `task-master expand --id=5`)
+
+```
+Please break down task 5 using research-backed generation.
+```
+
+(Agent runs: `task-master expand --id=5 --research`)
+
+### Updating Tasks with Research
+
+```
+We need to update task 15 based on the latest React Query v5 changes. Can you research this and update the task?
+```
+
+(Agent runs: `task-master update-task --id=15 --prompt="Update based on React Query v5 changes" --research`)
+
+### Adding Tasks with Research
+
+```
+Please add a new task to implement user profile image uploads using Cloudinary, research the best approach.
+```
+
+(Agent runs: `task-master add-task --prompt="Implement user profile image uploads using Cloudinary" --research`)

docs/licensing.md

@@ -0,0 +1,18 @@
+# Licensing
+
+Task Master is licensed under the MIT License with Commons Clause. This means you can:
+
+## ✅ Allowed:
+
+- Use Task Master for any purpose (personal, commercial, academic)
+- Modify the code
+- Distribute copies
+- Create and sell products built using Task Master
+
+## ❌ Not Allowed:
+
+- Sell Task Master itself
+- Offer Task Master as a hosted service
+- Create competing products based on Task Master
+
+See the [LICENSE](../LICENSE) file for the complete license text.

docs/task-structure.md

@@ -0,0 +1,139 @@
+# Task Structure
+
+Tasks in Task Master follow a specific format designed to provide comprehensive information for both humans and AI assistants.
+
+## Task Fields in tasks.json
+
+Tasks in tasks.json have the following structure:
+
+- `id`: Unique identifier for the task (Example: `1`)
+- `title`: Brief, descriptive title of the task (Example: `"Initialize Repo"`)
+- `description`: Concise description of what the task involves (Example: `"Create a new repository, set up initial structure."`)
+- `status`: Current state of the task (Example: `"pending"`, `"done"`, `"deferred"`)
+- `dependencies`: IDs of tasks that must be completed before this task (Example: `[1, 2]`)
+  - Dependencies are displayed with status indicators (✅ for completed, ⏱️ for pending)
+  - This helps quickly identify which prerequisite tasks are blocking work
+- `priority`: Importance level of the task (Example: `"high"`, `"medium"`, `"low"`)
+- `details`: In-depth implementation instructions (Example: `"Use GitHub client ID/secret, handle callback, set session token."`)
+- `testStrategy`: Verification approach (Example: `"Deploy and call endpoint to confirm 'Hello World' response."`)
+- `subtasks`: List of smaller, more specific tasks that make up the main task (Example: `[{"id": 1, "title": "Configure OAuth", ...}]`)
+
+## Task File Format
+
+Individual task files follow this format:
+
+```
+# Task ID: <id>
+# Title: <title>
+# Status: <status>
+# Dependencies: <comma-separated list of dependency IDs>
+# Priority: <priority>
+# Description: <brief description>
+# Details:
+<detailed implementation notes>
+
+# Test Strategy:
+<verification approach>
+```
+
+## Features in Detail
+
+### Analyzing Task Complexity
+
+The `analyze-complexity` command:
+
+- Analyzes each task using AI to assess its complexity on a scale of 1-10
+- Recommends optimal number of subtasks based on configured DEFAULT_SUBTASKS
+- Generates tailored prompts for expanding each task
+- Creates a comprehensive JSON report with ready-to-use commands
+- Saves the report to scripts/task-complexity-report.json by default
+
+The generated report contains:
+
+- Complexity analysis for each task (scored 1-10)
+- Recommended number of subtasks based on complexity
+- AI-generated expansion prompts customized for each task
+- Ready-to-run expansion commands directly within each task analysis
+
+### Viewing Complexity Report
+
+The `complexity-report` command:
+
+- Displays a formatted, easy-to-read version of the complexity analysis report
+- Shows tasks organized by complexity score (highest to lowest)
+- Provides complexity distribution statistics (low, medium, high)
+- Highlights tasks recommended for expansion based on threshold score
+- Includes ready-to-use expansion commands for each complex task
+- If no report exists, offers to generate one on the spot
+
+### Smart Task Expansion
+
+The `expand` command automatically checks for and uses the complexity report:
+
+When a complexity report exists:
+
+- Tasks are automatically expanded using the recommended subtask count and prompts
+- When expanding all tasks, they're processed in order of complexity (highest first)
+- Research-backed generation is preserved from the complexity analysis
+- You can still override recommendations with explicit command-line options
+
+Example workflow:
+
+```bash
+# Generate the complexity analysis report with research capabilities
+task-master analyze-complexity --research
+
+# Review the report in a readable format
+task-master complexity-report
+
+# Expand tasks using the optimized recommendations
+task-master expand --id=8
+# or expand all tasks
+task-master expand --all
+```
+
+### Finding the Next Task
+
+The `next` command:
+
+- Identifies tasks that are pending/in-progress and have all dependencies satisfied
+- Prioritizes tasks by priority level, dependency count, and task ID
+- Displays comprehensive information about the selected task:
+  - Basic task details (ID, title, priority, dependencies)
+  - Implementation details
+  - Subtasks (if they exist)
+- Provides contextual suggested actions:
+  - Command to mark the task as in-progress
+  - Command to mark the task as done
+  - Commands for working with subtasks
+
+### Viewing Specific Task Details
+
+The `show` command:
+
+- Displays comprehensive details about a specific task or subtask
+- Shows task status, priority, dependencies, and detailed implementation notes
+- For parent tasks, displays all subtasks and their status
+- For subtasks, shows parent task relationship
+- Provides contextual action suggestions based on the task's state
+- Works with both regular tasks and subtasks (using the format taskId.subtaskId)
+
+## Best Practices for AI-Driven Development
+
+1. **Start with a detailed PRD**: The more detailed your PRD, the better the generated tasks will be.
+
+2. **Review generated tasks**: After parsing the PRD, review the tasks to ensure they make sense and have appropriate dependencies.
+
+3. **Analyze task complexity**: Use the complexity analysis feature to identify which tasks should be broken down further.
+
+4. **Follow the dependency chain**: Always respect task dependencies - the Cursor agent will help with this.
+
+5. **Update as you go**: If your implementation diverges from the plan, use the update command to keep future tasks aligned with your current approach.
+
+6. **Break down complex tasks**: Use the expand command to break down complex tasks into manageable subtasks.
+
+7. **Regenerate task files**: After any updates to tasks.json, regenerate the task files to keep them in sync.
+
+8. **Communicate context to the agent**: When asking the Cursor agent to help with a task, provide context about what you're trying to achieve.
+
+9. **Validate dependencies**: Periodically run the validate-dependencies command to check for invalid or circular dependencies.

docs/tutorial.md

@@ -0,0 +1,371 @@
+# Task Master Tutorial
+
+This tutorial will guide you through setting up and using Task Master for AI-driven development.
+
+## Initial Setup
+
+There are two ways to set up Task Master: using MCP (recommended) or via npm installation.
+
+### Option 1: Using MCP (Recommended)
+
+MCP (Model Control Protocol) provides the easiest way to get started with Task Master directly in your editor.
+
+1. **Install the package**
+
+```bash
+npm i -g task-master-ai
+```
+
+2. **Add the MCP config to your IDE/MCP Client** (Cursor is recommended, but it works with other clients):
+
+```json
+{
+	"mcpServers": {
+		"taskmaster-ai": {
+			"command": "npx",
+			"args": ["-y", "--package=task-master-ai", "task-master-ai"],
+			"env": {
+				"ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE",
+				"PERPLEXITY_API_KEY": "YOUR_PERPLEXITY_API_KEY_HERE",
+				"OPENAI_API_KEY": "YOUR_OPENAI_KEY_HERE",
+				"GOOGLE_API_KEY": "YOUR_GOOGLE_KEY_HERE",
+				"MISTRAL_API_KEY": "YOUR_MISTRAL_KEY_HERE",
+				"OPENROUTER_API_KEY": "YOUR_OPENROUTER_KEY_HERE",
+				"XAI_API_KEY": "YOUR_XAI_KEY_HERE",
+				"AZURE_OPENAI_API_KEY": "YOUR_AZURE_KEY_HERE"
+			}
+		}
+	}
+}
+```
+
+**IMPORTANT:** An API key is _required_ for each AI provider you plan on using. Run the `task-master models` command to see your selected models and the status of your API keys across .env and mcp.json
+
+**To use AI commands in CLI** you MUST have API keys in the .env file
+**To use AI commands in MCP** you MUST have API keys in the .mcp.json file (or MCP config equivalent)
+
+We recommend having keys in both places and adding mcp.json to your gitignore so your API keys aren't checked into git.
+
+3. **Enable the MCP** in your editor settings
+
+4. **Prompt the AI** to initialize Task Master:
+
+```
+Can you please initialize taskmaster-ai into my project?
+```
+
+The AI will:
+
+- Create necessary project structure
+- Set up initial configuration files
+- Guide you through the rest of the process
+
+5. Place your PRD document in the `scripts/` directory (e.g., `scripts/prd.txt`)
+
+6. **Use natural language commands** to interact with Task Master:
+
+```
+Can you parse my PRD at scripts/prd.txt?
+What's the next task I should work on?
+Can you help me implement task 3?
+```
+
+### Option 2: Manual Installation
+
+If you prefer to use the command line interface directly:
+
+```bash
+# Install globally
+npm install -g task-master-ai
+
+# OR install locally within your project
+npm install task-master-ai
+```
+
+Initialize a new project:
+
+```bash
+# If installed globally
+task-master init
+
+# If installed locally
+npx task-master init
+```
+
+This will prompt you for project details and set up a new project with the necessary files and structure.
+
+## Common Commands
+
+After setting up Task Master, you can use these commands (either via AI prompts or CLI):
+
+```bash
+# Parse a PRD and generate tasks
+task-master parse-prd your-prd.txt
+
+# List all tasks
+task-master list
+
+# Show the next task to work on
+task-master next
+
+# Generate task files
+task-master generate
+```
+
+## Setting up Cursor AI Integration
+
+Task Master is designed to work seamlessly with [Cursor AI](https://www.cursor.so/), providing a structured workflow for AI-driven development.
+
+### Using Cursor with MCP (Recommended)
+
+If you've already set up Task Master with MCP in Cursor, the integration is automatic. You can simply use natural language to interact with Task Master:
+
+```
+What tasks are available to work on next?
+Can you analyze the complexity of our tasks?
+I'd like to implement task 4. What does it involve?
+```
+
+### Manual Cursor Setup
+
+If you're not using MCP, you can still set up Cursor integration:
+
+1. After initializing your project, open it in Cursor
+2. The `.cursor/rules/dev_workflow.mdc` file is automatically loaded by Cursor, providing the AI with knowledge about the task management system
+3. Place your PRD document in the `scripts/` directory (e.g., `scripts/prd.txt`)
+4. Open Cursor's AI chat and switch to Agent mode
+
+### Alternative MCP Setup in Cursor
+
+You can also set up the MCP server in Cursor settings:
+
+1. Go to Cursor settings
+2. Navigate to the MCP section
+3. Click on "Add New MCP Server"
+4. Configure with the following details:
+   - Name: "Task Master"
+   - Type: "Command"
+   - Command: "npx -y --package=task-master-ai task-master-ai"
+5. Save the settings
+
+Once configured, you can interact with Task Master's task management commands directly through Cursor's interface, providing a more integrated experience.
+
+## Initial Task Generation
+
+In Cursor's AI chat, instruct the agent to generate tasks from your PRD:
+
+```
+Please use the task-master parse-prd command to generate tasks from my PRD. The PRD is located at scripts/prd.txt.
+```
+
+The agent will execute:
+
+```bash
+task-master parse-prd scripts/prd.txt
+```
+
+This will:
+
+- Parse your PRD document
+- Generate a structured `tasks.json` file with tasks, dependencies, priorities, and test strategies
+- The agent will understand this process due to the Cursor rules
+
+### Generate Individual Task Files
+
+Next, ask the agent to generate individual task files:
+
+```
+Please generate individual task files from tasks.json
+```
+
+The agent will execute:
+
+```bash
+task-master generate
+```
+
+This creates individual task files in the `tasks/` directory (e.g., `task_001.txt`, `task_002.txt`), making it easier to reference specific tasks.
+
+## AI-Driven Development Workflow
+
+The Cursor agent is pre-configured (via the rules file) to follow this workflow:
+
+### 1. Task Discovery and Selection
+
+Ask the agent to list available tasks:
+
+```
+What tasks are available to work on next?
+```
+
+The agent will:
+
+- Run `task-master list` to see all tasks
+- Run `task-master next` to determine the next task to work on
+- Analyze dependencies to determine which tasks are ready to be worked on
+- Prioritize tasks based on priority level and ID order
+- Suggest the next task(s) to implement
+
+### 2. Task Implementation
+
+When implementing a task, the agent will:
+
+- Reference the task's details section for implementation specifics
+- Consider dependencies on previous tasks
+- Follow the project's coding standards
+- Create appropriate tests based on the task's testStrategy
+
+You can ask:
+
+```
+Let's implement task 3. What does it involve?
+```
+
+### 3. Task Verification
+
+Before marking a task as complete, verify it according to:
+
+- The task's specified testStrategy
+- Any automated tests in the codebase
+- Manual verification if required
+
+### 4. Task Completion
+
+When a task is completed, tell the agent:
+
+```
+Task 3 is now complete. Please update its status.
+```
+
+The agent will execute:
+
+```bash
+task-master set-status --id=3 --status=done
+```
+
+### 5. Handling Implementation Drift
+
+If during implementation, you discover that:
+
+- The current approach differs significantly from what was planned
+- Future tasks need to be modified due to current implementation choices
+- New dependencies or requirements have emerged
+
+Tell the agent:
+
+```
+We've decided to use MongoDB instead of PostgreSQL. Can you update all future tasks (from ID 4) to reflect this change?
+```
+
+The agent will execute:
+
+```bash
+task-master update --from=4 --prompt="Now we are using MongoDB instead of PostgreSQL."
+
+# OR, if research is needed to find best practices for MongoDB:
+task-master update --from=4 --prompt="Update to use MongoDB, researching best practices" --research
+```
+
+This will rewrite or re-scope subsequent tasks in tasks.json while preserving completed work.
+
+### 6. Breaking Down Complex Tasks
+
+For complex tasks that need more granularity:
+
+```
+Task 5 seems complex. Can you break it down into subtasks?
+```
+
+The agent will execute:
+
+```bash
+task-master expand --id=5 --num=3
+```
+
+You can provide additional context:
+
+```
+Please break down task 5 with a focus on security considerations.
+```
+
+The agent will execute:
+
+```bash
+task-master expand --id=5 --prompt="Focus on security aspects"
+```
+
+You can also expand all pending tasks:
+
+```
+Please break down all pending tasks into subtasks.
+```
+
+The agent will execute:
+
+```bash
+task-master expand --all
+```
+
+For research-backed subtask generation using the configured research model:
+
+```
+Please break down task 5 using research-backed generation.
+```
+
+The agent will execute:
+
+```bash
+task-master expand --id=5 --research
+```
+
+## Example Cursor AI Interactions
+
+### Starting a new project
+
+```
+I've just initialized a new project with Claude Task Master. I have a PRD at scripts/prd.txt.
+Can you help me parse it and set up the initial tasks?
+```
+
+### Working on tasks
+
+```
+What's the next task I should work on? Please consider dependencies and priorities.
+```
+
+### Implementing a specific task
+
+```
+I'd like to implement task 4. Can you help me understand what needs to be done and how to approach it?
+```
+
+### Managing subtasks
+
+```
+I need to regenerate the subtasks for task 3 with a different approach. Can you help me clear and regenerate them?
+```
+
+### Handling changes
+
+```
+We've decided to use MongoDB instead of PostgreSQL. Can you update all future tasks to reflect this change?
+```
+
+### Completing work
+
+```
+I've finished implementing the authentication system described in task 2. All tests are passing.
+Please mark it as complete and tell me what I should work on next.
+```
+
+### Analyzing complexity
+
+```
+Can you analyze the complexity of our tasks to help me understand which ones need to be broken down further?
+```
+
+### Viewing complexity report
+
+```
+Can you show me the complexity report in a more readable format?
+```

