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Author SHA1 Message Date
Ralph Khreish
293b59bac6 Merge pull request #630 from eyaltoledano/changeset-release/main
Version Packages
2025-06-01 17:49:18 +02:00
Ralph Khreish
1809c4ed7b chore: add package-lock.json 2025-06-01 11:48:11 -04:00
github-actions[bot]
6e406958c1 Version Packages 2025-06-01 15:24:59 +00:00
Ralph Khreish
074b7ec0bc Merge pull request #625 from eyaltoledano/next 2025-06-01 17:24:37 +02:00
Ralph Khreish
e0438c8fb8 chore: cleanup migration-guide 2025-06-01 01:08:31 -04:00
github-actions[bot]
1f6694fb3d chore: rc version bump 2025-06-01 04:20:35 +00:00
Ralph Khreish
b0dfcf345e chore: apply requested changes from next branch (#629) 2025-06-01 06:19:55 +02:00
Ralph Khreish
3f64202c9f feat: Add .taskmaster directory (#619) 2025-05-31 16:21:03 +02:00
Ralph Khreish
669b744ced Feat/add nvmrc (#612)
* feat: Add .nvmrc and align engines to Node 20

* chore: set nvm to 22, engines to 18

* chore: format

* chore: add changeset

---------

Co-authored-by: Amir Golan <amirgolan@Amirs-MacBook-Pro.local>
2025-05-28 15:02:15 +02:00
Nathan Marley
f058543888 Replace prettier with biome (#531) 2025-05-28 14:47:16 +02:00
Ralph Khreish
acd5c1ea3d chore: add contributing.md (#611) 2025-05-28 00:59:14 +02:00
github-actions[bot]
682b54e103 docs: Auto-update and format models.md 2025-05-27 22:42:42 +00:00
Ralph Khreish
6a8a68e1a3 Feat/add.azure.and.other.providers (#607)
* fix: claude-4 not having the right max_tokens

* feat: add bedrock support

* chore: fix package-lock.json

* fix: rename baseUrl to baseURL

* feat: add azure support

* fix: final touches of azure integration

* feat: add google vertex provider

* chore: fix tests and refactor task-manager.test.js

* chore: move task 92 to 94
2025-05-28 00:42:31 +02:00
Ralph Khreish
80735f9e60 feat(config): Implement TASK_MASTER_PROJECT_ROOT support for project root resolution (#604)
* feat(config): Implement TASK_MASTER_PROJECT_ROOT support for project root resolution

- Added support for the TASK_MASTER_PROJECT_ROOT environment variable in MCP configuration, establishing a clear precedence order for project root resolution.
- Updated utility functions to prioritize the environment variable, followed by args.projectRoot and session-based resolution.
- Enhanced error handling and logging for project root determination.
- Introduced new tasks for comprehensive testing and documentation updates related to the new configuration options.

* chore: fix CI issues
2025-05-28 00:32:34 +02:00
195 changed files with 11274 additions and 7079 deletions

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@@ -1,7 +0,0 @@
---
'task-master-ai': minor
---
Add TASK_MASTER_PROJECT_ROOT env variable supported in mcp.json and .env for project root resolution
- Some users were having issues where the MCP wasn't able to detect the location of their project root, you can now set the `TASK_MASTER_PROJECT_ROOT` environment variable to the root of your project.

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@@ -1,5 +0,0 @@
---
'task-master-ai': patch
---
Fix add-task MCP command causing an error

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@@ -104,7 +104,7 @@ Task Master offers two primary ways to interact:
Taskmaster configuration is managed through two main mechanisms:
1. **`.taskmasterconfig` File (Primary):**
1. **`.taskmaster/config.json` 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.

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@@ -36,7 +36,7 @@ This document provides a detailed reference for interacting with Taskmaster, cov
* `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.
* **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 .taskmaster/templates/example_prd.txt.
### 2. Parse PRD (`parse_prd`)
@@ -50,7 +50,7 @@ This document provides a detailed reference for interacting with Taskmaster, cov
* `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, 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`.
* **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 `.taskmaster/templates/example_prd.txt` as a template for creating the PRD based on their idea, for use with `parse-prd`.
---
@@ -77,10 +77,10 @@ This document provides a detailed reference for interacting with Taskmaster, cov
* `--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.
* **Notes:** Configuration is stored in `.taskmaster/config.json` 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.
* **Warning:** DO NOT MANUALLY EDIT THE .taskmaster/config.json 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.
---
@@ -348,7 +348,7 @@ This document provides a detailed reference for interacting with Taskmaster, cov
* **CLI Command:** `task-master analyze-complexity [options]`
* **Description:** `Have Taskmaster analyze your tasks to determine their complexity and suggest which ones need to be broken down further.`
* **Key Parameters/Options:**
* `output`: `Where to save the complexity analysis report (default: 'scripts/task-complexity-report.json').` (CLI: `-o, --output <file>`)
* `output`: `Where to save the complexity analysis report (default: '.taskmaster/reports/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 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>`)
@@ -361,7 +361,7 @@ This document provides a detailed reference for interacting with Taskmaster, cov
* **CLI Command:** `task-master complexity-report [options]`
* **Description:** `Display the task complexity analysis report in a readable format.`
* **Key Parameters/Options:**
* `file`: `Path to the complexity report (default: 'scripts/task-complexity-report.json').` (CLI: `-f, --file <file>`)
* `file`: `Path to the complexity report (default: '.taskmaster/reports/task-complexity-report.json').` (CLI: `-f, --file <file>`)
* **Usage:** Review and understand the complexity analysis results after running analyze-complexity.
---
@@ -382,7 +382,7 @@ This document provides a detailed reference for interacting with Taskmaster, cov
## Environment Variables Configuration (Updated)
Taskmaster primarily uses the **`.taskmasterconfig`** file (in project root) for configuration (models, parameters, logging level, etc.), managed via `task-master models --setup`.
Taskmaster primarily uses the **`.taskmaster/config.json`** file (in project root) for configuration (models, parameters, logging level, etc.), managed via `task-master models --setup`.
Environment variables are used **only** for sensitive API keys related to AI providers and specific overrides like the Ollama base URL:
@@ -396,11 +396,11 @@ Environment variables are used **only** for sensitive API keys related to AI pro
* `OPENROUTER_API_KEY`
* `XAI_API_KEY`
* `OLLANA_API_KEY` (Requires `OLLAMA_BASE_URL` too)
* **Endpoints (Optional/Provider Specific inside .taskmasterconfig):**
* **Endpoints (Optional/Provider Specific inside .taskmaster/config.json):**
* `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.
**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 `.taskmaster/config.json` via `task-master models` command or `models` MCP tool.
---

