Disciplined plan execution for implementation tasks. Use when executing a saved implementation plan, following step-by-step instructions from a plan document.

Assesses and responds to incoming code review feedback on PRs (reviewer comments, requested changes), especially when suggestions are unclear, technically questionable, or scope-expanding. Use...

Red-green-refactor development methodology requiring verified test coverage. Use for feature implementation, bugfixes, refactoring, or any behavior changes where tests must prove correctness.

Git branch completion workflow. Use when implementation is complete, tests pass, and a feature branch needs to be integrated via merge, pull request, or cleanup.

Structured implementation planning for multi-step development tasks. Use when you have a spec or requirements and need to break work into executable steps.

Git worktree–based workspace isolation for parallel or non-disruptive development. Use when work must occur without modifying or interfering with the current working tree.

Collaborative design exploration that refines ideas into validated specs through iterative questioning. Use before any creative work including creating features, building components, adding...

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Use this skill when the user asks to save, remember, recall, or organize memories. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check your notes',...

Use this skill when the user asks to save, remember, recall, or organize memories. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check your notes',...

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에이전트/스킬 실행 기여도를 분석하고 리포트를 생성합니다. stream.jsonl의 실행 로그를 파싱하여 호출 횟수, 성공률, 순위를 계산합니다. 내장 에이전트(general-purpose, Explore, Plan 등)는 제외하고 커스텀 에이전트/스킬만 분석합니다. "기여도 분석해줘", "이주의 에이전트", "에이전트 통계" 등의 요청 시 사용합니다.

Feature-first init: create or reuse worktree/branch and seed per-feature context. Git-aware and idempotent.

Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration

Fully autonomous TDD with strict guardrails. Use when you want the AI to drive the entire RED-GREEN-REFACTOR cycle independently while maintaining TDD discipline.

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