entries.json

@@ -1,41 +0,0 @@
-import os
-import json
-
-# Path to Cursor's history folder
-history_path = os.path.expanduser('~/Library/Application Support/Cursor/User/History')
-
-# File to search for
-target_file = 'tasks/tasks.json'
-
-# Function to search through all entries.json files
-def search_entries_for_file(history_path, target_file):
-    matching_folders = []
-    for folder in os.listdir(history_path):
-        folder_path = os.path.join(history_path, folder)
-        if not os.path.isdir(folder_path):
-            continue
-
-        # Look for entries.json
-        entries_file = os.path.join(folder_path, 'entries.json')
-        if not os.path.exists(entries_file):
-            continue
-
-        # Parse entries.json to find the resource key
-        with open(entries_file, 'r') as f:
-            data = json.load(f)
-            resource = data.get('resource', None)
-            if resource and target_file in resource:
-                matching_folders.append(folder_path)
-
-    return matching_folders
-
-# Search for the target file
-matching_folders = search_entries_for_file(history_path, target_file)
-
-# Output the matching folders
-if matching_folders:
-    print(f"Found {target_file} in the following folders:")
-    for folder in matching_folders:
-        print(folder)
-else:
-    print(f"No matches found for {target_file}.")

index.js

@@ -46,22 +46,18 @@ export const initProject = async (options = {}) => {
 };
 
 // Export a function to run init as a CLI command
-export const runInitCLI = async () => {
-  // Using spawn to ensure proper handling of stdio and process exit
-  const child = spawn('node', [resolve(__dirname, './scripts/init.js')], {
-    stdio: 'inherit',
-    cwd: process.cwd()
-  });
-  
-  return new Promise((resolve, reject) => {
-    child.on('close', (code) => {
-      if (code === 0) {
-        resolve();
-      } else {
-        reject(new Error(`Init script exited with code ${code}`));
+export const runInitCLI = async (options = {}) => {
+	try {
+		const init = await import('./scripts/init.js');
+		const result = await init.initializeProject(options);
+		return result;
+	} catch (error) {
+		console.error('Initialization failed:', error.message);
+		if (process.env.DEBUG === 'true') {
+			console.error('Debug stack trace:', error.stack);
+		}
+		throw error; // Re-throw to be handled by the command handler
 	}
-    });
-  });
 };
 
 // Export version information
@@ -79,11 +75,21 @@ if (import.meta.url === `file://${process.argv[1]}`) {
 	program
 		.command('init')
 		.description('Initialize a new project')
-    .action(() => {
-      runInitCLI().catch(err => {
+		.option('-y, --yes', 'Skip prompts and use default values')
+		.option('-n, --name <n>', 'Project name')
+		.option('-d, --description <description>', 'Project description')
+		.option('-v, --version <version>', 'Project version', '0.1.0')
+		.option('-a, --author <author>', 'Author name')
+		.option('--skip-install', 'Skip installing dependencies')
+		.option('--dry-run', 'Show what would be done without making changes')
+		.option('--aliases', 'Add shell aliases (tm, taskmaster)')
+		.action(async (cmdOptions) => {
+			try {
+				await runInitCLI(cmdOptions);
+			} catch (err) {
 				console.error('Init failed:', err.message);
 				process.exit(1);
-      });
+			}
 		});
 
 	program

jest.config.js

@@ -15,11 +15,7 @@ export default {
 	roots: ['<rootDir>/tests'],
 
 	// The glob patterns Jest uses to detect test files
-  testMatch: [
-    '**/__tests__/**/*.js',
-    '**/?(*.)+(spec|test).js',
-    '**/tests/*.test.js'
-  ],
+	testMatch: ['**/__tests__/**/*.js', '**/?(*.)+(spec|test).js'],
 
 	// Transform files
 	transform: {},

mcp-server/server.js

@@ -1,8 +1,8 @@
 #!/usr/bin/env node
 
-import TaskMasterMCPServer from "./src/index.js";
-import dotenv from "dotenv";
-import logger from "./src/logger.js";
+import TaskMasterMCPServer from './src/index.js';
+import dotenv from 'dotenv';
+import logger from './src/logger.js';
 
 // Load environment variables
 dotenv.config();
@@ -14,12 +14,12 @@ async function startServer() {
 	const server = new TaskMasterMCPServer();
 
 	// Handle graceful shutdown
-  process.on("SIGINT", async () => {
+	process.on('SIGINT', async () => {
 		await server.stop();
 		process.exit(0);
 	});
 
-  process.on("SIGTERM", async () => {
+	process.on('SIGTERM', async () => {
 		await server.stop();
 		process.exit(0);
 	});

mcp-server/src/core/__tests__/context-manager.test.js

@@ -14,7 +14,9 @@ describe('ContextManager', () => {
 
 	describe('getContext', () => {
 		it('should create a new context when not in cache', async () => {
-      const context = await contextManager.getContext('test-id', { test: true });
+			const context = await contextManager.getContext('test-id', {
+				test: true
+			});
 			expect(context.id).toBe('test-id');
 			expect(context.metadata.test).toBe(true);
 			expect(contextManager.stats.misses).toBe(1);
@@ -26,7 +28,9 @@ describe('ContextManager', () => {
 			await contextManager.getContext('test-id', { test: true });
 
 			// Second call should hit cache
-      const context = await contextManager.getContext('test-id', { test: true });
+			const context = await contextManager.getContext('test-id', {
+				test: true
+			});
 			expect(context.id).toBe('test-id');
 			expect(context.metadata.test).toBe(true);
 			expect(contextManager.stats.hits).toBe(1);
@@ -38,7 +42,7 @@ describe('ContextManager', () => {
 			await contextManager.getContext('test-id', { test: true });
 
 			// Wait for TTL to expire
-      await new Promise(resolve => setTimeout(resolve, 1100));
+			await new Promise((resolve) => setTimeout(resolve, 1100));
 
 			// Should create new context
 			await contextManager.getContext('test-id', { test: true });
@@ -50,7 +54,9 @@ describe('ContextManager', () => {
 	describe('updateContext', () => {
 		it('should update existing context metadata', async () => {
 			await contextManager.getContext('test-id', { initial: true });
-      const updated = await contextManager.updateContext('test-id', { updated: true });
+			const updated = await contextManager.updateContext('test-id', {
+				updated: true
+			});
 
 			expect(updated.metadata.initial).toBe(true);
 			expect(updated.metadata.updated).toBe(true);

mcp-server/src/core/context-manager.js

@@ -112,7 +112,8 @@ export class ContextManager {
 	 */
 	getCachedData(key) {
 		const cached = this.cache.get(key);
-    if (cached !== undefined) { // Check for undefined specifically, as null/false might be valid cached values
+		if (cached !== undefined) {
+			// Check for undefined specifically, as null/false might be valid cached values
 			this.stats.hits++;
 			return cached;
 		}

mcp-server/src/core/direct-functions/add-dependency.js

@@ -4,26 +4,41 @@
  */
 
 import { addDependency } from '../../../../scripts/modules/dependency-manager.js';
-import { findTasksJsonPath } from '../utils/path-utils.js';
-import { enableSilentMode, disableSilentMode } from '../../../../scripts/modules/utils.js';
+import {
+	enableSilentMode,
+	disableSilentMode
+} from '../../../../scripts/modules/utils.js';
 
