update-installed-skills
This skill updates previously installed AI agent skills to their latest versions while safeguarding against breaking changes and data loss. Use it when maintaining an agent's skill library, particularly when upstream repositories release updates. The skill enforces a dry-run-first workflow that lists current installations, checks for available updates, previews changes before applying them, and supports both individual and bulk synchronization with structured JSON output for tracking modifications.
git clone --depth 1 https://github.com/MoizIbnYousaf/Ai-Agent-Skills /tmp/update-installed-skills && cp -r /tmp/update-installed-skills/skills/update-installed-skills ~/.claude/skills/update-installed-skillsSKILL.md
# Update Installed Skills ## Goal Keep installed skills current without breaking the agent's workflow or silently overwriting local customizations. ## Guardrails - Always use `--dry-run` before running a real update. - Check what is currently installed before updating: `npx ai-agent-skills list --installed`. - Never update all skills at once in production without reviewing the dry-run output. - Use `--format json` to capture structured update results for logging. ## Workflow 1. List currently installed skills. ```bash npx ai-agent-skills list --installed --format json --fields name ``` 2. Check for available updates. ```bash npx ai-agent-skills check ``` 3. Dry-run the update. ```bash npx ai-agent-skills sync <skill-name> --dry-run ``` 4. Apply the update after reviewing. ```bash npx ai-agent-skills sync <skill-name> ``` 5. For bulk updates, review each skill's dry-run output. ```bash npx ai-agent-skills sync --all --dry-run ``` ## Gotchas - Skills installed from GitHub will attempt a fresh clone during sync. If the upstream repo is gone, the update will fail gracefully. - Manually edited SKILL.md files will be overwritten by sync. Back up customizations before syncing. - The `check` command makes network requests to verify upstream sources. It may be slow or fail if sources are unreachable.
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.