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@@ -7,3 +7,9 @@ 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
# Google Vertex AI Configuration
VERTEX_PROJECT_ID=your-gcp-project-id
VERTEX_LOCATION=us-central1
# Optional: Path to service account credentials JSON file (alternative to API key)
GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account-credentials.json

1
.nvmrc Normal file
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@@ -0,0 +1 @@
22

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

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

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.taskmaster/config.json Normal file
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@@ -0,0 +1,32 @@
{
"models": {
"main": {
"provider": "anthropic",
"modelId": "claude-sonnet-4-20250514",
"maxTokens": 50000,
"temperature": 0.2
},
"research": {
"provider": "perplexity",
"modelId": "sonar-pro",
"maxTokens": 8700,
"temperature": 0.1
},
"fallback": {
"provider": "anthropic",
"modelId": "claude-3-7-sonnet-20250219",
"maxTokens": 128000,
"temperature": 0.2
}
},
"global": {
"logLevel": "info",
"debug": false,
"defaultSubtasks": 5,
"defaultPriority": "medium",
"projectName": "Taskmaster",
"ollamaBaseURL": "http://localhost:11434/api",
"userId": "1234567890",
"azureBaseURL": "https://your-endpoint.azure.com/"
}
}

528
.taskmaster/docs/prd.txt Normal file
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@@ -0,0 +1,528 @@
# Claude Task Master - Product Requirements Document
<PRD>
# Technical Architecture
## System Components
1. **Task Management Core**
- Tasks.json file structure (single source of truth)
- Task model with dependencies, priorities, and metadata
- Task state management system
- Task file generation subsystem
2. **AI Integration Layer**
- Anthropic Claude API integration
- Perplexity API integration (optional)
- Prompt engineering components
- Response parsing and processing
3. **Command Line Interface**
- Command parsing and execution
- Interactive user input handling
- Display and formatting utilities
- Status reporting and feedback system
4. **Cursor AI Integration**
- Cursor rules documentation
- Agent interaction patterns
- Workflow guideline specifications
## Data Models
### Task Model
```json
{
"id": 1,
"title": "Task Title",
"description": "Brief task description",
"status": "pending|done|deferred",
"dependencies": [0],
"priority": "high|medium|low",
"details": "Detailed implementation instructions",
"testStrategy": "Verification approach details",
"subtasks": [
{
"id": 1,
"title": "Subtask Title",
"description": "Subtask description",
"status": "pending|done|deferred",
"dependencies": [],
"acceptanceCriteria": "Verification criteria"
}
]
}
```
### Tasks Collection Model
```json
{
"meta": {
"projectName": "Project Name",
"version": "1.0.0",
"prdSource": "path/to/prd.txt",
"createdAt": "ISO-8601 timestamp",
"updatedAt": "ISO-8601 timestamp"
},
"tasks": [
// Array of Task objects
]
}
```
### Task File 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>
# Subtasks:
1. <subtask title> - <subtask description>
```
## APIs and Integrations
1. **Anthropic Claude API**
- Authentication via API key
- Prompt construction and streaming
- Response parsing and extraction
- Error handling and retries
2. **Perplexity API (via OpenAI client)**
- Authentication via API key
- Research-oriented prompt construction
- Enhanced contextual response handling
- Fallback mechanisms to Claude
3. **File System API**
- Reading/writing tasks.json
- Managing individual task files
- Command execution logging
- Debug logging system
## Infrastructure Requirements
1. **Node.js Runtime**
- Version 14.0.0 or higher
- ES Module support
- File system access rights
- Command execution capabilities
2. **Configuration Management**
- Environment variable handling
- .env file support
- Configuration validation
- Sensible defaults with overrides
3. **Development Environment**
- Git repository
- NPM package management
- Cursor editor integration
- Command-line terminal access
# Development Roadmap
## Phase 1: Core Task Management System
1. **Task Data Structure**
- Design and implement the tasks.json structure
- Create task model validation
- Implement basic task operations (create, read, update)
- Develop file system interactions
2. **Command Line Interface Foundation**
- Implement command parsing with Commander.js
- Create help documentation
- Implement colorized console output
- Add logging system with configurable levels
3. **Basic Task Operations**
- Implement task listing functionality
- Create task status update capability
- Add dependency tracking
- Implement priority management
4. **Task File Generation**
- Create task file templates
- Implement generation from tasks.json
- Add bi-directional synchronization
- Implement proper file naming and organization
## Phase 2: AI Integration
1. **Claude API Integration**
- Implement API authentication
- Create prompt templates for PRD parsing
- Design response handlers
- Add error management and retries
2. **PRD Parsing System**
- Implement PRD file reading
- Create PRD to task conversion logic
- Add intelligent dependency inference
- Implement priority assignment logic
3. **Task Expansion With Claude**
- Create subtask generation prompts
- Implement subtask creation workflow
- Add context-aware expansion capabilities
- Implement parent-child relationship management
4. **Implementation Drift Handling**
- Add capability to update future tasks
- Implement task rewriting based on new context
- Create dependency chain updates
- Preserve completed work while updating future tasks
## Phase 3: Advanced Features
1. **Perplexity Integration**
- Implement Perplexity API authentication
- Create research-oriented prompts
- Add fallback to Claude when unavailable
- Implement response quality comparison logic
2. **Research-Backed Subtask Generation**
- Create specialized research prompts
- Implement context enrichment
- Add domain-specific knowledge incorporation
- Create more detailed subtask generation
3. **Batch Operations**
- Implement multi-task status updates
- Add bulk subtask generation
- Create task filtering and querying
- Implement advanced dependency management
4. **Project Initialization**
- Create project templating system
- Implement interactive setup
- Add environment configuration
- Create documentation generation
## Phase 4: Cursor AI Integration
1. **Cursor Rules Implementation**
- Create dev_workflow.mdc documentation
- Implement cursor_rules.mdc
- Add self_improve.mdc
- Design rule integration documentation
2. **Agent Workflow Guidelines**
- Document task discovery workflow
- Create task selection guidelines
- Implement implementation guidance
- Add verification procedures
3. **Agent Command Integration**
- Document command syntax for agents
- Create example interactions
- Implement agent response patterns
- Add context management for agents