 /**
  * Direct function wrapper for addDependency with error handling.
  *
  * @param {Object} args - Command arguments
+ * @param {string} args.tasksJsonPath - Explicit path to the tasks.json file.
  * @param {string|number} args.id - Task ID to add dependency to
  * @param {string|number} args.dependsOn - Task ID that will become a dependency
- * @param {string} [args.file] - Path to the tasks file
- * @param {string} [args.projectRoot] - Project root directory
  * @param {Object} log - Logger object
  * @returns {Promise<Object>} - Result object with success status and data/error information
  */
 export async function addDependencyDirect(args, log) {
+	// Destructure expected args
+	const { tasksJsonPath, id, dependsOn } = args;
 	try {
 		log.info(`Adding dependency with args: ${JSON.stringify(args)}`);
 
+		// Check if tasksJsonPath was provided
+		if (!tasksJsonPath) {
+			log.error('addDependencyDirect called without tasksJsonPath');
+			return {
+				success: false,
+				error: {
+					code: 'MISSING_ARGUMENT',
+					message: 'tasksJsonPath is required'
+				}
+			};
+		}
+
 		// Validate required parameters
-    if (!args.id) {
+		if (!id) {
 			return {
 				success: false,
 				error: {
@@ -33,7 +48,7 @@ export async function addDependencyDirect(args, log) {
 			};
 		}
 
-    if (!args.dependsOn) {
+		if (!dependsOn) {
 			return {
 				success: false,
 				error: {
@@ -43,19 +58,25 @@ export async function addDependencyDirect(args, log) {
 			};
 		}
 
-    // Find the tasks.json path
-    const tasksPath = findTasksJsonPath(args, log);
+		// Use provided path
+		const tasksPath = tasksJsonPath;
 
 		// Format IDs for the core function
-    const taskId = args.id.includes && args.id.includes('.') ? args.id : parseInt(args.id, 10);
-    const dependencyId = args.dependsOn.includes && args.dependsOn.includes('.') ? args.dependsOn : parseInt(args.dependsOn, 10);
+		const taskId =
+			id && id.includes && id.includes('.') ? id : parseInt(id, 10);
+		const dependencyId =
+			dependsOn && dependsOn.includes && dependsOn.includes('.')
+				? dependsOn
+				: parseInt(dependsOn, 10);
 
-    log.info(`Adding dependency: task ${taskId} will depend on ${dependencyId}`);
+		log.info(
+			`Adding dependency: task ${taskId} will depend on ${dependencyId}`
+		);
 
 		// Enable silent mode to prevent console logs from interfering with JSON response
 		enableSilentMode();
 
-    // Call the core function
+		// Call the core function using the provided path
 		await addDependency(tasksPath, taskId, dependencyId);
 
 		// Restore normal logging

mcp-server/src/core/direct-functions/add-subtask.js

@@ -3,12 +3,15 @@
  */
 
 import { addSubtask } from '../../../../scripts/modules/task-manager.js';
-import { findTasksJsonPath } from '../utils/path-utils.js';
-import { enableSilentMode, disableSilentMode } from '../../../../scripts/modules/utils.js';
+import {
+	enableSilentMode,
+	disableSilentMode
+} from '../../../../scripts/modules/utils.js';
 
 /**
  * Add a subtask to an existing task
  * @param {Object} args - Function arguments
+ * @param {string} args.tasksJsonPath - Explicit path to the tasks.json file.
  * @param {string} args.id - Parent task ID
  * @param {string} [args.taskId] - Existing task ID to convert to subtask (optional)
  * @param {string} [args.title] - Title for new subtask (when creating a new subtask)
@@ -16,17 +19,39 @@ import { enableSilentMode, disableSilentMode } from '../../../../scripts/modules
  * @param {string} [args.details] - Implementation details for new subtask
  * @param {string} [args.status] - Status for new subtask (default: 'pending')
  * @param {string} [args.dependencies] - Comma-separated list of dependency IDs
- * @param {string} [args.file] - Path to the tasks file
  * @param {boolean} [args.skipGenerate] - Skip regenerating task files
- * @param {string} [args.projectRoot] - Project root directory
  * @param {Object} log - Logger object
  * @returns {Promise<{success: boolean, data?: Object, error?: string}>}
  */
 export async function addSubtaskDirect(args, log) {
+	// Destructure expected args
+	const {
+		tasksJsonPath,
+		id,
+		taskId,
+		title,
+		description,
+		details,
+		status,
+		dependencies: dependenciesStr,
+		skipGenerate
+	} = args;
 	try {
 		log.info(`Adding subtask with args: ${JSON.stringify(args)}`);
 
-    if (!args.id) {
+		// Check if tasksJsonPath was provided
+		if (!tasksJsonPath) {
+			log.error('addSubtaskDirect called without tasksJsonPath');
+			return {
+				success: false,
+				error: {
+					code: 'MISSING_ARGUMENT',
+					message: 'tasksJsonPath is required'
+				}
+			};
+		}
+
+		if (!id) {
 			return {
 				success: false,
 				error: {
@@ -37,7 +62,7 @@ export async function addSubtaskDirect(args, log) {
 		}
 
 		// Either taskId or title must be provided
-    if (!args.taskId && !args.title) {
+		if (!taskId && !title) {
 			return {
 				success: false,
 				error: {
@@ -47,26 +72,26 @@ export async function addSubtaskDirect(args, log) {
 			};
 		}
 
-    // Find the tasks.json path
-    const tasksPath = findTasksJsonPath(args, log);
+		// Use provided path
+		const tasksPath = tasksJsonPath;
 
 		// Parse dependencies if provided
 		let dependencies = [];
-    if (args.dependencies) {
-      dependencies = args.dependencies.split(',').map(id => {
+		if (dependenciesStr) {
+			dependencies = dependenciesStr.split(',').map((depId) => {
 				// Handle both regular IDs and dot notation
-        return id.includes('.') ? id.trim() : parseInt(id.trim(), 10);
+				return depId.includes('.') ? depId.trim() : parseInt(depId.trim(), 10);
 			});
 		}
 
 		// Convert existingTaskId to a number if provided
-    const existingTaskId = args.taskId ? parseInt(args.taskId, 10) : null;
+		const existingTaskId = taskId ? parseInt(taskId, 10) : null;
 
 		// Convert parent ID to a number
-    const parentId = parseInt(args.id, 10);
+		const parentId = parseInt(id, 10);
 
 		// Determine if we should generate files
-    const generateFiles = !args.skipGenerate;
+		const generateFiles = !skipGenerate;
 
 		// Enable silent mode to prevent console logs from interfering with JSON response
 		enableSilentMode();
@@ -74,7 +99,13 @@ export async function addSubtaskDirect(args, log) {
 		// Case 1: Convert existing task to subtask
 		if (existingTaskId) {
 			log.info(`Converting task ${existingTaskId} to a subtask of ${parentId}`);
-      const result = await addSubtask(tasksPath, parentId, existingTaskId, null, generateFiles);
+			const result = await addSubtask(
+				tasksPath,
+				parentId,
+				existingTaskId,
+				null,
+				generateFiles
+			);
 
 			// Restore normal logging
 			disableSilentMode();
@@ -92,14 +123,20 @@ export async function addSubtaskDirect(args, log) {
 			log.info(`Creating new subtask for parent task ${parentId}`);
 
 			const newSubtaskData = {
-        title: args.title,
-        description: args.description || '',
-        details: args.details || '',
-        status: args.status || 'pending',
+				title: title,
+				description: description || '',
+				details: details || '',
+				status: status || 'pending',
 				dependencies: dependencies
 			};
 
-      const result = await addSubtask(tasksPath, parentId, null, newSubtaskData, generateFiles);
+			const result = await addSubtask(
+				tasksPath,
+				parentId,
+				null,
+				newSubtaskData,
+				generateFiles
+			);
 
 			// Restore normal logging
 			disableSilentMode();

mcp-server/src/core/direct-functions/add-task.js

@@ -4,151 +4,157 @@
  */
 
 import { addTask } from '../../../../scripts/modules/task-manager.js';
-import { findTasksJsonPath } from '../utils/path-utils.js';
-import { enableSilentMode, disableSilentMode } from '../../../../scripts/modules/utils.js';
-import { getAnthropicClientForMCP, getModelConfig } from '../utils/ai-client-utils.js';
-import { _buildAddTaskPrompt, parseTaskJsonResponse, _handleAnthropicStream } from '../../../../scripts/modules/ai-services.js';
+import {
+	enableSilentMode,
+	disableSilentMode
+} from '../../../../scripts/modules/utils.js';
+import { createLogWrapper } from '../../tools/utils.js';
 
 /**
  * Direct function wrapper for adding a new task with error handling.
  *
  * @param {Object} args - Command arguments
- * @param {string} args.prompt - Description of the task to add
- * @param {Array<number>} [args.dependencies=[]] - Task dependencies as array of IDs
+ * @param {string} [args.prompt] - Description of the task to add (required if not using manual fields)
+ * @param {string} [args.title] - Task title (for manual task creation)
+ * @param {string} [args.description] - Task description (for manual task creation)
+ * @param {string} [args.details] - Implementation details (for manual task creation)
+ * @param {string} [args.testStrategy] - Test strategy (for manual task creation)
+ * @param {string} [args.dependencies] - Comma-separated list of task IDs this task depends on
  * @param {string} [args.priority='medium'] - Task priority (high, medium, low)
- * @param {string} [args.file] - Path to the tasks file
- * @param {string} [args.projectRoot] - Project root directory
- * @param {boolean} [args.research] - Whether to use research capabilities for task creation
+ * @param {string} [args.tasksJsonPath] - Path to the tasks.json file (resolved by tool)
+ * @param {boolean} [args.research=false] - Whether to use research capabilities for task creation
+ * @param {string} [args.projectRoot] - Project root path
  * @param {Object} log - Logger object
- * @param {Object} context - Additional context (reportProgress, session)
+ * @param {Object} context - Additional context (session)
  * @returns {Promise<Object>} - Result object { success: boolean, data?: any, error?: { code: string, message: string } }
  */
 export async function addTaskDirect(args, log, context = {}) {
-  try {
+	// Destructure expected args (including research and projectRoot)
+	const {
+		tasksJsonPath,
+		prompt,
+		dependencies,
+		priority,
+		research,
+		projectRoot
+	} = args;
+	const { session } = context; // Destructure session from context
+
 	// Enable silent mode to prevent console logs from interfering with JSON response
 	enableSilentMode();
 
-    // Find the tasks.json path
-    const tasksPath = findTasksJsonPath(args, log);
+	// Create logger wrapper using the utility
+	const mcpLog = createLogWrapper(log);
+
+	try {
+		// Check if tasksJsonPath was provided
+		if (!tasksJsonPath) {
+			log.error('addTaskDirect called without tasksJsonPath');
+			disableSilentMode(); // Disable before returning
+			return {
+				success: false,
+				error: {
+					code: 'MISSING_ARGUMENT',
+					message: 'tasksJsonPath is required'
+				}
+			};
+		}
+
+		// Use provided path
+		const tasksPath = tasksJsonPath;
+
+		// Check if this is manual task creation or AI-driven task creation
+		const isManualCreation = args.title && args.description;
 
