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Found 5,140 Skills
Continuous self-improvement through structured reflection and memory
Use when deploying to production, handling sensitive data, or the workflow needs safety constraints, input validation, and security boundaries.
Use when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing. Always use --fields to limit output size and --dry-run before committing to an install.
Use when evaluating whether a skill belongs in a library. Preview content, check frontmatter, validate structure, and decide whether to keep, curate, or remove.
Check Nowledge Mem connection status, server version, CLI version, and configuration. Use when diagnosing issues or verifying setup.
Use when executing implementation plans. Dispatches independent subagents for individual tasks with code review checkpoints between iterations for rapid, controlled development.
Plan-then-execute implementation against SPEC.md. Native single-thread loop, no sub-agents. On test or build failure, auto-invokes the backprop skill before retrying — a failed verification always considers whether a new §V invariant would prevent recurrence. Triggers when the user asks to build, implement, execute the spec, or tackle a specific §T task (`build §T.3`, `build --next`, `implement next task`, `run the build`). Expects SPEC.md to exist; if not, defers to the spec skill.
어떤 주제/과제든 받아서 스스로 팀을 구성하고 조사·분석·검토·결과도출까지 처리하는 범용 에이전트 팀 오케스트레이터. "팀으로 분석해줘", "에이전트 팀으로 조사해줘", "다각도로 검토해줘", "심층 분석 부탁해", "여러 관점으로 봐줘", "think-team", "think team" 키워드로 트리거. 단순 질문이 아닌 복합적 판단, 조사, 전략 결정이 필요한 모든 상황에서 사용.
PeachSolution 신규 모듈 전체 개발을 조율하는 팀 오케스트레이터 스킬. "팀으로 만들어줘", "풀스택 개발", "백엔드+UI 전체 생성" 키워드로 트리거. mode=backend(API+Store), mode=ui(UI만), mode=fullstack(전체) 지원.
Use when acting as Grunk - reads specs from beads, plans, implements, commits, tags pr-ready. Merged TL+Engineer. Works in loop mode or interactive mode.
Use when creating or editing skills, before deployment, to verify they work under pressure and resist rationalization - applies RED-GREEN-REFACTOR cycle to process documentation by running baseline without skill, writing to address failures, iterating to close loopholes
Launch a meta-judge then a judge sub-agent to evaluate results produced in the current conversation