Where are the task manifest files stored?

All task lists are saved in the .claude/tasks/ directory within your project root using a timestamped YAML format for easy versioning and tracking.

Does this skill actually write or modify my code?

No, this skill is specifically designed for planning and documentation. It creates a task manifest file to guide the process but does not execute the actual implementation steps.

What is included in each generated subtask?

Each subtask includes a descriptive title, a detailed execution prompt, the current state (waiting/running/done), and a list of specific file paths involved.

Why is there a limit of 10 file changes per subtask?

This constraint ensures that each step remains focused and manageable for an AI or developer, reducing the risk of errors and making code reviews significantly easier.

How does it handle ambiguous requests?

If a user request is unclear or incomplete, the skill is programmed to use the AskUserQuestion tool to seek clarification before attempting to generate a breakdown.

Task Breakdown Specialist

Name: Task Breakdown Specialist
Author: GmwEnterprise

byGmwEnterprise

生産性とワークフロー

Deconstructs complex engineering requirements into actionable, structured subtasks with automated metadata documentation.

概要

The Task Breakdown skill transforms ambiguous or large-scale development requests into organized, manageable execution plans. It meticulously analyzes project architecture using LSP and exploration tools, identifies dependencies, and generates a structured YAML manifest within the .claude/tasks/ directory. By enforcing granular subtasks and providing clear execution prompts for each step, it ensures that subsequent coding phases are systematic, verifiable, and less prone to errors or scope creep.

主な機能

Logical dependency ordering from infrastructure to testing
Deep project structure analysis using LSP and grep patterns
0 GitHub stars
Automated YAML manifest generation with state tracking
Requirement clarification through automated user questioning
Granular task mapping limited to 10 file changes per step

ユースケース

Refactoring complex systems while maintaining a clear audit trail of steps
Onboarding AI agents to new projects with a defined execution roadmap
Planning a major feature implementation across multiple legacy modules

概要

主な機能

Logical dependency ordering from infrastructure to testing
Deep project structure analysis using LSP and grep patterns
0 GitHub stars
Automated YAML manifest generation with state tracking
Requirement clarification through automated user questioning
Granular task mapping limited to 10 file changes per step

ユースケース

Refactoring complex systems while maintaining a clear audit trail of steps
Onboarding AI agents to new projects with a defined execution roadmap
Planning a major feature implementation across multiple legacy modules