 		// Check required parameters
-    if (!args.prompt) {
-      log.error('Missing required parameter: prompt');
+		if (!args.prompt && !isManualCreation) {
+			log.error(
+				'Missing required parameters: either prompt or title+description must be provided'
+			);
 			disableSilentMode();
 			return {
 				success: false,
 				error: {
 					code: 'MISSING_PARAMETER',
-          message: 'The prompt parameter is required for adding a task'
+					message:
+						'Either the prompt parameter or both title and description parameters are required for adding a task'
 				}
 			};
 		}
 
 		// Extract and prepare parameters
-    const prompt = args.prompt;
-    const dependencies = Array.isArray(args.dependencies) 
-      ? args.dependencies 
-      : (args.dependencies ? String(args.dependencies).split(',').map(id => parseInt(id.trim(), 10)) : []);
-    const priority = args.priority || 'medium';
+		const taskDependencies = Array.isArray(dependencies)
+			? dependencies // Already an array if passed directly
+			: dependencies // Check if dependencies exist and are a string
+				? String(dependencies)
+						.split(',')
+						.map((id) => parseInt(id.trim(), 10)) // Split, trim, and parse
+				: []; // Default to empty array if null/undefined
+		const taskPriority = priority || 'medium'; // Default priority
 
-    log.info(`Adding new task with prompt: "${prompt}", dependencies: [${dependencies.join(', ')}], priority: ${priority}`);
+		let manualTaskData = null;
+		let newTaskId;
+		let telemetryData;
 
-    // Extract context parameters for advanced functionality
-    // Commenting out reportProgress extraction
-    // const { reportProgress, session } = context; 
-    const { session } = context; // Keep session
-
-    // Initialize AI client with session environment
-    let localAnthropic;
-    try {
-      localAnthropic = getAnthropicClientForMCP(session, log);
-    } catch (error) {
-      log.error(`Failed to initialize Anthropic client: ${error.message}`);
-      disableSilentMode();
-      return {
-        success: false,
-        error: {
-          code: 'AI_CLIENT_ERROR',
-          message: `Cannot initialize AI client: ${error.message}`
-        }
+		if (isManualCreation) {
+			// Create manual task data object
+			manualTaskData = {
+				title: args.title,
+				description: args.description,
+				details: args.details || '',
+				testStrategy: args.testStrategy || ''
 			};
-    }
 
-    // Get model configuration from session
-    const modelConfig = getModelConfig(session);
-
-    // Read existing tasks to provide context
-    let tasksData;
-    try {
-      const fs = await import('fs');
-      tasksData = JSON.parse(fs.readFileSync(tasksPath, 'utf8'));
-    } catch (error) {
-      log.warn(`Could not read existing tasks for context: ${error.message}`);
-      tasksData = { tasks: [] };
-    }
-
-    // Build prompts for AI
-    const { systemPrompt, userPrompt } = _buildAddTaskPrompt(prompt, tasksData.tasks);
-
-    // Make the AI call using the streaming helper
-    let responseText;
-    try {
-      responseText = await _handleAnthropicStream(
-        localAnthropic,
-        {
-          model: modelConfig.model,
-          max_tokens: modelConfig.maxTokens,
-          temperature: modelConfig.temperature,
-          messages: [{ role: "user", content: userPrompt }],
-          system: systemPrompt
-        },
-        {
-          // reportProgress: context.reportProgress, // Commented out to prevent Cursor stroking out 
-          mcpLog: log
-        }
+			log.info(
+				`Adding new task manually with title: "${args.title}", dependencies: [${taskDependencies.join(', ')}], priority: ${priority}`
 			);
-    } catch (error) {
-      log.error(`AI processing failed: ${error.message}`);
-      disableSilentMode();
-      return {
-        success: false,
-        error: {
-          code: 'AI_PROCESSING_ERROR',
-          message: `Failed to generate task with AI: ${error.message}`
-        }
-      };
-    }
 
-    // Parse the AI response
-    let taskDataFromAI;
-    try {
-      taskDataFromAI = parseTaskJsonResponse(responseText);
-    } catch (error) {
-      log.error(`Failed to parse AI response: ${error.message}`);
-      disableSilentMode();
-      return {
-        success: false,
-        error: {
-          code: 'RESPONSE_PARSING_ERROR',
-          message: `Failed to parse AI response: ${error.message}`
-        }
-      };
-    }
-    
-    // Call the addTask function with 'json' outputFormat to prevent console output when called via MCP
-    const newTaskId = await addTask(
+			// Call the addTask function with manual task data
+			const result = await addTask(
 				tasksPath,
-      prompt, 
-      dependencies, 
-      priority, 
+				null, // prompt is null for manual creation
+				taskDependencies,
+				taskPriority,
 				{
-        // reportProgress, // Commented out
-        mcpLog: log, 
 					session,
-        taskDataFromAI // Pass the parsed AI result
+					mcpLog,
+					projectRoot,
+					commandName: 'add-task',
+					outputType: 'mcp'
 				},
-      'json'
+				'json', // outputFormat
+				manualTaskData, // Pass the manual task data
+				false, // research flag is false for manual creation
+				projectRoot // Pass projectRoot
 			);
+			newTaskId = result.newTaskId;
+			telemetryData = result.telemetryData;
+		} else {
+			// AI-driven task creation
+			log.info(
+				`Adding new task with prompt: "${prompt}", dependencies: [${taskDependencies.join(', ')}], priority: ${taskPriority}, research: ${research}`
+			);
+
+			// Call the addTask function, passing the research flag
+			const result = await addTask(
+				tasksPath,
+				prompt, // Use the prompt for AI creation
+				taskDependencies,
+				taskPriority,
+				{
+					session,
+					mcpLog,
+					projectRoot,
+					commandName: 'add-task',
+					outputType: 'mcp'
+				},
+				'json', // outputFormat
+				null, // manualTaskData is null for AI creation
+				research // Pass the research flag
+			);
+			newTaskId = result.newTaskId;
+			telemetryData = result.telemetryData;
+		}
 
 		// Restore normal logging
 		disableSilentMode();
@@ -157,7 +163,8 @@ export async function addTaskDirect(args, log, context = {}) {
 			success: true,
 			data: {
 				taskId: newTaskId,
-        message: `Successfully added new task #${newTaskId}`
+				message: `Successfully added new task #${newTaskId}`,
+				telemetryData: telemetryData
 			}
 		};
 	} catch (error) {
@@ -165,10 +172,11 @@ export async function addTaskDirect(args, log, context = {}) {
 		disableSilentMode();
 
 		log.error(`Error in addTaskDirect: ${error.message}`);
+		// Add specific error code checks if needed
 		return {
 			success: false,
 			error: {
-        code: 'ADD_TASK_ERROR',
+				code: error.code || 'ADD_TASK_ERROR', // Use error code if available
 				message: error.message
 			}
 		};

mcp-server/src/core/direct-functions/analyze-task-complexity.js

@@ -2,118 +2,164 @@
  * Direct function wrapper for analyzeTaskComplexity
  */
 
-import { analyzeTaskComplexity } from '../../../../scripts/modules/task-manager.js';
-import { findTasksJsonPath } from '../utils/path-utils.js';
-import { enableSilentMode, disableSilentMode, isSilentMode, readJSON } from '../../../../scripts/modules/utils.js';
+import analyzeTaskComplexity from '../../../../scripts/modules/task-manager/analyze-task-complexity.js';
+import {
+	enableSilentMode,
+	disableSilentMode,
+	isSilentMode
+} from '../../../../scripts/modules/utils.js';
 import fs from 'fs';
-import path from 'path';
+import { createLogWrapper } from '../../tools/utils.js'; // Import the new utility
 
 /**
  * Analyze task complexity and generate recommendations
  * @param {Object} args - Function arguments
- * @param {string} [args.file] - Path to the tasks file
- * @param {string} [args.output] - Output file path for the report
- * @param {string} [args.model] - LLM model to use for analysis
+ * @param {string} args.tasksJsonPath - Explicit path to the tasks.json file.
+ * @param {string} args.outputPath - Explicit absolute path to save the report.
  * @param {string|number} [args.threshold] - Minimum complexity score to recommend expansion (1-10)
  * @param {boolean} [args.research] - Use Perplexity AI for research-backed complexity analysis
- * @param {string} [args.projectRoot] - Project root directory
+ * @param {string} [args.projectRoot] - Project root path.
  * @param {Object} log - Logger object
  * @param {Object} [context={}] - Context object containing session data
+ * @param {Object} [context.session] - MCP session object
  * @returns {Promise<{success: boolean, data?: Object, error?: {code: string, message: string}}>}
  */
 export async function analyzeTaskComplexityDirect(args, log, context = {}) {
-  const { session } = context; // Only extract session, not reportProgress
+	const { session } = context;
+	const { tasksJsonPath, outputPath, threshold, research, projectRoot } = args;
 
+	const logWrapper = createLogWrapper(log);
+
+	// --- Initial Checks (remain the same) ---
 	try {
 		log.info(`Analyzing task complexity with args: ${JSON.stringify(args)}`);
 
-    // Find the tasks.json path
-    const tasksPath = findTasksJsonPath(args, log);
-    
-    // Determine output path
-    let outputPath = args.output || 'scripts/task-complexity-report.json';
-    if (!path.isAbsolute(outputPath) && args.projectRoot) {
-      outputPath = path.join(args.projectRoot, outputPath);
-    }
-    
-    log.info(`Analyzing task complexity from: ${tasksPath}`);
-    log.info(`Output report will be saved to: ${outputPath}`);
-    
-    if (args.research) {
-      log.info('Using Perplexity AI for research-backed complexity analysis');
-    }
-    
-    // Create options object for analyzeTaskComplexity
-    const options = {
-      file: tasksPath,
-      output: outputPath,
-      model: args.model,
-      threshold: args.threshold,
-      research: args.research === true
-    };
-    
-    // Enable silent mode to prevent console logs from interfering with JSON response
-    const wasSilent = isSilentMode();
-    if (!wasSilent) {
-      enableSilentMode();
-    }
-    
-    // Create a logWrapper that matches the expected mcpLog interface as specified in utilities.mdc
-    const logWrapper = {
-      info: (message, ...args) => log.info(message, ...args),
-      warn: (message, ...args) => log.warn(message, ...args),
-      error: (message, ...args) => log.error(message, ...args),
-      debug: (message, ...args) => log.debug && log.debug(message, ...args),
-      success: (message, ...args) => log.info(message, ...args) // Map success to info
-    };
-    
-    try {
-      // Call the core function with session and logWrapper as mcpLog
-      await analyzeTaskComplexity(options, {
-        session,
-        mcpLog: logWrapper // Use the wrapper instead of passing log directly
-      });
-    } catch (error) {
-      log.error(`Error in analyzeTaskComplexity: ${error.message}`);
+		if (!tasksJsonPath) {
+			log.error('analyzeTaskComplexityDirect called without tasksJsonPath');
 			return {
 				success: false,
 				error: {
-          code: 'ANALYZE_ERROR',
-          message: `Error running complexity analysis: ${error.message}`
+					code: 'MISSING_ARGUMENT',
+					message: 'tasksJsonPath is required'
+				}
+			};
+		}
+		if (!outputPath) {
+			log.error('analyzeTaskComplexityDirect called without outputPath');
+			return {
+				success: false,
+				error: { code: 'MISSING_ARGUMENT', message: 'outputPath is required' }
+			};
+		}
+
+		const tasksPath = tasksJsonPath;
+		const resolvedOutputPath = outputPath;
+
+		log.info(`Analyzing task complexity from: ${tasksPath}`);
+		log.info(`Output report will be saved to: ${resolvedOutputPath}`);
+
+		if (research) {
+			log.info('Using research role for complexity analysis');
+		}
+
+		// Prepare options for the core function - REMOVED mcpLog and session here
+		const coreOptions = {
+			file: tasksJsonPath,
+			output: outputPath,
+			threshold: threshold,
+			research: research === true, // Ensure boolean
+			projectRoot: projectRoot // Pass projectRoot here
+		};
+		// --- End Initial Checks ---
+
+		// --- Silent Mode and Logger Wrapper ---
+		const wasSilent = isSilentMode();
+		if (!wasSilent) {
+			enableSilentMode(); // Still enable silent mode as a backup
+		}
+
+		let report;
+		let coreResult;
+
+		try {
+			// --- Call Core Function (Pass context separately) ---
+			// Pass coreOptions as the first argument
+			// Pass context object { session, mcpLog } as the second argument
+			coreResult = await analyzeTaskComplexity(coreOptions, {
+				session,
+				mcpLog: logWrapper,
+				commandName: 'analyze-complexity',
+				outputType: 'mcp'
+			});
+			report = coreResult.report;
+		} catch (error) {
+			log.error(
+				`Error in analyzeTaskComplexity core function: ${error.message}`
+			);
+			// Restore logging if we changed it
+			if (!wasSilent && isSilentMode()) {
+				disableSilentMode();
+			}
+			return {
+				success: false,
+				error: {
+					code: 'ANALYZE_CORE_ERROR',
+					message: `Error running core complexity analysis: ${error.message}`
 				}
 			};
 		} finally {
-      // Always restore normal logging in finally block, but only if we enabled it
-      if (!wasSilent) {
+			// Always restore normal logging in finally block if we enabled silent mode
+			if (!wasSilent && isSilentMode()) {
 				disableSilentMode();
 			}
 		}
 