4. **User Documentation**
- Create detailed README
- Add scripts documentation
- Implement example workflows
- Create troubleshooting guides
# Logical Dependency Chain
## Foundation Layer
1. **Task Data Structure**
- Must be implemented first as all other functionality depends on this
- Defines the core data model for the entire system
- Establishes the single source of truth concept
2. **Command Line Interface**
- Built on top of the task data structure
- Provides the primary user interaction mechanism
- Required for all subsequent operations to be accessible
3. **Basic Task Operations**
- Depends on both task data structure and CLI
- Provides the fundamental operations for task management
- Enables the minimal viable workflow
## Functional Layer
4. **Task File Generation**
- Depends on task data structure and basic operations
- Creates the individual task files for reference
- Enables the file-based workflow complementing tasks.json
5. **Claude API Integration**
- Independent of most previous components but needs the task data structure
- Provides the AI capabilities that enhance the system
- Gateway to advanced task generation features
6. **PRD Parsing System**
- Depends on Claude API integration and task data structure
- Enables the initial task generation workflow
- Creates the starting point for new projects
## Enhancement Layer
7. **Task Expansion With Claude**
- Depends on Claude API integration and basic task operations
- Enhances existing tasks with more detailed subtasks
- Improves the implementation guidance
8. **Implementation Drift Handling**
- Depends on Claude API integration and task operations
- Addresses a key challenge in AI-driven development
- Maintains the relevance of task planning as implementation evolves
9. **Perplexity Integration**
- Can be developed in parallel with other features after Claude integration
- Enhances the quality of generated content
- Provides research-backed improvements
## Advanced Layer
10. **Research-Backed Subtask Generation**
- Depends on Perplexity integration and task expansion
- Provides higher quality, more contextual subtasks
- Enhances the value of the task breakdown
11. **Batch Operations**
- Depends on basic task operations
- Improves efficiency for managing multiple tasks
- Quality-of-life enhancement for larger projects
12. **Project Initialization**
- Depends on most previous components being stable
- Provides a smooth onboarding experience
- Creates a complete project setup in one step
## Integration Layer
13. **Cursor Rules Implementation**
- Can be developed in parallel after basic functionality
- Provides the guidance for Cursor AI agent
- Enhances the AI-driven workflow
14. **Agent Workflow Guidelines**
- Depends on Cursor rules implementation
- Structures how the agent interacts with the system
- Ensures consistent agent behavior
15. **Agent Command Integration**
- Depends on agent workflow guidelines
- Provides specific command patterns for the agent
- Optimizes the agent-user interaction
16. **User Documentation**
- Should be developed alongside all features
- Must be completed before release
- Ensures users can effectively use the system
# Risks and Mitigations
## Technical Challenges
### API Reliability
**Risk**: Anthropic or Perplexity API could have downtime, rate limiting, or breaking changes.
**Mitigation**:
- Implement robust error handling with exponential backoff
- Add fallback mechanisms (Claude fallback for Perplexity)
- Cache important responses to reduce API dependency
- Support offline mode for critical functions
### Model Output Variability
**Risk**: AI models may produce inconsistent or unexpected outputs.
**Mitigation**:
- Design robust prompt templates with strict output formatting requirements
- Implement response validation and error detection
- Add self-correction mechanisms and retries with improved prompts
- Allow manual editing of generated content
### Node.js Version Compatibility
**Risk**: Differences in Node.js versions could cause unexpected behavior.
**Mitigation**:
- Clearly document minimum Node.js version requirements
- Use transpilers if needed for compatibility
- Test across multiple Node.js versions
- Handle version-specific features gracefully
## MVP Definition
### Feature Prioritization
**Risk**: Including too many features in the MVP could delay release and adoption.
**Mitigation**:
- Define MVP as core task management + basic Claude integration
- Ensure each phase delivers a complete, usable product
- Implement feature flags for easy enabling/disabling of features
- Get early user feedback to validate feature importance
### Scope Creep
**Risk**: The project could expand beyond its original intent, becoming too complex.
**Mitigation**:
- Maintain a strict definition of what the tool is and isn't
- Focus on task management for AI-driven development
- Evaluate new features against core value proposition
- Implement extensibility rather than building every feature
### User Expectations
**Risk**: Users might expect a full project management solution rather than a task tracking system.
**Mitigation**:
- Clearly communicate the tool's purpose and limitations
- Provide integration points with existing project management tools
- Focus on the unique value of AI-driven development
- Document specific use cases and example workflows
## Resource Constraints
### Development Capacity
**Risk**: Limited development resources could delay implementation.
**Mitigation**:
- Phase implementation to deliver value incrementally
- Focus on core functionality first
- Leverage open source libraries where possible
- Design for extensibility to allow community contributions
### AI Cost Management
**Risk**: Excessive API usage could lead to high costs.
**Mitigation**:
- Implement token usage tracking and reporting
- Add configurable limits to prevent unexpected costs
- Cache responses where appropriate
- Optimize prompts for token efficiency
- Support local LLM options in the future
### Documentation Overhead
**Risk**: Complexity of the system requires extensive documentation that is time-consuming to maintain.
**Mitigation**:
- Use AI to help generate and maintain documentation
- Create self-documenting commands and features
- Implement progressive documentation (basic to advanced)
- Build help directly into the CLI
# Appendix
## AI Prompt Engineering Specifications
### PRD Parsing Prompt Structure
```
You are assisting with transforming a Product Requirements Document (PRD) into a structured set of development tasks.
Given the following PRD, create a comprehensive list of development tasks that would be needed to implement the described product.
For each task:
1. Assign a short, descriptive title
2. Write a concise description
3. Identify dependencies (which tasks must be completed before this one)
4. Assign a priority (high, medium, low)
5. Include detailed implementation notes
6. Describe a test strategy to verify completion
