- Hardcoded gateway endpoint to http://localhost:4444/api/v1/telemetry
- Updated credential handling to use config-based approach (not env vars)
- Added registerUserWithGateway() function for user registration/lookup
- Enhanced init.js with hosted gateway setup option and configureTelemetrySettings()
- Updated all 10 tests to reflect new architecture - all passing
- Security features maintained: sensitive data filtering, Bearer token auth
- Ready for ai-services-unified.js integration in subtask 90.3
- Implement secure telemetry submission service
- Created scripts/modules/telemetry-submission.js with submitTelemetryData function
- Implemented secure filtering: removes commandArgs and fullOutput before remote submission
- Added comprehensive validation using Zod schema for telemetry data integrity
- Implemented exponential backoff retry logic (3 attempts max) with smart retry decisions
- Added graceful error handling that never blocks execution
- Respects user opt-out preferences via config.telemetryEnabled
- Configured for localhost testing endpoint (http://localhost:4444/api/v1/telemetry) for now
- Added comprehensive test coverage with 6/6 passing tests covering all scenarios
- Includes submitTelemetryDataAsync for fire-and-forget submissions
- Implement secure telemetry capture with filtering - Enhanced ai-services-unified.js to capture commandArgs and fullOutput in telemetry - Added filterSensitiveTelemetryData() function to prevent sensitive data exposure - Updated processMCPResponseData() to filter telemetry before sending to MCP clients - Verified CLI displayAiUsageSummary() only shows safe fields - Added comprehensive test coverage with 4 passing tests - Resolved critical security issue: API keys and sensitive data now filtered from responses
- Fixed logic in moveTaskToNewId function that was incorrectly treating task-to-task moves as subtask creation instead of task replacement
- Updated moveTaskToNewId to properly handle replacing existing destination tasks instead of just placeholders
- The move command now correctly replaces destination tasks and cleans up properly without leaving duplicates
- Task Management: Moved task 93 (Google Vertex AI Provider) to position 88, Moved task 94 (Azure OpenAI Provider) to position 89, Updated task dependencies and regenerated task files, Cleaned up orphaned task files automatically
- All important validations remain in place: Prevents moving tasks to themselves, Prevents moving parent tasks to their own subtasks, Prevents circular dependencies
- Resolves the issue where moving tasks would leave both source and destination tasks in tasks.json and file system
* 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
* 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
* fix(add-task): fixes an isse in which stdout leaks out of add-task causing the mcp server to crash if used.
* chore: add changeset
---------
Co-authored-by: Ralph Khreish <35776126+Crunchyman-ralph@users.noreply.github.com>
- Enhanced get-task/show command to support comma-separated task IDs for efficient batch operations.
- New features include multiple task retrieval, smart display logic, interactive action menu with batch operations, MCP array response for AI agent efficiency, and support for mixed parent tasks and subtasks.
- Implementation includes updated CLI show command, enhanced MCP get_task tool, modified showTaskDirect function, and maintained full backward compatibility.
- Documentation updated across all relevant files.
Benefits include faster context gathering for AI agents, improved workflow with interactive batch operations, better UX with responsive layout, and enhanced API efficiency.
- Enhanced fuzzy search to include subtasks in discovery - Added interactive follow-up question functionality using inquirer
- Improved context discovery by including both tasks and subtasks
- Follow-up option for research with default to 'n' for quick workflow
- Fixed parent-to-parent task moves where original task would remain as duplicate
- Fixed moving tasks to become subtasks of empty parents (validation errors)
- Fixed moving subtasks between different parent tasks
- Improved comma-separated batch moves with proper error handling
- Updated MCP tool to use core logic instead of custom implementation
- Resolves task duplication issues and enables proper task hierarchy reorganization
Adds a new CLI command and MCP tool to reorganize tasks and subtasks within the hierarchy. Features include:
- Moving tasks between different positions in the task list
- Converting tasks to subtasks and vice versa
- Moving subtasks between parents
- Moving multiple tasks at once with comma-separated IDs
- Creating placeholder tasks when moving to new IDs
- Validation to prevent accidental data loss
This is particularly useful for resolving merge conflicts when multiple team members create tasks on different branches.
