share-a-library
Share-a-Library publishes a completed local library to GitHub and generates the exact install command for teammates to use. Use this when a managed library has been built and documented, and is ready to be shared across a team or organization as a reusable package installable via the ai-agent-skills CLI.
git clone --depth 1 https://github.com/MoizIbnYousaf/Ai-Agent-Skills /tmp/share-a-library && cp -r /tmp/share-a-library/skills/share-a-library ~/.claude/skills/share-a-librarySKILL.md
# Share A Library ## Goal Turn a finished local library into a real shared artifact with a repo URL and an install command another agent can use. ## Preconditions - You are already inside a managed library workspace. - The library has been sanity-checked. - `npx ai-agent-skills build-docs` has already run, or you run it now before publishing. ## Workflow 1. Regenerate docs if needed. ```bash npx ai-agent-skills build-docs ``` 2. Publish the workspace to GitHub. ```bash git init git add . git commit -m "Initialize skills library" gh repo create <owner>/<repo> --public --source=. --remote=origin --push ``` 3. Return the exact shareable install command. If the library has a `starter-pack` collection: ```bash npx ai-agent-skills install <owner>/<repo> --collection starter-pack -p ``` Otherwise: ```bash npx ai-agent-skills install <owner>/<repo> -p ``` ## Guardrails - Do not stop at `git init`. A shared library is not shared until the repo exists and the install command is ready. - If the repo already exists, connect the existing remote and push instead of creating a duplicate. - Prefer the collection install command when a curated starter pack exists. - Return the actual repo coordinates you used, not placeholders. ## Done Return: - the repo URL - whether you shared a collection or the whole library - the exact install command to hand to teammates
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.