Structure the tasks in a logical order of implementation.
PRD:
{prd_content}
```
### Task Expansion Prompt Structure
```
You are helping to break down a development task into more manageable subtasks.
Main task:
Title: {task_title}
Description: {task_description}
Details: {task_details}
Please create {num_subtasks} specific subtasks that together would accomplish this main task.
For each subtask, provide:
1. A clear, actionable title
2. A concise description
3. Any dependencies on other subtasks
4. Specific acceptance criteria to verify completion
Additional context:
{additional_context}
```
### Research-Backed Expansion Prompt Structure
```
You are a technical researcher and developer helping to break down a software development task into detailed, well-researched subtasks.
Main task:
Title: {task_title}
Description: {task_description}
Details: {task_details}
Research the latest best practices, technologies, and implementation patterns for this type of task. Then create {num_subtasks} specific, actionable subtasks that together would accomplish the main task.
For each subtask:
1. Provide a clear, specific title
2. Write a detailed description including technical approach
3. Identify dependencies on other subtasks
4. Include specific acceptance criteria
5. Reference any relevant libraries, tools, or resources that should be used
Consider security, performance, maintainability, and user experience in your recommendations.
```
## Task File System Specification
### Directory Structure
```
/
├── .cursor/
│ └── rules/
│ ├── dev_workflow.mdc
│ ├── cursor_rules.mdc
│ └── self_improve.mdc
├── scripts/
│ ├── dev.js
│ └── README.md
├── tasks/
│ ├── task_001.txt
│ ├── task_002.txt
│ └── ...
├── .env
├── .env.example
├── .gitignore
├── package.json
├── README.md
└── tasks.json
```
### Task ID Specification
- Main tasks: Sequential integers (1, 2, 3, ...)
- Subtasks: Parent ID + dot + sequential integer (1.1, 1.2, 2.1, ...)
- ID references: Used in dependencies, command parameters
- ID ordering: Implies suggested implementation order
## Command-Line Interface Specification
### Global Options
- `--help`: Display help information
- `--version`: Display version information
- `--file=<file>`: Specify an alternative tasks.json file
- `--quiet`: Reduce output verbosity
- `--debug`: Increase output verbosity
- `--json`: Output in JSON format (for programmatic use)
### Command Structure
- `node scripts/dev.js <command> [options]`
- All commands operate on tasks.json by default
- Commands follow consistent parameter naming
- Common parameter styles: `--id=<id>`, `--status=<status>`, `--prompt="<text>"`
- Boolean flags: `--all`, `--force`, `--with-subtasks`
## API Integration Specifications
### Anthropic API Configuration
- Authentication: ANTHROPIC_API_KEY environment variable
- Model selection: MODEL environment variable
- Default model: claude-3-7-sonnet-20250219
- Maximum tokens: MAX_TOKENS environment variable (default: 4000)
- Temperature: TEMPERATURE environment variable (default: 0.7)
### Perplexity API Configuration
- Authentication: PERPLEXITY_API_KEY environment variable
- Model selection: PERPLEXITY_MODEL environment variable
- Default model: sonar-medium-online
- Connection: Via OpenAI client
- Fallback: Use Claude if Perplexity unavailable
</PRD>

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@@ -0,0 +1,357 @@
{
"meta": {
"generatedAt": "2025-05-22T05:48:33.026Z",
"tasksAnalyzed": 6,
"totalTasks": 88,
"analysisCount": 43,
"thresholdScore": 5,
"projectName": "Taskmaster",
"usedResearch": true
},
"complexityAnalysis": [
{
"taskId": 24,
"taskTitle": "Implement AI-Powered Test Generation Command",
"complexityScore": 7,
"recommendedSubtasks": 5,
"expansionPrompt": "Break down the implementation of the AI-powered test generation command into detailed subtasks covering: command structure setup, AI prompt engineering, test file generation logic, integration with Claude API, and comprehensive error handling.",
"reasoning": "This task involves complex integration with an AI service (Claude), requires sophisticated prompt engineering, and needs to generate structured code files. The existing 3 subtasks are a good start but could be expanded to include more detailed steps for AI integration, error handling, and test file formatting."
},
{
"taskId": 26,
"taskTitle": "Implement Context Foundation for AI Operations",
"complexityScore": 6,
"recommendedSubtasks": 4,
"expansionPrompt": "The current 4 subtasks for implementing the context foundation appear comprehensive. Consider if any additional subtasks are needed for testing, documentation, or integration with existing systems.",
"reasoning": "This task involves creating a foundation for context integration with several well-defined components. The existing 4 subtasks cover the main implementation areas (context-file flag, cursor rules integration, context extraction utility, and command handler updates). The complexity is moderate as it requires careful integration with existing systems but has clear requirements."
},
{
"taskId": 27,
"taskTitle": "Implement Context Enhancements for AI Operations",
"complexityScore": 7,
"recommendedSubtasks": 4,
"expansionPrompt": "The current 4 subtasks for implementing context enhancements appear well-structured. Consider if any additional subtasks are needed for testing, documentation, or performance optimization.",
"reasoning": "This task builds upon the foundation from Task #26 and adds more sophisticated context handling features. The 4 existing subtasks cover the main implementation areas (code context extraction, task history context, PRD context integration, and context formatting). The complexity is higher than the foundation task due to the need for intelligent context selection and optimization."
},
{
"taskId": 28,
"taskTitle": "Implement Advanced ContextManager System",
"complexityScore": 8,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing the advanced ContextManager system appear comprehensive. Consider if any additional subtasks are needed for testing, documentation, or backward compatibility with previous context implementations.",
"reasoning": "This task represents the most complex phase of the context implementation, requiring a sophisticated class design, optimization algorithms, and integration with multiple systems. The 5 existing subtasks cover the core implementation areas, but the complexity is high due to the need for intelligent context prioritization, token management, and performance monitoring."
},
{
"taskId": 40,
"taskTitle": "Implement 'plan' Command for Task Implementation Planning",
"complexityScore": 5,
"recommendedSubtasks": 4,
"expansionPrompt": "The current 4 subtasks for implementing the 'plan' command appear well-structured. Consider if any additional subtasks are needed for testing, documentation, or integration with existing task management workflows.",
