Use when evaluating, comparing, installing, or recommending a Claude Code plugin, Agent Skill, MCP server, agent toolkit, or GitHub-hosted AI extension, especially when popularity is weak evidence or the candidate requests shell, network, filesystem, or credential access.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Collect comparable evidence about GitHub-hosted agent capabilities before installation. The bundled script uses the GitHub API without cloning a repository. It reports maintenance metadata, license, distribution files, executable surfaces, test signals, and high-risk text patterns. It does not install, authenticate, or declare a project safe.
Convert each candidate to owner/repo or a GitHub repository URL.
Run the script for all credible candidates, not only the popularity leader:
python ${CLAUDE_SKILL_DIR}/scripts/audit.py owner/repo another/repo
Read the exact pinned commit or package that would be installed. The script inspects the current default branch only; say so explicitly.
Open every discovered plugin manifest, SKILL.md frontmatter, hook, MCP configuration, and executable script before recommending installation.
Compare candidates using task fit, blast radius, runtime proof, maintenance, interoperability, rollback, documentation, and adoption. Cap adoption at 5% of the decision.
Report four states separately: discovered, structurally inspected, installed/authenticated, and runtime-tested.
Use --json for machine-readable output and --token-env NAME only when an existing GitHub token environment variable is needed for rate limits. Never paste a token into the command.
SECURITY.md is a review signal, not proof of insecurity.allowed-tools, install scripts, and downloaded binaries define the effective trust boundary.Read ecosystem-discovery-guide.md for the source order, weighted scorecard, research seeds, and installation gate.
Inspect the artifact you will execute, at the version you will execute—not the reputation of its repository.
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Use when cutting a release, writing a CHANGELOG entry, or summarizing what changed since a tag — when the repo's commits follow (or mostly follow) Conventional Commits and a mechanically-accurate section breakdown beats a model's reading of the diff.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use before committing, opening a PR, or reporting a task done — when you want ground-truth confirmation there are no conflict markers, live-looking credentials, debug leftovers, untracked TODOs, or oversized files, without spending a model turn re-reading every file yourself.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use before publishing documentation, merging a docs PR, or reporting a Markdown-heavy repo's navigation as complete — when you want ground-truth confirmation that internal links, heading anchors, and directory links resolve, without opening every file yourself.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when the user names a coding or Claude Code task ("add OAuth", "set up hooks", "review this PR", "pick a model"), asks which prompt to use, says to "use the right prompt", or when you enter this repo and need to orient without reading every file.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when the user names a coding, Claude Code, research, documentation, or technology-selection task; asks which prompt to use; says to use the right prompt; or when an agent enters this repository and needs to orient without reading every file.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when a skill isn't triggering as expected, before adding a new skill (to check for a name collision), during periodic cleanup of an accumulated skills directory, or when asked to review skill quality — checks frontmatter validity, description quality against Skill Discovery Optimization conventions, body size, and cross-scope name collisions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.