-    // Verify the report file was created
-    if (!fs.existsSync(outputPath)) {
+		// --- Result Handling (remains largely the same) ---
+		// Verify the report file was created (core function writes it)
+		if (!fs.existsSync(resolvedOutputPath)) {
 			return {
 				success: false,
 				error: {
-          code: 'ANALYZE_ERROR',
-          message: 'Analysis completed but no report file was created'
+					code: 'ANALYZE_REPORT_MISSING', // Specific code
+					message:
+						'Analysis completed but no report file was created at the expected path.'
+				}
+			};
+		}
+
+		if (
+			!coreResult ||
+			!coreResult.report ||
+			typeof coreResult.report !== 'object'
+		) {
+			log.error(
+				'Core analysis function returned an invalid or undefined response.'
+			);
+			return {
+				success: false,
+				error: {
+					code: 'INVALID_CORE_RESPONSE',
+					message: 'Core analysis function returned an invalid response.'
 				}
 			};
 		}
 
-    // Read the report file
-    let report;
 		try {
-      report = JSON.parse(fs.readFileSync(outputPath, 'utf8'));
+			// Ensure complexityAnalysis exists and is an array
+			const analysisArray = Array.isArray(coreResult.report.complexityAnalysis)
+				? coreResult.report.complexityAnalysis
+				: [];
 
-      // Important: Handle different report formats
-      // The core function might return an array or an object with a complexityAnalysis property
-      const analysisArray = Array.isArray(report) ? report : 
-                           (report.complexityAnalysis || []);
-      
-      // Count tasks by complexity
-      const highComplexityTasks = analysisArray.filter(t => t.complexityScore >= 8).length;
-      const mediumComplexityTasks = analysisArray.filter(t => t.complexityScore >= 5 && t.complexityScore < 8).length;
-      const lowComplexityTasks = analysisArray.filter(t => t.complexityScore < 5).length;
+			// Count tasks by complexity (remains the same)
+			const highComplexityTasks = analysisArray.filter(
+				(t) => t.complexityScore >= 8
+			).length;
+			const mediumComplexityTasks = analysisArray.filter(
+				(t) => t.complexityScore >= 5 && t.complexityScore < 8
+			).length;
+			const lowComplexityTasks = analysisArray.filter(
+				(t) => t.complexityScore < 5
+			).length;
 
 			return {
 				success: true,
@@ -125,30 +171,34 @@ export async function analyzeTaskComplexityDirect(args, log, context = {}) {
 						highComplexityTasks,
 						mediumComplexityTasks,
 						lowComplexityTasks
-          }
+					},
+					fullReport: coreResult.report,
+					telemetryData: coreResult.telemetryData
 				}
 			};
 		} catch (parseError) {
-      log.error(`Error parsing report file: ${parseError.message}`);
+			// Should not happen if core function returns object, but good safety check
+			log.error(`Internal error processing report data: ${parseError.message}`);
 			return {
 				success: false,
 				error: {
-          code: 'REPORT_PARSE_ERROR',
-          message: `Error parsing complexity report: ${parseError.message}`
+					code: 'REPORT_PROCESS_ERROR',
+					message: `Internal error processing complexity report: ${parseError.message}`
 				}
 			};
 		}
+		// --- End Result Handling ---
 	} catch (error) {
-    // Make sure to restore normal logging even if there's an error
+		// Catch errors from initial checks or path resolution
+		// Make sure to restore normal logging if silent mode was enabled
 		if (isSilentMode()) {
 			disableSilentMode();
 		}
-    
-    log.error(`Error in analyzeTaskComplexityDirect: ${error.message}`);
+		log.error(`Error in analyzeTaskComplexityDirect setup: ${error.message}`);
 		return {
 			success: false,
 			error: {
-        code: 'CORE_FUNCTION_ERROR',
+				code: 'DIRECT_FUNCTION_SETUP_ERROR',
 				message: error.message
 			}
 		};

mcp-server/src/core/direct-functions/clear-subtasks.js

@@ -3,37 +3,53 @@
  */
 
 import { clearSubtasks } from '../../../../scripts/modules/task-manager.js';
-import { findTasksJsonPath } from '../utils/path-utils.js';
-import { enableSilentMode, disableSilentMode } from '../../../../scripts/modules/utils.js';
+import {
+	enableSilentMode,
+	disableSilentMode
+} from '../../../../scripts/modules/utils.js';
 import fs from 'fs';
 
 /**
  * Clear subtasks from specified tasks
  * @param {Object} args - Function arguments
+ * @param {string} args.tasksJsonPath - Explicit path to the tasks.json file.
  * @param {string} [args.id] - Task IDs (comma-separated) to clear subtasks from
  * @param {boolean} [args.all] - Clear subtasks from all tasks
- * @param {string} [args.file] - Path to the tasks file
- * @param {string} [args.projectRoot] - Project root directory
  * @param {Object} log - Logger object
  * @returns {Promise<{success: boolean, data?: Object, error?: {code: string, message: string}}>}
  */
 export async function clearSubtasksDirect(args, log) {
+	// Destructure expected args
+	const { tasksJsonPath, id, all } = args;
 	try {
 		log.info(`Clearing subtasks with args: ${JSON.stringify(args)}`);
 
-    // Either id or all must be provided
-    if (!args.id && !args.all) {
+		// Check if tasksJsonPath was provided
+		if (!tasksJsonPath) {
+			log.error('clearSubtasksDirect called without tasksJsonPath');
 			return {
 				success: false,
 				error: {
-          code: 'INPUT_VALIDATION_ERROR',
-          message: 'Either task IDs with id parameter or all parameter must be provided'
+					code: 'MISSING_ARGUMENT',
+					message: 'tasksJsonPath is required'
 				}
 			};
 		}
 
-    // Find the tasks.json path
-    const tasksPath = findTasksJsonPath(args, log);
+		// Either id or all must be provided
+		if (!id && !all) {
+			return {
+				success: false,
+				error: {
+					code: 'INPUT_VALIDATION_ERROR',
+					message:
+						'Either task IDs with id parameter or all parameter must be provided'
+				}
+			};
+		}
+
+		// Use provided path
+		const tasksPath = tasksJsonPath;
 
 		// Check if tasks.json exists
 		if (!fs.existsSync(tasksPath)) {
@@ -49,7 +65,7 @@ export async function clearSubtasksDirect(args, log) {
 		let taskIds;
 
 		// If all is specified, get all task IDs
-    if (args.all) {
+		if (all) {
 			log.info('Clearing subtasks from all tasks');
 			const data = JSON.parse(fs.readFileSync(tasksPath, 'utf8'));
 			if (!data || !data.tasks || data.tasks.length === 0) {
@@ -61,10 +77,10 @@ export async function clearSubtasksDirect(args, log) {
 					}
 				};
 			}
-      taskIds = data.tasks.map(t => t.id).join(',');
+			taskIds = data.tasks.map((t) => t.id).join(',');
 		} else {
 			// Use the provided task IDs
-      taskIds = args.id;
+			taskIds = id;
 		}
 
 		log.info(`Clearing subtasks from tasks: ${taskIds}`);
@@ -80,12 +96,12 @@ export async function clearSubtasksDirect(args, log) {
 
 		// Read the updated data to provide a summary
 		const updatedData = JSON.parse(fs.readFileSync(tasksPath, 'utf8'));
-    const taskIdArray = taskIds.split(',').map(id => parseInt(id.trim(), 10));
+		const taskIdArray = taskIds.split(',').map((id) => parseInt(id.trim(), 10));
 
 		// Build a summary of what was done
 		const clearedTasksCount = taskIdArray.length;
-    const taskSummary = taskIdArray.map(id => {
-      const task = updatedData.tasks.find(t => t.id === id);
+		const taskSummary = taskIdArray.map((id) => {
+			const task = updatedData.tasks.find((t) => t.id === id);
 			return task ? { id, title: task.title } : { id, title: 'Task not found' };
 		});
 

mcp-server/src/core/direct-functions/complexity-report.js

@@ -3,34 +3,37 @@
  * Direct function implementation for displaying complexity analysis report
  */
 
-import { readComplexityReport, enableSilentMode, disableSilentMode } from '../../../../scripts/modules/utils.js';
-import { findTasksJsonPath } from '../utils/path-utils.js';
-import { getCachedOrExecute } from '../../tools/utils.js';
-import path from 'path';
+import {
+	readComplexityReport,
+	enableSilentMode,
+	disableSilentMode
+} from '../../../../scripts/modules/utils.js';
 
 /**
  * Direct function wrapper for displaying the complexity report with error handling and caching.
  *
- * @param {Object} args - Command arguments containing file path option
+ * @param {Object} args - Command arguments containing reportPath.
+ * @param {string} args.reportPath - Explicit path to the complexity report file.
  * @param {Object} log - Logger object
  * @returns {Promise<Object>} - Result object with success status and data/error information
  */
 export async function complexityReportDirect(args, log) {
+	// Destructure expected args
+	const { reportPath } = args;
 	try {
 		log.info(`Getting complexity report with args: ${JSON.stringify(args)}`);
 
-    // Get tasks file path to determine project root for the default report location
-    let tasksPath;
-    try {
-      tasksPath = findTasksJsonPath(args, log);
-    } catch (error) {
-      log.warn(`Tasks file not found, using current directory: ${error.message}`);
-      // Continue with default or specified report path
+		// Check if reportPath was provided
+		if (!reportPath) {
+			log.error('complexityReportDirect called without reportPath');
+			return {
+				success: false,
+				error: { code: 'MISSING_ARGUMENT', message: 'reportPath is required' },
+				fromCache: false
+			};
 		}
 
-    // Get report file path from args or use default
-    const reportPath = args.file || path.join(process.cwd(), 'scripts', 'task-complexity-report.json');
-    
+		// Use the provided report path
 		log.info(`Looking for complexity report at: ${reportPath}`);
 
