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Found 120 Skills
Test-driven development workflow with philosophy guide - plan → write tests → implement → validate
Write test files driven by acceptance criteria in strict TDD mode. No production code is generated. Use after the low-level design is approved.
ping-pong TDD 세션의 마지막 단계입니다. .tdd-sessions/에서 활성 세션 파일을 읽어 완료된 태스크를 요약하고, Conventional Commits 메시지를 제안하며, 커밋을 실행하고 세션 파일을 정리합니다. 모든 /tdd-task 호출이 완료된 후 실행합니다.
Agent skill for refinement - invoke with $agent-refinement
4-phase root cause debugging: understand bugs before fixing.
TDD-focused implementation planning. Creates plans with strict Red-Green-Commit/Rollback cycles for each step.
Test-Driven Development methodology enforcing RED-GREEN-REFACTOR cycle. Use for writing tests first, preventing regression, and ensuring code correctness. Based on obra/superpowers.
Develop software with validation requirements first. Emphasizes writing tests before implementation to guide design decisions.
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Design failing tests for complex features using Independent Evaluation — dispatches a context-free agent that sees only the requirement spec and code paths (not the implementation approach), then returns executable failing tests. Use when starting TDD for a non-trivial feature, when the requirement is ambiguous enough that biased tests are a risk, or when the user asks for independent test design.
Drives a disciplined explore → plan → implement → verify loop for changing an AI agent's behavior with confidence — whether fixing a reported failure or introducing a new requirement, business rule, or policy. Grounds the diagnosis in MLflow traces, codifies the desired behavior as a regression test suite (`mlflow.genai.evaluate` assertions in `@mlflow.test` pytest tests), and iterates the agent — not the test — until green, resisting quick system-prompt patches when the real fix is upstream (missing tool, retrieval source, or capability). Use whenever the user wants to fix or change how an agent behaves — e.g. "fix this issue in my agent", "this answer is wrong", "the agent is hallucinating", "improve my agent based on this trace", "make the agent do X instead of Y", "I want the agent to lead with/prioritize/recommend X", "new business rule: the agent should X", "always/never do X", "change the agent's default behavior" — or shares a trace they want addressed.
TDD enforcement during implementation. Reads `tdd:` setting from CLAUDE.md. Modes - strict (human approval for escape), soft (warnings), off (disabled). Auto-invoked by /implement.