suggest-toolinglisted

Propose work-relevant Claude Code skills, plugins, and MCP servers from a finished deep-research run; relevance-ranked and trust-tier-graded; never auto-installed. Load when the user says "/suggest-tooling <run-dir>", "propose tools for my research run", "what skills match this research", "suggère des outils pour ce run", or when deep-research delegates with --suggest-tooling. Do NOT activate for: installing or registering tools; single-tool lookup ("what does X do"); non-Claude-ecosystem tooling (npm packages, Python libs); running a fresh research run (use deep-research for that).
hashbulla/deep-research · ★ 1 · AI & Automation · score 73

Install: claude install-skill hashbulla/deep-research

> Consumes a finished `/deep-research` run and proposes work-relevant Claude Code skills, > plugins, and MCP servers — ranked by relevance, trust-tier-graded for supply-chain safety, > and never auto-installed. ## Trigger - Slash: `/suggest-tooling <run-dir>` - Delegation: `deep-research --suggest-tooling` (default OFF) passes `<run-dir>` and the work-relevant topic list computed at Phase 0. ## Workflow 1. **Read the run.** Load `<run-dir>/research-plan.md` and `<run-dir>/research-report.md`. Extract the work-relevant topics declared in the plan (the `ai-engineering` / `platform-ai-sre` / `freelance-acquisition` intersection flagged at Phase 0). If no work-relevant topics are found, emit an empty toolbox with a "no work-relevant topics" note and stop — do not propose tools for non-work-relevant runs. 2. **Classify topics to categories.** Map each work-relevant topic and each discovered candidate to one or more categories drawn from the closed taxonomy in `references/tooling-categories.md`. Classification uses LLM reasoning (semantic, not string-match) because it runs in the skill context, not inside the helper script. Emit a structured candidate JSON per the contract below for each discovered tool. 3. **Query the six connectors.** Run each independently; any channel may degrade without failing the run. Full per-channel mechanics and degradation rules are in `references/tooling-discovery.md`. Candidate contract (required fields): ```js