// 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.
| name | browse-and-evaluate |
| description | 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. |
| category | workflow |
| version | 4.1.0 |
Find the right skill for a task without flooding the context window or installing blindly.
--fields on list/search/info to keep output small. Default: --fields name,tier,workArea,description.--dry-run before installing anything.--format json in non-interactive pipelines. The CLI defaults to JSON when stdout is not a TTY.--limit when browsing large catalogs. Start with --limit 10.npx ai-agent-skills search <query> --fields name,tier,workArea,description --limit 10
npx ai-agent-skills info <skill-name> --fields name,description,tags,collections,installCommands
npx ai-agent-skills preview <skill-name>
npx ai-agent-skills install <skill-name> --dry-run
npx ai-agent-skills install <skill-name>
preview command sanitizes skill content to strip prompt injection patterns. If content looks truncated, check if suspicious patterns were removed.--list or --dry-run a collection before installing.--dry-run to verify the source is reachable.Use when checking the overall health of a skills library. Run doctor, validate, check for stale skills, and verify generated docs are in sync.
Use when regenerating README.md and WORK_AREAS.md in a managed library workspace. Always dry-run first to preview changes.
Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.
Backend API design, database architecture, microservices patterns, and test-driven development. Use for designing APIs, database schemas, or backend system architecture.
Transforms vague prompts into optimized Claude Code prompts. Adds verification, specific context, constraints, and proper phasing. Invoke with /best-practices.
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.