 		// Generate cache key based on report path
@@ -82,26 +85,20 @@ export async function complexityReportDirect(args, log) {
 
 		// Use the caching utility
 		try {
-      const result = await getCachedOrExecute({
-        cacheKey,
-        actionFn: coreActionFn,
-        log
-      });
-      log.info(`complexityReportDirect completed. From cache: ${result.fromCache}`);
-      return result; // Returns { success, data/error, fromCache }
+			const result = await coreActionFn();
+			log.info('complexityReportDirect completed');
+			return result;
 		} catch (error) {
-      // Catch unexpected errors from getCachedOrExecute itself
 			// Ensure silent mode is disabled
 			disableSilentMode();
 
-      log.error(`Unexpected error during getCachedOrExecute for complexityReport: ${error.message}`);
+			log.error(`Unexpected error during complexityReport: ${error.message}`);
 			return {
 				success: false,
 				error: {
 					code: 'UNEXPECTED_ERROR',
 					message: error.message
-        }, 
-        fromCache: false 
+				}
 			};
 		}
 	} catch (error) {

mcp-server/src/core/direct-functions/expand-all-tasks.js

@@ -3,118 +3,94 @@
  */
 
 import { expandAllTasks } from '../../../../scripts/modules/task-manager.js';
-import { enableSilentMode, disableSilentMode, isSilentMode } from '../../../../scripts/modules/utils.js';
-import { findTasksJsonPath } from '../utils/path-utils.js';
-import { getAnthropicClientForMCP } from '../utils/ai-client-utils.js';
-import path from 'path';
-import fs from 'fs';
+import {
+	enableSilentMode,
+	disableSilentMode
+} from '../../../../scripts/modules/utils.js';
+import { createLogWrapper } from '../../tools/utils.js';
 
 /**
- * Expand all pending tasks with subtasks
+ * Expand all pending tasks with subtasks (Direct Function Wrapper)
  * @param {Object} args - Function arguments
+ * @param {string} args.tasksJsonPath - Explicit path to the tasks.json file.
  * @param {number|string} [args.num] - Number of subtasks to generate
- * @param {boolean} [args.research] - Enable Perplexity AI for research-backed subtask generation
+ * @param {boolean} [args.research] - Enable research-backed subtask generation
  * @param {string} [args.prompt] - Additional context to guide subtask generation
  * @param {boolean} [args.force] - Force regeneration of subtasks for tasks that already have them
- * @param {string} [args.file] - Path to the tasks file
- * @param {string} [args.projectRoot] - Project root directory
- * @param {Object} log - Logger object
+ * @param {string} [args.projectRoot] - Project root path.
+ * @param {Object} log - Logger object from FastMCP
  * @param {Object} context - Context object containing session
  * @returns {Promise<{success: boolean, data?: Object, error?: {code: string, message: string}}>}
  */
 export async function expandAllTasksDirect(args, log, context = {}) {
-  const { session } = context; // Only extract session, not reportProgress
+	const { session } = context; // Extract session
+	// Destructure expected args, including projectRoot
+	const { tasksJsonPath, num, research, prompt, force, projectRoot } = args;
 
-  try {
-    log.info(`Expanding all tasks with args: ${JSON.stringify(args)}`);
+	// Create logger wrapper using the utility
+	const mcpLog = createLogWrapper(log);
 
-    // Enable silent mode early to prevent any console output
-    enableSilentMode();
-    
-    try {
-      // Find the tasks.json path
-      const tasksPath = findTasksJsonPath(args, log);
-      
-      // Parse parameters
-      const numSubtasks = args.num ? parseInt(args.num, 10) : undefined;
-      const useResearch = args.research === true;
-      const additionalContext = args.prompt || '';
-      const forceFlag = args.force === true;
-      
-      log.info(`Expanding all tasks with ${numSubtasks || 'default'} subtasks each...`);
-      
-      if (useResearch) {
-        log.info('Using Perplexity AI for research-backed subtask generation');
-        
-        // Initialize AI client for research-backed expansion
-        try {
-          await getAnthropicClientForMCP(session, log);
-        } catch (error) {
-          // Ensure silent mode is disabled before returning error
-          disableSilentMode();
-          
-          log.error(`Failed to initialize AI client: ${error.message}`);
+	if (!tasksJsonPath) {
+		log.error('expandAllTasksDirect called without tasksJsonPath');
 		return {
 			success: false,
 			error: {
-              code: 'AI_CLIENT_ERROR',
-              message: `Cannot initialize AI client: ${error.message}`
+				code: 'MISSING_ARGUMENT',
+				message: 'tasksJsonPath is required'
 			}
 		};
 	}
-      }
 
-      if (additionalContext) {
-        log.info(`Additional context: "${additionalContext}"`);
-      }
-      if (forceFlag) {
-        log.info('Force regeneration of subtasks is enabled');
-      }
+	enableSilentMode(); // Enable silent mode for the core function call
+	try {
+		log.info(
+			`Calling core expandAllTasks with args: ${JSON.stringify({ num, research, prompt, force, projectRoot })}`
+		);
 
-      // Call the core function with session context for AI operations
-      // and outputFormat as 'json' to prevent UI elements
+		// Parse parameters (ensure correct types)
+		const numSubtasks = num ? parseInt(num, 10) : undefined;
+		const useResearch = research === true;
+		const additionalContext = prompt || '';
+		const forceFlag = force === true;
+
+		// Call the core function, passing options and the context object { session, mcpLog, projectRoot }
 		const result = await expandAllTasks(
-        tasksPath,
+			tasksJsonPath,
 			numSubtasks,
 			useResearch,
 			additionalContext,
 			forceFlag,
-        { mcpLog: log, session },
-        'json' // Use JSON output format to prevent UI elements
+			{ session, mcpLog, projectRoot }
 		);
 
-      // The expandAllTasks function now returns a result object
+		// Core function now returns a summary object including the *aggregated* telemetryData
 		return {
 			success: true,
 			data: {
-          message: "Successfully expanded all pending tasks with subtasks",
+				message: `Expand all operation completed. Expanded: ${result.expandedCount}, Failed: ${result.failedCount}, Skipped: ${result.skippedCount}`,
 				details: {
-            numSubtasks: numSubtasks,
-            research: useResearch,
-            prompt: additionalContext,
-            force: forceFlag,
-            tasksExpanded: result.expandedCount,
-            totalEligibleTasks: result.tasksToExpand
-          }
+					expandedCount: result.expandedCount,
+					failedCount: result.failedCount,
+					skippedCount: result.skippedCount,
+					tasksToExpand: result.tasksToExpand
+				},
+				telemetryData: result.telemetryData // Pass the aggregated object
 			}
 		};
-    } finally {
-      // Restore normal logging in finally block to ensure it runs even if there's an error
-      disableSilentMode();
-    }
 	} catch (error) {
-    // Ensure silent mode is disabled if an error occurs
-    if (isSilentMode()) {
-      disableSilentMode();
-    }
+		// Log the error using the MCP logger
+		log.error(`Error during core expandAllTasks execution: ${error.message}`);
+		// Optionally log stack trace if available and debug enabled
+		// if (error.stack && log.debug) { log.debug(error.stack); }
 
-    log.error(`Error in expandAllTasksDirect: ${error.message}`);
 		return {
 			success: false,
 			error: {
-        code: 'CORE_FUNCTION_ERROR',
+				code: 'CORE_FUNCTION_ERROR', // Or a more specific code if possible
 				message: error.message
 			}
 		};
+	} finally {
+		disableSilentMode(); // IMPORTANT: Ensure silent mode is always disabled
 	}
 }

mcp-server/src/core/direct-functions/expand-task.js

@@ -3,68 +3,69 @@
  * Direct function implementation for expanding a task into subtasks
  */
 
-import { expandTask } from '../../../../scripts/modules/task-manager.js';
-import { readJSON, writeJSON, enableSilentMode, disableSilentMode, isSilentMode } from '../../../../scripts/modules/utils.js';
-import { findTasksJsonPath } from '../utils/path-utils.js';
-import { getAnthropicClientForMCP, getModelConfig } from '../utils/ai-client-utils.js';
+import expandTask from '../../../../scripts/modules/task-manager/expand-task.js';
+import {
+	readJSON,
+	writeJSON,
+	enableSilentMode,
+	disableSilentMode,
+	isSilentMode
+} from '../../../../scripts/modules/utils.js';
 import path from 'path';
 import fs from 'fs';
+import { createLogWrapper } from '../../tools/utils.js';
 
 /**
  * Direct function wrapper for expanding a task into subtasks with error handling.
  *
  * @param {Object} args - Command arguments
+ * @param {string} args.tasksJsonPath - Explicit path to the tasks.json file.
+ * @param {string} args.id - The ID of the task to expand.
+ * @param {number|string} [args.num] - Number of subtasks to generate.
+ * @param {boolean} [args.research] - Enable research role for subtask generation.
+ * @param {string} [args.prompt] - Additional context to guide subtask generation.
+ * @param {boolean} [args.force] - Force expansion even if subtasks exist.
+ * @param {string} [args.projectRoot] - Project root directory.
  * @param {Object} log - Logger object
- * @param {Object} context - Context object containing session and reportProgress
+ * @param {Object} context - Context object containing session
+ * @param {Object} [context.session] - MCP Session object
  * @returns {Promise<Object>} - Task expansion result { success: boolean, data?: any, error?: { code: string, message: string }, fromCache: boolean }
  */
 export async function expandTaskDirect(args, log, context = {}) {
-  const { session } = context;
+	const { session } = context; // Extract session
+	// Destructure expected args, including projectRoot
+	const { tasksJsonPath, id, num, research, prompt, force, projectRoot } = args;
 
 	// Log session root data for debugging
-  log.info(`Session data in expandTaskDirect: ${JSON.stringify({
+	log.info(
+		`Session data in expandTaskDirect: ${JSON.stringify({
 			hasSession: !!session,
 			sessionKeys: session ? Object.keys(session) : [],
 			roots: session?.roots,
 			rootsStr: JSON.stringify(session?.roots)
-  })}`);
-  
-  let tasksPath;
-  try {
-    // If a direct file path is provided, use it directly
-    if (args.file && fs.existsSync(args.file)) {
-      log.info(`[expandTaskDirect] Using explicitly provided tasks file: ${args.file}`);
-      tasksPath = args.file;
-    } else {
-      // Find the tasks path through standard logic
-      log.info(`[expandTaskDirect] No direct file path provided or file not found at ${args.file}, searching using findTasksJsonPath`);
-      tasksPath = findTasksJsonPath(args, log);
-    }
-  } catch (error) {
-    log.error(`[expandTaskDirect] Error during tasksPath determination: ${error.message}`);
-    
-    // Include session roots information in error
-    const sessionRootsInfo = session ? 
-      `\nSession.roots: ${JSON.stringify(session.roots)}\n` +
-      `Current Working Directory: ${process.cwd()}\n` +
-      `Args.projectRoot: ${args.projectRoot}\n` +
-      `Args.file: ${args.file}\n` : 
-      '\nSession object not available';
+		})}`
+	);
 
+	// Check if tasksJsonPath was provided
+	if (!tasksJsonPath) {
+		log.error('expandTaskDirect called without tasksJsonPath');
 		return {
 			success: false,
 			error: {
-        code: 'FILE_NOT_FOUND_ERROR', 
-        message: `Error determining tasksPath: ${error.message}${sessionRootsInfo}` 
+				code: 'MISSING_ARGUMENT',
+				message: 'tasksJsonPath is required'
 			},
 			fromCache: false
 		};
 	}
 