"reasoning": "This task involves creating a new command that leverages AI to generate implementation plans. The existing 4 subtasks cover the main implementation areas (retrieving task content, generating plans with AI, formatting in XML, and error handling). The complexity is moderate as it builds on existing patterns for task updates but requires careful AI integration."
},
{
"taskId": 41,
"taskTitle": "Implement Visual Task Dependency Graph in Terminal",
"complexityScore": 8,
"recommendedSubtasks": 10,
"expansionPrompt": "The current 10 subtasks for implementing the visual task dependency graph appear comprehensive. Consider if any additional subtasks are needed for performance optimization with large graphs or additional visualization options.",
"reasoning": "This task involves creating a sophisticated visualization system for terminal display, which is inherently complex due to layout algorithms, ASCII/Unicode rendering, and handling complex dependency relationships. The 10 existing subtasks cover all major aspects of implementation, from CLI interface to accessibility features."
},
{
"taskId": 42,
"taskTitle": "Implement MCP-to-MCP Communication Protocol",
"complexityScore": 9,
"recommendedSubtasks": 8,
"expansionPrompt": "The current 8 subtasks for implementing the MCP-to-MCP communication protocol appear well-structured. Consider if any additional subtasks are needed for security hardening, performance optimization, or comprehensive documentation.",
"reasoning": "This task involves designing and implementing a complex communication protocol between different MCP tools and servers. It requires sophisticated adapter patterns, client-server architecture, and handling of multiple operational modes. The complexity is very high due to the need for standardization, security, and backward compatibility."
},
{
"taskId": 44,
"taskTitle": "Implement Task Automation with Webhooks and Event Triggers",
"complexityScore": 8,
"recommendedSubtasks": 7,
"expansionPrompt": "The current 7 subtasks for implementing task automation with webhooks appear comprehensive. Consider if any additional subtasks are needed for security testing, rate limiting implementation, or webhook monitoring tools.",
"reasoning": "This task involves creating a sophisticated event system with webhooks for integration with external services. The complexity is high due to the need for secure authentication, reliable delivery mechanisms, and handling of various webhook formats and protocols. The existing subtasks cover the main implementation areas but security and monitoring could be emphasized more."
},
{
"taskId": 45,
"taskTitle": "Implement GitHub Issue Import Feature",
"complexityScore": 6,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing the GitHub issue import feature appear well-structured. Consider if any additional subtasks are needed for handling GitHub API rate limiting, caching, or supporting additional issue metadata.",
"reasoning": "This task involves integrating with the GitHub API to import issues as tasks. The complexity is moderate as it requires API authentication, data mapping, and error handling. The existing 5 subtasks cover the main implementation areas from design to end-to-end implementation."
},
{
"taskId": 46,
"taskTitle": "Implement ICE Analysis Command for Task Prioritization",
"complexityScore": 7,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing the ICE analysis command appear comprehensive. Consider if any additional subtasks are needed for visualization of ICE scores or integration with other prioritization methods.",
"reasoning": "This task involves creating an AI-powered analysis system for task prioritization using the ICE methodology. The complexity is high due to the need for sophisticated scoring algorithms, AI integration, and report generation. The existing subtasks cover the main implementation areas from algorithm design to integration with existing systems."
},
{
"taskId": 47,
"taskTitle": "Enhance Task Suggestion Actions Card Workflow",
"complexityScore": 6,
"recommendedSubtasks": 6,
"expansionPrompt": "The current 6 subtasks for enhancing the task suggestion actions card workflow appear well-structured. Consider if any additional subtasks are needed for user testing, accessibility improvements, or performance optimization.",
"reasoning": "This task involves redesigning the UI workflow for task expansion and management. The complexity is moderate as it requires careful UX design and state management but builds on existing components. The 6 existing subtasks cover the main implementation areas from design to testing."
},
{
"taskId": 48,
"taskTitle": "Refactor Prompts into Centralized Structure",
"complexityScore": 4,
"recommendedSubtasks": 3,
"expansionPrompt": "The current 3 subtasks for refactoring prompts into a centralized structure appear appropriate. Consider if any additional subtasks are needed for prompt versioning, documentation, or testing.",
"reasoning": "This task involves a straightforward refactoring to improve code organization. The complexity is relatively low as it primarily involves moving code rather than creating new functionality. The 3 existing subtasks cover the main implementation areas from directory structure to integration."
},
{
"taskId": 49,
"taskTitle": "Implement Code Quality Analysis Command",
"complexityScore": 8,
"recommendedSubtasks": 6,
"expansionPrompt": "The current 6 subtasks for implementing the code quality analysis command appear comprehensive. Consider if any additional subtasks are needed for performance optimization with large codebases or integration with existing code quality tools.",
"reasoning": "This task involves creating a sophisticated code analysis system with pattern recognition, best practice verification, and AI-powered recommendations. The complexity is high due to the need for code parsing, complex analysis algorithms, and integration with AI services. The existing subtasks cover the main implementation areas from algorithm design to user interface."
},
{
"taskId": 50,
"taskTitle": "Implement Test Coverage Tracking System by Task",
"complexityScore": 9,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing the test coverage tracking system appear well-structured. Consider if any additional subtasks are needed for integration with CI/CD systems, performance optimization, or visualization tools.",
"reasoning": "This task involves creating a complex system that maps test coverage to specific tasks and subtasks. The complexity is very high due to the need for sophisticated data structures, integration with coverage tools, and AI-powered test generation. The existing subtasks are comprehensive and cover the main implementation areas from data structure design to AI integration."
},
{
"taskId": 51,
"taskTitle": "Implement Perplexity Research Command",
