review-a-skill
This skill provides a structured workflow for evaluating whether individual skills meet quality, relevance, and safety standards before entering or remaining in an AI agent skills library. Use it when reviewing skill submissions, auditing existing catalog entries for curation needs, or determining whether to keep, improve, or remove skills based on content preview, metadata validation, dependency checking, and decision criteria around clarity, usefulness, and security.
git clone --depth 1 https://github.com/MoizIbnYousaf/Ai-Agent-Skills /tmp/review-a-skill && cp -r /tmp/review-a-skill/skills/review-a-skill ~/.claude/skills/review-a-skillSKILL.md
# Review A Skill ## Goal Evaluate a single skill's quality, relevance, and safety before it enters or stays in a library. ## Guardrails - Always use `--format json` for machine-readable output in automated pipelines. - Always use `--fields` to limit output size when inspecting catalog entries. - Always use `--dry-run` before curating or removing a skill. - Never remove a skill without first checking if other skills depend on it via `info --format json` dependencies. ## Workflow 1. Preview the skill content to check for quality and safety. ```bash npx ai-agent-skills preview <skill-name> ``` The preview command sanitizes content — if it flags sanitization, investigate before proceeding. 2. Inspect the catalog entry for metadata completeness. ```bash npx ai-agent-skills info <skill-name> --format json --fields name,description,tags,collections,dependencies ``` 3. Validate the skill's SKILL.md structure. ```bash npx ai-agent-skills validate <skill-name> ``` 4. If the skill needs curation (notes, collections, verification): ```bash npx ai-agent-skills curate <skill-name> --notes "Reviewed: solid patterns" --verify --dry-run npx ai-agent-skills curate <skill-name> --notes "Reviewed: solid patterns" --verify ``` 5. If the skill should be removed: ```bash npx ai-agent-skills curate <skill-name> --remove --dry-run npx ai-agent-skills curate <skill-name> --remove --yes ``` ## Decision Criteria - **Keep**: Clear description, valid frontmatter, useful to the library's audience, no injection patterns. - **Curate**: Needs better whyHere, collection placement, or verification status. - **Remove**: Duplicate, outdated, broken source, or contains suspicious content. ## Gotchas - The `preview` command only works for vendored (house) skills. Upstream skills show description and whyHere only. - The `validate` command checks frontmatter structure but not content quality — that requires human or agent judgment. - Removing a skill that other skills depend on will break the dependency graph. Always check `dependencies.usedBy` first.
Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.
Use when checking the overall health of a skills library. Run doctor, validate, check for stale skills, and verify generated docs are in sync.
Backend API design, database architecture, microservices patterns, and test-driven development. Use for designing APIs, database schemas, or backend system architecture.
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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 regenerating README.md and WORK_AREAS.md in a managed library workspace. Always dry-run first to preview changes.
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.