search-ai-tools

Description

# Search GitHub for AI Tools AI/ML tooling moves fast. A library that was best-in-class twelve months ago is often broken against current model APIs, SDK versions, or provider behaviour today. This skill applies a stricter recency filter than the general `search-repos` skill. ## When to use Trigger phrases include: - "Find an AI/ML library for X" - "Is there an MCP server for Y?" - "What's a good LLM framework for Z?" - "Search for agent frameworks / prompt management / eval tools / RAG libraries" ## Procedure ### 1. Frame the search with a recency cutoff Default cutoff: **last push within the last 6 months**. Unless the user overrides, exclude anything staler than that at the query level. ```bash # Compute a 6-month-ago date CUTOFF=$(date -d '6 months ago' +%Y-%m-%d) gh api -X GET search/repositories \ -f q="<ai-keywords> pushed:>$CUTOFF" \ -f sort=stars -f order=desc --jq '.items[] | { full_name, stars: .stargazers_count, pushed_at, updated_at, language, license: .license.spdx_id, open_issues: .open_issues_count, description, url: .html_url }' ``` Useful query operators to combine: - `topic:llm`, `topic:agents`, `topic:rag`, `topic:mcp`, `topic:prompt-engineering` - `stars:>50` to strip hobby projects - `archived:false` ### 2. Tier the results Sort candidates into three tiers based on recency, then by stars within each tier: - **Active** — pushed within last 30 days - **Maintained** — pushed 1–6 months ago - **Stale (⚠️)** — pushed 6–12 months ago; include only if the user explicitly asked for a complete picture - **Dead** — pushed > 12 months ago; exclude entirely unless specifically requested ### 3. Look for activity signals beyond last-push - **Recent releases** — `gh api repos/<owner>/<repo>/releases --jq '.[0].published_at'` - **Commit cadence** — `gh api repos/<owner>/<repo>/commits --jq '[.[].commit.author.date] | .[:5]'` - **Open PRs** — healthy projects have a steady stream, not hundreds untouched Flag projects where last-push is recent but commits are only dependency bumps (Dependabot churn) — that's not real maintenance. ### 4. Present results Output grouped by tier. For each candidate include: - Full name, stars, last push ("N days/weeks/months ago") - Language, license, open-issue count - One-sentence summary of what it does - A short note on maintenance signal ("active releases", "only Dependabot commits", "solo maintainer", etc.) where visible ### 5. Offer next steps - Deeper evaluation via `evaluate-candidates` - Documentation via `document-findings` (AI research especially benefits from date stamping — what's good today may be obsolete in 3 months) ## Guidance - **A 2k-star AI project last updated 14 months ago is almost always worse than a 200-star project updated yesterday.** Say so explicitly. - **Watch for abandoned demos** — viral projects from blog posts or tweet threads often look popular but have no ongoing maintenance. - **LLM API compatibility rots fast.** Anything predating the current model generations may be broken. - Do not invent projects. Report only what the CLI returned.

Security Status