"complexityScore": 6,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing the Perplexity research command appear comprehensive. Consider if any additional subtasks are needed for caching optimization, result formatting, or integration with other research tools.",
"reasoning": "This task involves creating a new command that integrates with the Perplexity AI API for research. The complexity is moderate as it requires API integration, context extraction, and result formatting. The 5 existing subtasks cover the main implementation areas from API client to caching system."
},
{
"taskId": 52,
"taskTitle": "Implement Task Suggestion Command for CLI",
"complexityScore": 6,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing the task suggestion command appear well-structured. Consider if any additional subtasks are needed for suggestion quality evaluation, user feedback collection, or integration with existing task workflows.",
"reasoning": "This task involves creating a new CLI command that generates contextually relevant task suggestions using AI. The complexity is moderate as it requires AI integration, context collection, and interactive CLI interfaces. The existing subtasks cover the main implementation areas from data collection to user interface."
},
{
"taskId": 53,
"taskTitle": "Implement Subtask Suggestion Feature for Parent Tasks",
"complexityScore": 6,
"recommendedSubtasks": 6,
"expansionPrompt": "The current 6 subtasks for implementing the subtask suggestion feature appear comprehensive. Consider if any additional subtasks are needed for suggestion quality metrics, user feedback collection, or performance optimization.",
"reasoning": "This task involves creating a feature that suggests contextually relevant subtasks for parent tasks. The complexity is moderate as it builds on existing task management systems but requires sophisticated AI integration and context analysis. The 6 existing subtasks cover the main implementation areas from validation to testing."
},
{
"taskId": 55,
"taskTitle": "Implement Positional Arguments Support for CLI Commands",
"complexityScore": 5,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing positional arguments support appear well-structured. Consider if any additional subtasks are needed for backward compatibility testing, documentation updates, or user experience improvements.",
"reasoning": "This task involves modifying the command parsing logic to support positional arguments alongside the existing flag-based syntax. The complexity is moderate as it requires careful handling of different argument styles and edge cases. The 5 existing subtasks cover the main implementation areas from analysis to documentation."
},
{
"taskId": 57,
"taskTitle": "Enhance Task-Master CLI User Experience and Interface",
"complexityScore": 7,
"recommendedSubtasks": 6,
"expansionPrompt": "The current 6 subtasks for enhancing the CLI user experience appear comprehensive. Consider if any additional subtasks are needed for accessibility testing, internationalization, or performance optimization.",
"reasoning": "This task involves a significant overhaul of the CLI interface to improve user experience. The complexity is high due to the breadth of changes (logging, visual elements, interactive components, etc.) and the need for consistent design across all commands. The 6 existing subtasks cover the main implementation areas from log management to help systems."
},
{
"taskId": 60,
"taskTitle": "Implement Mentor System with Round-Table Discussion Feature",
"complexityScore": 8,
"recommendedSubtasks": 7,
"expansionPrompt": "The current 7 subtasks for implementing the mentor system appear well-structured. Consider if any additional subtasks are needed for mentor personality consistency, discussion quality evaluation, or performance optimization with multiple mentors.",
"reasoning": "This task involves creating a sophisticated mentor simulation system with round-table discussions. The complexity is high due to the need for personality simulation, complex LLM integration, and structured discussion management. The 7 existing subtasks cover the main implementation areas from architecture to testing."
},
{
"taskId": 62,
"taskTitle": "Add --simple Flag to Update Commands for Direct Text Input",
"complexityScore": 4,
"recommendedSubtasks": 8,
"expansionPrompt": "The current 8 subtasks for implementing the --simple flag appear comprehensive. Consider if any additional subtasks are needed for user experience testing or documentation updates.",
"reasoning": "This task involves adding a simple flag option to bypass AI processing for updates. The complexity is relatively low as it primarily involves modifying existing command handlers and adding a flag. The 8 existing subtasks are very detailed and cover all aspects of implementation from command parsing to testing."
},
{
"taskId": 63,
"taskTitle": "Add pnpm Support for the Taskmaster Package",
"complexityScore": 5,
"recommendedSubtasks": 8,
"expansionPrompt": "The current 8 subtasks for adding pnpm support appear comprehensive. Consider if any additional subtasks are needed for CI/CD integration, performance comparison, or documentation updates.",
"reasoning": "This task involves ensuring the package works correctly with pnpm as an alternative package manager. The complexity is moderate as it requires careful testing of installation processes and scripts across different environments. The 8 existing subtasks cover all major aspects from documentation to binary verification."
},
{
"taskId": 64,
"taskTitle": "Add Yarn Support for Taskmaster Installation",
"complexityScore": 5,
"recommendedSubtasks": 9,
"expansionPrompt": "The current 9 subtasks for adding Yarn support appear comprehensive. Consider if any additional subtasks are needed for performance testing, CI/CD integration, or compatibility with different Yarn versions.",
"reasoning": "This task involves ensuring the package works correctly with Yarn as an alternative package manager. The complexity is moderate as it requires careful testing of installation processes and scripts across different environments. The 9 existing subtasks are very detailed and cover all aspects from configuration to testing."
},
{
"taskId": 65,
"taskTitle": "Add Bun Support for Taskmaster Installation",
"complexityScore": 6,
"recommendedSubtasks": 6,
"expansionPrompt": "The current 6 subtasks for adding Bun support appear well-structured. Consider if any additional subtasks are needed for handling Bun-specific issues, performance testing, or documentation updates.",
"reasoning": "This task involves adding support for the newer Bun package manager. The complexity is slightly higher than the other package manager tasks due to Bun's differences from Node.js and potential compatibility issues. The 6 existing subtasks cover the main implementation areas from research to documentation."
},
{
"taskId": 67,
"taskTitle": "Add CLI JSON output and Cursor keybindings integration",
