Total 40,430 skills
Showing 12 of 40430 skills
모드 기반 완전 자율 실행기. plan 모드에서 Story 구조를 생성하고, epic 모드에서 에픽 1개를 자율 실행(implement → E2E → review)한다. 사람과 직접 소통하지 않는다.
AC 문서를 입력받아 Tech Spec을 작성하고, 자동으로 bf-lead-review를 통해 다관점 리뷰를 수행한다. BF 워크플로우 진입점.
sprint-status.yaml의 메트릭 데이터를 분석하여 모델 배당 최적화 및 난이도 재태깅을 제안한다. 읽기 전용 스킬로, 파일 변경 없이 대화로만 결과를 출력한다.
Vox single-entry voice orchestration skill. Used to complete environment guarding, CLI installation, on-demand model download, ASR transcription, voice cloning, pipeline execution and task troubleshooting through natural language. It is used when users only describe the target without providing specific commands.
스프린트 중 코드 리뷰에서 발견된 반복 패턴을 conventions.md에 반영한다. Convention Guard의 규칙 소스를 축적하여 다음 스프린트의 리뷰 품질을 높인다.
중단된 BF 워크플로우를 복구한다. sprint-status.yaml에서 마지막 완료 지점을 분석하여 bf-execute와 동일한 에픽 단위 루프로 재개한다.
Interact with the Apple Notes app. CRUD operations for persistent storage of thoughts, data, and information across sessions.
Access agent workspace files from any device via WebDAV + Cloudflare Tunnel. Starts a file bridge so users can browse, upload, and download files using their native file manager (Finder, Explorer, Files app, Dolphin). Use for "file sync", "share files", "access files", "remote files", "webdav", "file bridge", "mount workspace", "browse files from phone".
Build a structured taxonomy of failure modes from open-coded trace annotations. Use this skill whenever the user has freeform annotations from reviewing LLM traces and wants to cluster them into a coherent, non-overlapping set of binary failure categories (axial coding). Also use when the user mentions "failure modes", "error taxonomy", "axial coding", "cluster annotations", "categorize errors", "failure analysis", or wants to go from raw observation notes to structured evaluation criteria. This skill covers the full pipeline: grouping open codes, defining failure modes, re-labeling traces, and quantifying error rates.
Walk Claude through PyDESeq2-based differential expression, including ID mapping, DE testing, fold-change thresholding, and enrichment visualisation.
Guide for collaborating on GitHub projects. This skill should be used when contributing to projects, creating PRs, reviewing code, or managing issues on GitHub.
Generate a custom trace annotation web app for open coding during LLM error analysis. Use when the user wants to review LLM traces, annotate failures with freeform comments, and do first-pass qualitative labeling (open coding). Also use when the user mentions "annotate traces", "trace review tool", "open coding tool", "label traces", "build an annotation interface", "review LLM outputs", or wants to manually inspect pipeline traces before building a failure taxonomy. This skill produces a tailored Python web application using FastHTML, TailwindCSS, and HTMX.