browse-and-evaluate
This skill provides a structured workflow for discovering and evaluating skills from the ai-agent-skills catalog before installation. It enforces context-aware filtering with --fields flags, dry-run previews to prevent blind installs, and safeguards against installing excessive skills simultaneously or accepting suspicious content.
git clone --depth 1 https://github.com/MoizIbnYousaf/Ai-Agent-Skills /tmp/browse-and-evaluate && cp -r /tmp/browse-and-evaluate/skills/browse-and-evaluate ~/.claude/skills/browse-and-evaluateSKILL.md
# Browse And Evaluate ## Goal Find the right skill for a task without flooding the context window or installing blindly. ## Guardrails - Always use `--fields` on list/search/info to keep output small. Default: `--fields name,tier,workArea,description`. - Always use `--dry-run` before installing anything. - Never install more than 3 skills at once without explicit user confirmation. - Prefer `--format json` in non-interactive pipelines. The CLI defaults to JSON when stdout is not a TTY. - Use `--limit` when browsing large catalogs. Start with `--limit 10`. ## Workflow 1. Search or browse the catalog. ```bash npx ai-agent-skills search <query> --fields name,tier,workArea,description --limit 10 ``` 2. Get details on a candidate. ```bash npx ai-agent-skills info <skill-name> --fields name,description,tags,collections,installCommands ``` 3. Preview the skill content. ```bash npx ai-agent-skills preview <skill-name> ``` 4. Dry-run the install. ```bash npx ai-agent-skills install <skill-name> --dry-run ``` 5. Install only after reviewing the dry-run output. ```bash npx ai-agent-skills install <skill-name> ``` ## Gotchas - The `preview` command sanitizes skill content to strip prompt injection patterns. If content looks truncated, check if suspicious patterns were removed. - Collection installs pull multiple skills. Always `--list` or `--dry-run` a collection before installing. - Upstream (non-vendored) skills require a network fetch at install time. Use `--dry-run` to verify the source is reachable.
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 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.
Writing effective code documentation - API docs, README files, inline comments, and technical guides. Use for documenting codebases, APIs, or writing developer guides.