"complexityScore": 5,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing JSON output and Cursor keybindings appear well-structured. Consider if any additional subtasks are needed for testing across different operating systems, documentation updates, or user experience improvements.",
"reasoning": "This task involves two distinct features: adding JSON output to CLI commands and creating a keybindings installation command. The complexity is moderate as it requires careful handling of different output formats and OS-specific file paths. The 5 existing subtasks cover the main implementation areas for both features."
},
{
"taskId": 68,
"taskTitle": "Ability to create tasks without parsing PRD",
"complexityScore": 3,
"recommendedSubtasks": 2,
"expansionPrompt": "The current 2 subtasks for implementing task creation without PRD appear appropriate. Consider if any additional subtasks are needed for validation, error handling, or integration with existing task management workflows.",
"reasoning": "This task involves a relatively simple modification to allow task creation without requiring a PRD document. The complexity is low as it primarily involves creating a form interface and saving functionality. The 2 existing subtasks cover the main implementation areas of UI design and data saving."
},
{
"taskId": 72,
"taskTitle": "Implement PDF Generation for Project Progress and Dependency Overview",
"complexityScore": 7,
"recommendedSubtasks": 6,
"expansionPrompt": "The current 6 subtasks for implementing PDF generation appear comprehensive. Consider if any additional subtasks are needed for handling large projects, additional visualization options, or integration with existing reporting tools.",
"reasoning": "This task involves creating a feature to generate PDF reports of project progress and dependency visualization. The complexity is high due to the need for PDF generation, data collection, and visualization integration. The 6 existing subtasks cover the main implementation areas from library selection to export options."
},
{
"taskId": 75,
"taskTitle": "Integrate Google Search Grounding for Research Role",
"complexityScore": 5,
"recommendedSubtasks": 4,
"expansionPrompt": "The current 4 subtasks for integrating Google Search Grounding appear well-structured. Consider if any additional subtasks are needed for testing with different query types, error handling, or performance optimization.",
"reasoning": "This task involves updating the AI service layer to enable Google Search Grounding for research roles. The complexity is moderate as it requires careful integration with the existing AI service architecture and conditional logic. The 4 existing subtasks cover the main implementation areas from service layer modification to testing."
},
{
"taskId": 76,
"taskTitle": "Develop E2E Test Framework for Taskmaster MCP Server (FastMCP over stdio)",
"complexityScore": 8,
"recommendedSubtasks": 7,
"expansionPrompt": "The current 7 subtasks for developing the E2E test framework appear comprehensive. Consider if any additional subtasks are needed for test result reporting, CI/CD integration, or performance benchmarking.",
"reasoning": "This task involves creating a sophisticated end-to-end testing framework for the MCP server. The complexity is high due to the need for subprocess management, protocol handling, and robust test case definition. The 7 existing subtasks cover the main implementation areas from architecture to documentation."
},
{
"taskId": 77,
"taskTitle": "Implement AI Usage Telemetry for Taskmaster (with external analytics endpoint)",
"complexityScore": 7,
"recommendedSubtasks": 18,
"expansionPrompt": "The current 18 subtasks for implementing AI usage telemetry appear very comprehensive. Consider if any additional subtasks are needed for security hardening, privacy compliance, or user feedback collection.",
"reasoning": "This task involves creating a telemetry system to track AI usage metrics. The complexity is high due to the need for secure data transmission, comprehensive data collection, and integration across multiple commands. The 18 existing subtasks are extremely detailed and cover all aspects of implementation from core utility to provider-specific updates."
},
{
"taskId": 80,
"taskTitle": "Implement Unique User ID Generation and Storage During Installation",
"complexityScore": 4,
"recommendedSubtasks": 5,
"expansionPrompt": "The current 5 subtasks for implementing unique user ID generation appear well-structured. Consider if any additional subtasks are needed for privacy compliance, security auditing, or integration with the telemetry system.",
"reasoning": "This task involves generating and storing a unique user identifier during installation. The complexity is relatively low as it primarily involves UUID generation and configuration file management. The 5 existing subtasks cover the main implementation areas from script structure to documentation."
},
{
"taskId": 81,
"taskTitle": "Task #81: Implement Comprehensive Local Telemetry System with Future Server Integration Capability",
"complexityScore": 8,
"recommendedSubtasks": 6,
"expansionPrompt": "The current 6 subtasks for implementing the comprehensive local telemetry system appear well-structured. Consider if any additional subtasks are needed for data migration, storage optimization, or visualization tools.",
"reasoning": "This task involves expanding the telemetry system to capture additional metrics and implement local storage with future server integration capability. The complexity is high due to the breadth of data collection, storage requirements, and privacy considerations. The 6 existing subtasks cover the main implementation areas from data collection to user-facing benefits."
},
{
"taskId": 82,
"taskTitle": "Update supported-models.json with token limit fields",
"complexityScore": 3,
"recommendedSubtasks": 1,
"expansionPrompt": "This task appears straightforward enough to be implemented without further subtasks. Focus on researching accurate token limit values for each model and ensuring backward compatibility.",
"reasoning": "This task involves a simple update to the supported-models.json file to include new token limit fields. The complexity is low as it primarily involves research and data entry. No subtasks are necessary as the task is well-defined and focused."
},
{
"taskId": 83,
"taskTitle": "Update config-manager.js defaults and getters",
"complexityScore": 4,
"recommendedSubtasks": 1,
"expansionPrompt": "This task appears straightforward enough to be implemented without further subtasks. Focus on updating the DEFAULTS object and related getter functions while maintaining backward compatibility.",
"reasoning": "This task involves updating the config-manager.js module to replace maxTokens with more specific token limit fields. The complexity is relatively low as it primarily involves modifying existing code rather than creating new functionality. No subtasks are necessary as the task is well-defined and focused."