-  log.info(`[expandTaskDirect] Determined tasksPath: ${tasksPath}`);
+	// Use provided path
+	const tasksPath = tasksJsonPath;
+
+	log.info(`[expandTaskDirect] Using tasksPath: ${tasksPath}`);
 
 	// Validate task ID
-  const taskId = args.id ? parseInt(args.id, 10) : null;
+	const taskId = id ? parseInt(id, 10) : null;
 	if (!taskId) {
 		log.error('Task ID is required');
 		return {
@@ -78,39 +79,27 @@ export async function expandTaskDirect(args, log, context = {}) {
 	}
 
 	// Process other parameters
-  const numSubtasks = args.num ? parseInt(args.num, 10) : undefined;
-  const useResearch = args.research === true;
-  const additionalContext = args.prompt || '';
-
-  // Initialize AI client if needed (for expandTask function)
-  try {
-    // This ensures the AI client is available by checking it
-    if (useResearch) {
-      log.info('Verifying AI client for research-backed expansion');
-      await getAnthropicClientForMCP(session, log);
-    }
-  } catch (error) {
-    log.error(`Failed to initialize AI client: ${error.message}`);
-    return {
-      success: false,
-      error: {
-        code: 'AI_CLIENT_ERROR',
-        message: `Cannot initialize AI client: ${error.message}`
-      },
-      fromCache: false
-    };
-  }
+	const numSubtasks = num ? parseInt(num, 10) : undefined;
+	const useResearch = research === true;
+	const additionalContext = prompt || '';
+	const forceFlag = force === true;
 
 	try {
-    log.info(`[expandTaskDirect] Expanding task ${taskId} into ${numSubtasks || 'default'} subtasks. Research: ${useResearch}`);
+		log.info(
+			`[expandTaskDirect] Expanding task ${taskId} into ${numSubtasks || 'default'} subtasks. Research: ${useResearch}, Force: ${forceFlag}`
+		);
 
 		// Read tasks data
 		log.info(`[expandTaskDirect] Attempting to read JSON from: ${tasksPath}`);
 		const data = readJSON(tasksPath);
-    log.info(`[expandTaskDirect] Result of readJSON: ${data ? 'Data read successfully' : 'readJSON returned null or undefined'}`);
+		log.info(
+			`[expandTaskDirect] Result of readJSON: ${data ? 'Data read successfully' : 'readJSON returned null or undefined'}`
+		);
 
 		if (!data || !data.tasks) {
-      log.error(`[expandTaskDirect] readJSON failed or returned invalid data for path: ${tasksPath}`);
+			log.error(
+				`[expandTaskDirect] readJSON failed or returned invalid data for path: ${tasksPath}`
+			);
 			return {
 				success: false,
 				error: {
@@ -123,7 +112,7 @@ export async function expandTaskDirect(args, log, context = {}) {
 
 		// Find the specific task
 		log.info(`[expandTaskDirect] Searching for task ID ${taskId} in data`);
-    const task = data.tasks.find(t => t.id === taskId);
+		const task = data.tasks.find((t) => t.id === taskId);
 		log.info(`[expandTaskDirect] Task found: ${task ? 'Yes' : 'No'}`);
 
 		if (!task) {
@@ -149,15 +138,16 @@ export async function expandTaskDirect(args, log, context = {}) {
 			};
 		}
 
-    // Check for existing subtasks
+		// Check for existing subtasks and force flag
 		const hasExistingSubtasks = task.subtasks && task.subtasks.length > 0;
-    
-    // If the task already has subtasks, just return it (matching core behavior)
-    if (hasExistingSubtasks) {
-      log.info(`Task ${taskId} already has ${task.subtasks.length} subtasks`);
+		if (hasExistingSubtasks && !forceFlag) {
+			log.info(
+				`Task ${taskId} already has ${task.subtasks.length} subtasks. Use --force to overwrite.`
+			);
 			return {
 				success: true,
 				data: {
+					message: `Task ${taskId} already has subtasks. Expansion skipped.`,
 					task,
 					subtasksAdded: 0,
 					hasExistingSubtasks
@@ -166,6 +156,14 @@ export async function expandTaskDirect(args, log, context = {}) {
 			};
 		}
 
+		// If force flag is set, clear existing subtasks
+		if (hasExistingSubtasks && forceFlag) {
+			log.info(
+				`Force flag set. Clearing existing subtasks for task ${taskId}.`
+			);
+			task.subtasks = [];
+		}
+
 		// Keep a copy of the task before modification
 		const originalTask = JSON.parse(JSON.stringify(task));
 
@@ -184,46 +182,62 @@ export async function expandTaskDirect(args, log, context = {}) {
 		// Save tasks.json with potentially empty subtasks array
 		writeJSON(tasksPath, data);
 
+		// Create logger wrapper using the utility
+		const mcpLog = createLogWrapper(log);
+
+		let wasSilent; // Declare wasSilent outside the try block
 		// Process the request
 		try {
 			// Enable silent mode to prevent console logs from interfering with JSON response
-      enableSilentMode();
+			wasSilent = isSilentMode(); // Assign inside the try block
+			if (!wasSilent) enableSilentMode();
 
-      // Call expandTask with session context to ensure AI client is properly initialized
-      const result = await expandTask(
+			// Call the core expandTask function with the wrapped logger and projectRoot
+			const coreResult = await expandTask(
 				tasksPath,
 				taskId,
 				numSubtasks,
 				useResearch,
 				additionalContext,
-        { mcpLog: log, session } // Only pass mcpLog and session, NOT reportProgress
+				{
+					mcpLog,
+					session,
+					projectRoot,
+					commandName: 'expand-task',
+					outputType: 'mcp'
+				},
+				forceFlag
 			);
 
 			// Restore normal logging
-      disableSilentMode();
+			if (!wasSilent && isSilentMode()) disableSilentMode();
 
 			// Read the updated data
 			const updatedData = readJSON(tasksPath);
-      const updatedTask = updatedData.tasks.find(t => t.id === taskId);
+			const updatedTask = updatedData.tasks.find((t) => t.id === taskId);
 
 			// Calculate how many subtasks were added
-      const subtasksAdded = updatedTask.subtasks ? 
-        updatedTask.subtasks.length - subtasksCountBefore : 0;
+			const subtasksAdded = updatedTask.subtasks
+				? updatedTask.subtasks.length - subtasksCountBefore
+				: 0;
 
-      // Return the result
-      log.info(`Successfully expanded task ${taskId} with ${subtasksAdded} new subtasks`);
+			// Return the result, including telemetryData
+			log.info(
+				`Successfully expanded task ${taskId} with ${subtasksAdded} new subtasks`
+			);
 			return {
 				success: true,
 				data: {
-          task: updatedTask,
+					task: coreResult.task,
 					subtasksAdded,
-          hasExistingSubtasks
+					hasExistingSubtasks,
+					telemetryData: coreResult.telemetryData
 				},
 				fromCache: false
 			};
 		} catch (error) {
 			// Make sure to restore normal logging even if there's an error
-      disableSilentMode();
+			if (!wasSilent && isSilentMode()) disableSilentMode();
 
 			log.error(`Error expanding task: ${error.message}`);
 			return {

mcp-server/src/core/direct-functions/fix-dependencies.js

@@ -3,24 +3,39 @@
  */
 
 import { fixDependenciesCommand } from '../../../../scripts/modules/dependency-manager.js';
-import { findTasksJsonPath } from '../utils/path-utils.js';
-import { enableSilentMode, disableSilentMode } from '../../../../scripts/modules/utils.js';
+import {
+	enableSilentMode,
+	disableSilentMode
+} from '../../../../scripts/modules/utils.js';
 import fs from 'fs';
 
 /**
  * Fix invalid dependencies in tasks.json automatically
  * @param {Object} args - Function arguments
- * @param {string} [args.file] - Path to the tasks file
- * @param {string} [args.projectRoot] - Project root directory
+ * @param {string} args.tasksJsonPath - Explicit path to the tasks.json file.
  * @param {Object} log - Logger object
  * @returns {Promise<{success: boolean, data?: Object, error?: {code: string, message: string}}>}
  */
 export async function fixDependenciesDirect(args, log) {
+	// Destructure expected args
+	const { tasksJsonPath } = args;
 	try {
-    log.info(`Fixing invalid dependencies in tasks...`);
+		log.info(`Fixing invalid dependencies in tasks: ${tasksJsonPath}`);
 
-    // Find the tasks.json path
-    const tasksPath = findTasksJsonPath(args, log);
+		// Check if tasksJsonPath was provided
+		if (!tasksJsonPath) {
+			log.error('fixDependenciesDirect called without tasksJsonPath');
+			return {
+				success: false,
+				error: {
+					code: 'MISSING_ARGUMENT',
+					message: 'tasksJsonPath is required'
+				}
+			};
+		}
+
+		// Use provided path
+		const tasksPath = tasksJsonPath;
 
 		// Verify the file exists
 		if (!fs.existsSync(tasksPath)) {
@@ -36,7 +51,7 @@ export async function fixDependenciesDirect(args, log) {
 		// Enable silent mode to prevent console logs from interfering with JSON response
 		enableSilentMode();
 
-    // Call the original command function
+		// Call the original command function using the provided path
 		await fixDependenciesCommand(tasksPath);
 
 		// Restore normal logging

mcp-server/src/core/direct-functions/generate-task-files.js

@@ -4,41 +4,49 @@
  */
 
 import { generateTaskFiles } from '../../../../scripts/modules/task-manager.js';
-import { enableSilentMode, disableSilentMode } from '../../../../scripts/modules/utils.js';
-import { findTasksJsonPath } from '../utils/path-utils.js';
-import path from 'path';
+import {
+	enableSilentMode,
+	disableSilentMode
+} from '../../../../scripts/modules/utils.js';
 
 /**
  * Direct function wrapper for generateTaskFiles with error handling.
  *
- * @param {Object} args - Command arguments containing file and output path options.
+ * @param {Object} args - Command arguments containing tasksJsonPath and outputDir.
  * @param {Object} log - Logger object.
  * @returns {Promise<Object>} - Result object with success status and data/error information.
  */
 export async function generateTaskFilesDirect(args, log) {
+	// Destructure expected args
+	const { tasksJsonPath, outputDir } = args;
 	try {
 		log.info(`Generating task files with args: ${JSON.stringify(args)}`);
 
-    // Get tasks file path
-    let tasksPath;
-    try {
-      tasksPath = findTasksJsonPath(args, log);
-    } catch (error) {
-      log.error(`Error finding tasks file: ${error.message}`);
+		// Check if paths were provided
+		if (!tasksJsonPath) {
+			const errorMessage = 'tasksJsonPath is required but was not provided.';
+			log.error(errorMessage);
 			return {
 				success: false,
-        error: { code: 'TASKS_FILE_ERROR', message: error.message },
+				error: { code: 'MISSING_ARGUMENT', message: errorMessage },
+				fromCache: false
+			};
+		}
+		if (!outputDir) {
+			const errorMessage = 'outputDir is required but was not provided.';
+			log.error(errorMessage);
+			return {
+				success: false,
+				error: { code: 'MISSING_ARGUMENT', message: errorMessage },
 				fromCache: false
 			};
 		}
 
-    // Get output directory (defaults to the same directory as the tasks file)
-    let outputDir = args.output;
-    if (!outputDir) {
-      outputDir = path.dirname(tasksPath);
-    }
+		// Use the provided paths
+		const tasksPath = tasksJsonPath;
+		const resolvedOutputDir = outputDir;
 
-    log.info(`Generating task files from ${tasksPath} to ${outputDir}`);
+		log.info(`Generating task files from ${tasksPath} to ${resolvedOutputDir}`);
 