Enhance analyze-complexity to support analyzing specific tasks by ID or range:
- Add --id option for comma-separated task IDs
- Add --from/--to options for analyzing tasks within a range
- Implement intelligent merging with existing reports
- Update CLI, MCP tools, and direct functions for consistent support
- Add changeset documenting the feature
This commit implements automatic tasks.json file creation when it doesn't exist:
- When tasks.json is missing or invalid, create a new one with { tasks: [] }
- Allows adding tasks immediately after initializing a project without parsing a PRD
- Replaces error with informative feedback about file creation
- Enables smoother workflow for new projects or directories
This change improves user experience by removing the requirement to parse a PRD
before adding the first task to a newly initialized project. Closes#494
This commit significantly improves the functionality by implementing
fuzzy semantic search to find contextually relevant dependencies:
- Add Fuse.js for powerful fuzzy search capability with weighted multi-field matching
- Implement score-based relevance ranking with high/medium relevance tiers
- Enhance context generation to include detailed information about similar tasks
- Fix context shadowing issue that prevented detailed task information from
reaching the AI model
- Add informative CLI output showing semantic search results and dependency patterns
- Improve formatting of dependency information in prompts with task titles
The result is that newly created tasks are automatically placed within the correct
dependency structure without manual intervention, with the AI having much better
context about which tasks are most relevant to the new one being created.
This significantly improves the user experience by reducing the need to manually
update task dependencies after creation, all without increasing token usage or costs.
* Fix: Correct version resolution for banner and update check
Resolves issues where the tool's version was displayed as 'unknown'.
- Modified 'displayBanner' in 'ui.js' and 'checkForUpdate' in 'commands.js' to read package.json relative to their own script locations using import.meta.url.
- This ensures the correct local version is identified for both the main banner display and the update notification mechanism.
- Restored a missing closing brace in 'ui.js' to fix a SyntaxError.
* fix: refactor and cleanup
* fix: chores and cleanup and testing
* chore: cleanup
* fix: add changeset
---------
Co-authored-by: Christer Soederlund <christer.soderlund@gmail.com>
This commit introduces several improvements to AI interactions and
task management functionalities:
- AI Provider Enhancements (for Telemetry & Robustness):
- :
- Added a check in to ensure
is a string, throwing an error if not. This prevents downstream
errors (e.g., in ).
- , , :
- Standardized return structures for their respective
and functions to consistently include /
and fields. This aligns them with other providers (like
Anthropic, Google, Perplexity) for consistent telemetry data
collection, as part of implementing subtask 77.14 and similar work.
- Task Expansion ():
- Updated to be more explicit
about using an empty array for empty to
better guide AI output.
- Implemented a pre-emptive cleanup step in
to replace malformed with
before JSON parsing. This improves resilience to AI output quirks,
particularly observed with Perplexity.
- Adjusts issue in commands.js where successfulRemovals would be undefined. It's properly invoked from the result variable now.
- Updates supported models for Gemini
These changes address issues observed during E2E tests, enhance the
reliability of AI-driven task analysis and expansion, and promote
consistent telemetry data across multiple AI providers.
This commit updates to more robustly handle responses from .
Previously, the module strictly expected the AI-generated object to be nested under . This change ensures that it now first checks if itself contains the expected task data object, and then falls back to checking .
This enhancement increases compatibility with varying AI provider response structures, similar to the improvements recently made in .
This commit introduces two key improvements:
1. **Google Provider Telemetry:**
- Updated to include token usage data (, ) in the responses from and .
- This aligns the Google provider with others for consistent AI usage telemetry.
2. **Robust AI Object Response Handling:**
- Modified to more flexibly handle responses from .
- The add-task module now check for the AI-generated object in both and , improving compatibility with different AI provider response structures (e.g., Gemini).
These changes enhance the reliability of AI interactions, particularly with the Google provider, and ensure accurate telemetry collection.
This commit applies the standard telemetry pattern to the analyze-task-complexity command and its corresponding MCP tool.
Key Changes:
1. Core Logic (scripts/modules/task-manager/analyze-task-complexity.js):
- The call to generateTextService now includes commandName: 'analyze-complexity' and outputType.
- The full response { mainResult, telemetryData } is captured.
- mainResult (the AI-generated text) is used for parsing the complexity report JSON.
- If running in CLI mode (outputFormat === 'text'), displayAiUsageSummary is called with the telemetryData.
- The function now returns { report: ..., telemetryData: ... }.
2. Direct Function (mcp-server/src/core/direct-functions/analyze-task-complexity.js):
- The call to the core analyzeTaskComplexity function now passes the necessary context for telemetry (commandName, outputType).
- The successful response object now correctly extracts coreResult.telemetryData and includes it in the data.telemetryData field returned to the MCP client.