},
{
"taskId": 84,
"taskTitle": "Implement token counting utility",
"complexityScore": 5,
"recommendedSubtasks": 1,
"expansionPrompt": "This task appears well-defined enough to be implemented without further subtasks. Focus on implementing accurate token counting for different models and proper fallback mechanisms.",
"reasoning": "This task involves creating a utility function to count tokens for different AI models. The complexity is moderate as it requires integration with the tiktoken library and handling different tokenization schemes. No subtasks are necessary as the task is well-defined and focused."
},
{
"taskId": 69,
"taskTitle": "Enhance Analyze Complexity for Specific Task IDs",
"complexityScore": 7,
"recommendedSubtasks": 6,
"expansionPrompt": "Break down the task 'Enhance Analyze Complexity for Specific Task IDs' into 6 subtasks focusing on: 1) Core logic modification to accept ID parameters, 2) Report merging functionality, 3) CLI interface updates, 4) MCP tool integration, 5) Documentation updates, and 6) Comprehensive testing across all components.",
"reasoning": "This task involves modifying existing functionality across multiple components (core logic, CLI, MCP) with complex logic for filtering tasks and merging reports. The implementation requires careful handling of different parameter combinations and edge cases. The task has interdependent components that need to work together seamlessly, and the report merging functionality adds significant complexity."
},
{
"taskId": 70,
"taskTitle": "Implement 'diagram' command for Mermaid diagram generation",
"complexityScore": 6,
"recommendedSubtasks": 5,
"expansionPrompt": "Break down the 'diagram' command implementation into 5 subtasks: 1) Command interface and parameter handling, 2) Task data extraction and transformation to Mermaid syntax, 3) Diagram rendering with status color coding, 4) Output formatting and file export functionality, and 5) Error handling and edge case management.",
"reasoning": "This task requires implementing a new feature rather than modifying existing code, which reduces complexity from integration challenges. However, it involves working with visualization logic, dependency mapping, and multiple output formats. The color coding based on status and handling of dependency relationships adds moderate complexity. The task is well-defined but requires careful attention to diagram formatting and error handling."
},
{
"taskId": 85,
"taskTitle": "Update ai-services-unified.js for dynamic token limits",
"complexityScore": 7,
"recommendedSubtasks": 5,
"expansionPrompt": "Break down the update of ai-services-unified.js for dynamic token limits into subtasks such as: (1) Import and integrate the token counting utility, (2) Refactor _unifiedServiceRunner to calculate and enforce dynamic token limits, (3) Update error handling for token limit violations, (4) Add and verify logging for token usage, (5) Write and execute tests for various prompt and model scenarios.",
"reasoning": "This task involves significant code changes to a core function, integration of a new utility, dynamic logic for multiple models, and robust error handling. It also requires comprehensive testing for edge cases and integration, making it moderately complex and best managed by splitting into focused subtasks."
},
{
"taskId": 86,
"taskTitle": "Update .taskmasterconfig schema and user guide",
"complexityScore": 6,
"recommendedSubtasks": 4,
"expansionPrompt": "Expand this task into subtasks: (1) Draft a migration guide for users, (2) Update user documentation to explain new config fields, (3) Modify schema validation logic in config-manager.js, (4) Test and validate backward compatibility and error messaging.",
"reasoning": "The task spans documentation, schema changes, migration guidance, and validation logic. While not algorithmically complex, it requires careful coordination and thorough testing to ensure a smooth user transition and robust validation."
},
{
"taskId": 87,
"taskTitle": "Implement validation and error handling",
"complexityScore": 5,
"recommendedSubtasks": 4,
"expansionPrompt": "Decompose this task into: (1) Add validation logic for model and config loading, (2) Implement error handling and fallback mechanisms, (3) Enhance logging and reporting for token usage, (4) Develop helper functions for configuration suggestions and improvements.",
"reasoning": "This task is primarily about adding validation, error handling, and logging. While important for robustness, the logic is straightforward and can be modularized into a few clear subtasks."
},
{
"taskId": 89,
"taskTitle": "Introduce Prioritize Command with Enhanced Priority Levels",
"complexityScore": 6,
"recommendedSubtasks": 5,
"expansionPrompt": "Expand this task into: (1) Implement the prioritize command with all required flags and shorthands, (2) Update CLI output and help documentation for new priority levels, (3) Ensure backward compatibility with existing commands, (4) Add error handling for invalid inputs, (5) Write and run tests for all command scenarios.",
"reasoning": "This CLI feature requires command parsing, updating internal logic for new priority levels, documentation, and robust error handling. The complexity is moderate due to the need for backward compatibility and comprehensive testing."
},
{
"taskId": 90,
"taskTitle": "Implement Subtask Progress Analyzer and Reporting System",
"complexityScore": 8,
"recommendedSubtasks": 6,
"expansionPrompt": "Break down the analyzer implementation into: (1) Design and implement progress tracking logic, (2) Develop status validation and issue detection, (3) Build the reporting system with multiple output formats, (4) Integrate analyzer with the existing task management system, (5) Optimize for performance and scalability, (6) Write unit, integration, and performance tests.",
"reasoning": "This is a complex, multi-faceted feature involving data analysis, reporting, integration, and performance optimization. It touches many parts of the system and requires careful design, making it one of the most complex tasks in the list."
},
{
"taskId": 91,
"taskTitle": "Implement Move Command for Tasks and Subtasks",
"complexityScore": 7,
"recommendedSubtasks": 5,
"expansionPrompt": "Expand this task into: (1) Implement move logic for tasks and subtasks, (2) Handle edge cases (invalid ids, non-existent parents, circular dependencies), (3) Update CLI to support move command with flags, (4) Ensure data integrity and update relationships, (5) Write and execute tests for various move scenarios.",
"reasoning": "Moving tasks and subtasks requires careful handling of hierarchical data, edge cases, and data integrity. The command must be robust and user-friendly, necessitating multiple focused subtasks for safe implementation."
}
]
}

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