 		// Execute core generateTaskFiles function in a separate try/catch
 		try {
@@ -46,7 +54,7 @@ export async function generateTaskFilesDirect(args, log) {
 			enableSilentMode();
 
 			// The function is synchronous despite being awaited elsewhere
-      generateTaskFiles(tasksPath, outputDir);
+			generateTaskFiles(tasksPath, resolvedOutputDir);
 
 			// Restore normal logging after task generation
 			disableSilentMode();
@@ -67,9 +75,10 @@ export async function generateTaskFilesDirect(args, log) {
 			success: true,
 			data: {
 				message: `Successfully generated task files`,
-        tasksPath,
-        outputDir,
-        taskFiles: 'Individual task files have been generated in the output directory'
+				tasksPath: tasksPath,
+				outputDir: resolvedOutputDir,
+				taskFiles:
+					'Individual task files have been generated in the output directory'
 			},
 			fromCache: false // This operation always modifies state and should never be cached
 		};
@@ -80,7 +89,10 @@ export async function generateTaskFilesDirect(args, log) {
 		log.error(`Error generating task files: ${error.message}`);
 		return {
 			success: false,
-      error: { code: 'GENERATE_TASKS_ERROR', message: error.message || 'Unknown error generating task files' },
+			error: {
+				code: 'GENERATE_TASKS_ERROR',
+				message: error.message || 'Unknown error generating task files'
+			},
 			fromCache: false
 		};
 	}

mcp-server/src/core/direct-functions/initialize-project.js

@@ -0,0 +1,104 @@
+import { initializeProject } from '../../../../scripts/init.js'; // Import core function and its logger if needed separately
+import {
+	enableSilentMode,
+	disableSilentMode
+	// isSilentMode // Not used directly here
+} from '../../../../scripts/modules/utils.js';
+import os from 'os'; // Import os module for home directory check
+
+/**
+ * Direct function wrapper for initializing a project.
+ * Derives target directory from session, sets CWD, and calls core init logic.
+ * @param {object} args - Arguments containing initialization options (addAliases, skipInstall, yes, projectRoot)
+ * @param {object} log - The FastMCP logger instance.
+ * @param {object} context - The context object, must contain { session }.
+ * @returns {Promise<{success: boolean, data?: any, error?: {code: string, message: string}}>} - Standard result object.
+ */
+export async function initializeProjectDirect(args, log, context = {}) {
+	const { session } = context; // Keep session if core logic needs it
+	const homeDir = os.homedir();
+
+	log.info(`Args received in direct function: ${JSON.stringify(args)}`);
+
+	// --- Determine Target Directory ---
+	// TRUST the projectRoot passed from the tool layer via args
+	// The HOF in the tool layer already normalized and validated it came from a reliable source (args or session)
+	const targetDirectory = args.projectRoot;
+
+	// --- Validate the targetDirectory (basic sanity checks) ---
+	if (
+		!targetDirectory ||
+		typeof targetDirectory !== 'string' || // Ensure it's a string
+		targetDirectory === '/' ||
+		targetDirectory === homeDir
+	) {
+		log.error(
+			`Invalid target directory received from tool layer: '${targetDirectory}'`
+		);
+		return {
+			success: false,
+			error: {
+				code: 'INVALID_TARGET_DIRECTORY',
+				message: `Cannot initialize project: Invalid target directory '${targetDirectory}' received. Please ensure a valid workspace/folder is open or specified.`,
+				details: `Received args.projectRoot: ${args.projectRoot}` // Show what was received
+			},
+			fromCache: false
+		};
+	}
+
+	// --- Proceed with validated targetDirectory ---
+	log.info(`Validated target directory for initialization: ${targetDirectory}`);
+
+	const originalCwd = process.cwd();
+	let resultData;
+	let success = false;
+	let errorResult = null;
+
+	log.info(
+		`Temporarily changing CWD to ${targetDirectory} for initialization.`
+	);
+	process.chdir(targetDirectory); // Change CWD to the HOF-provided root
+
+	enableSilentMode();
+	try {
+		// Construct options ONLY from the relevant flags in args
+		// The core initializeProject operates in the current CWD, which we just set
+		const options = {
+			aliases: args.addAliases,
+			skipInstall: args.skipInstall,
+			yes: true // Force yes mode
+		};
+
+		log.info(`Initializing project with options: ${JSON.stringify(options)}`);
+		const result = await initializeProject(options); // Call core logic
+
+		resultData = {
+			message: 'Project initialized successfully.',
+			next_step:
+				'Now that the project is initialized, the next step is to create the tasks by parsing a PRD. This will create the tasks folder and the initial task files (tasks folder will be created when parse-prd is run). The parse-prd tool will require a prd.txt file as input (typically found in the project root directory, scripts/ directory). You can create a prd.txt file by asking the user about their idea, and then using the scripts/example_prd.txt file as a template to genrate a prd.txt file in scripts/. You may skip all of this if the user already has a prd.txt file. You can THEN use the parse-prd tool to create the tasks. So: step 1 after initialization is to create a prd.txt file in scripts/prd.txt or confirm the user already has one. Step 2 is to use the parse-prd tool to create the tasks. Do not bother looking for tasks after initialization, just use the parse-prd tool to create the tasks after creating a prd.txt from which to parse the tasks. You do NOT need to reinitialize the project to parse-prd.',
+			...result
+		};
+		success = true;
+		log.info(
+			`Project initialization completed successfully in ${targetDirectory}.`
+		);
+	} catch (error) {
+		log.error(`Core initializeProject failed: ${error.message}`);
+		errorResult = {
+			code: 'INITIALIZATION_FAILED',
+			message: `Core project initialization failed: ${error.message}`,
+			details: error.stack
+		};
+		success = false;
+	} finally {
+		disableSilentMode();
+		log.info(`Restoring original CWD: ${originalCwd}`);
+		process.chdir(originalCwd);
+	}
+
+	if (success) {
+		return { success: true, data: resultData, fromCache: false };
+	} else {
+		return { success: false, error: errorResult, fromCache: false };
+	}
+}

mcp-server/src/core/direct-functions/list-tasks.js

@@ -4,37 +4,37 @@
  */
 
 import { listTasks } from '../../../../scripts/modules/task-manager.js';
-import { getCachedOrExecute } from '../../tools/utils.js';
-import { findTasksJsonPath } from '../utils/path-utils.js';
-import { enableSilentMode, disableSilentMode } from '../../../../scripts/modules/utils.js';
+import {
+	enableSilentMode,
+	disableSilentMode
+} from '../../../../scripts/modules/utils.js';
 
 /**
  * Direct function wrapper for listTasks with error handling and caching.
  *
- * @param {Object} args - Command arguments (projectRoot is expected to be resolved).
+ * @param {Object} args - Command arguments (now expecting tasksJsonPath explicitly).
  * @param {Object} log - Logger object.
  * @returns {Promise<Object>} - Task list result { success: boolean, data?: any, error?: { code: string, message: string }, fromCache: boolean }.
  */
 export async function listTasksDirect(args, log) {
-  let tasksPath;
-  try {
-    // Find the tasks path first - needed for cache key and execution
-    tasksPath = findTasksJsonPath(args, log);
-  } catch (error) {
-    if (error.code === 'TASKS_FILE_NOT_FOUND') {
-      log.error(`Tasks file not found: ${error.message}`);
-      // Return the error structure expected by the calling tool/handler
-      return { success: false, error: { code: error.code, message: error.message }, fromCache: false };
-    }
-    log.error(`Unexpected error finding tasks file: ${error.message}`);
-    // Re-throw for outer catch or return structured error
-     return { success: false, error: { code: 'FIND_TASKS_PATH_ERROR', message: error.message }, fromCache: false };
+	// Destructure the explicit tasksJsonPath from args
+	const { tasksJsonPath, reportPath, status, withSubtasks } = args;
+
+	if (!tasksJsonPath) {
+		log.error('listTasksDirect called without tasksJsonPath');
+		return {
+			success: false,
+			error: {
+				code: 'MISSING_ARGUMENT',
+				message: 'tasksJsonPath is required'
+			},
+			fromCache: false
+		};
 	}
 
-  // Generate cache key *after* finding tasksPath
-  const statusFilter = args.status || 'all';
-  const withSubtasks = args.withSubtasks || false;
-  const cacheKey = `listTasks:${tasksPath}:${statusFilter}:${withSubtasks}`;
+	// Use the explicit tasksJsonPath for cache key
+	const statusFilter = status || 'all';
+	const withSubtasksFilter = withSubtasks || false;
 
 	// Define the action function to be executed on cache miss
 	const coreListTasksAction = async () => {
@@ -42,42 +42,65 @@ export async function listTasksDirect(args, log) {
 			// Enable silent mode to prevent console logs from interfering with JSON response
 			enableSilentMode();
 
-      log.info(`Executing core listTasks function for path: ${tasksPath}, filter: ${statusFilter}, subtasks: ${withSubtasks}`);
-      const resultData = listTasks(tasksPath, statusFilter, withSubtasks, 'json');
+			log.info(
+				`Executing core listTasks function for path: ${tasksJsonPath}, filter: ${statusFilter}, subtasks: ${withSubtasksFilter}`
+			);
+			// Pass the explicit tasksJsonPath to the core function
+			const resultData = listTasks(
+				tasksJsonPath,
+				statusFilter,
+				reportPath,
+				withSubtasksFilter,
+				'json'
+			);
 
 			if (!resultData || !resultData.tasks) {
 				log.error('Invalid or empty response from listTasks core function');
-        return { success: false, error: { code: 'INVALID_CORE_RESPONSE', message: 'Invalid or empty response from listTasks core function' } };
+				return {
+					success: false,
+					error: {
+						code: 'INVALID_CORE_RESPONSE',
+						message: 'Invalid or empty response from listTasks core function'
 					}
-      log.info(`Core listTasks function retrieved ${resultData.tasks.length} tasks`);
+				};
+			}
+
+			log.info(
+				`Core listTasks function retrieved ${resultData.tasks.length} tasks`
+			);
 
 			// Restore normal logging
 			disableSilentMode();
 
 			return { success: true, data: resultData };
-
 		} catch (error) {
 			// Make sure to restore normal logging even if there's an error
 			disableSilentMode();
 
 			log.error(`Core listTasks function failed: ${error.message}`);
-      return { success: false, error: { code: 'LIST_TASKS_CORE_ERROR', message: error.message || 'Failed to list tasks' } };
+			return {
+				success: false,
+				error: {
+					code: 'LIST_TASKS_CORE_ERROR',
+					message: error.message || 'Failed to list tasks'
+				}
+			};
 		}
 	};
 
-  // Use the caching utility
 	try {
-      const result = await getCachedOrExecute({
-          cacheKey,
-          actionFn: coreListTasksAction,
-          log
-      });
-      log.info(`listTasksDirect completed. From cache: ${result.fromCache}`);
-      return result; // Returns { success, data/error, fromCache }
-  } catch(error) {
-      // Catch unexpected errors from getCachedOrExecute itself (though unlikely)
-      log.error(`Unexpected error during getCachedOrExecute for listTasks: ${error.message}`);
+		const result = await coreListTasksAction();
+		log.info('listTasksDirect completed');
+		return result;
+	} catch (error) {
+		log.error(`Unexpected error during listTasks: ${error.message}`);
 		console.error(error.stack);
-      return { success: false, error: { code: 'CACHE_UTIL_ERROR', message: error.message }, fromCache: false };
+		return {
+			success: false,
+			error: {
+				code: 'UNEXPECTED_ERROR',
+				message: error.message
+			}
+		};
 	}
 }