install-from-remote-library
This skill provides a structured workflow for installing skills from remote shared libraries without accidentally over-installing or skipping preview steps. Use it when adding capabilities from external ai-agent-skills repositories, ensuring you first inspect available options with `--list`, choose the most appropriate collection or individual skill, preview changes with `--dry-run`, and then execute the actual installation only after confirming the plan.
git clone --depth 1 https://github.com/MoizIbnYousaf/Ai-Agent-Skills /tmp/install-from-remote-library && cp -r /tmp/install-from-remote-library/skills/install-from-remote-library ~/.claude/skills/install-from-remote-librarySKILL.md
# Install From Remote Library ## Goal Install from a shared library repo without guessing, over-installing, or skipping the preview step. ## Invariants - Always inspect the remote library first with `install <source> --list`. - Prefer `--collection` when the library clearly exposes a starter pack or focused bundle. - Always run `--dry-run` before the real install. - Keep the install small. Do not pull a whole library when the user only needs a narrow slice. ## Workflow 1. Inspect the source library. ```bash npx ai-agent-skills install <owner>/<repo> --list ``` 2. Choose the smallest fitting target. - Prefer `--collection starter-pack` or another named collection when it matches the user's need. - Use `--skill <name>` only when the user needs one specific skill or the library has no useful collection. - Do not combine `--collection` and `--skill`. 3. Preview the install plan before mutating anything. ```bash npx ai-agent-skills install <owner>/<repo> --collection starter-pack --dry-run -p ``` or ```bash npx ai-agent-skills install <owner>/<repo> --skill <skill-name> --dry-run -p ``` 4. If the plan looks right, run the real install with the same scope. ```bash npx ai-agent-skills install <owner>/<repo> --collection starter-pack -p ``` ## Decision Rules - If the library has a curated collection that already matches the user's stack, use it. - If the remote library is empty or the list output is unclear, stop and report that instead of guessing. - If the install path throws an `ERROR` / `HINT`, surface that verbatim and follow the hint before retrying. - If the user is exploring a large library, keep them in browse mode first rather than installing immediately. ## Done Return: - what source library you inspected - which collection or skill you chose - the dry-run result - the exact final install command you used
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.