* 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
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Co-authored-by: Ralph Khreish <35776126+Crunchyman-ralph@users.noreply.github.com>
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.
