← ClaudeAtlas

find-skillslisted

Pull expert skills into this harness from the Rockie platform catalog (~300 skills across ML training/inference, biology, chemistry, physics, databases, coding). Use BEFORE writing domain guidance from scratch or fumbling an unfamiliar framework — if the task names a library (vLLM, GRPO, TRL, AlphaFold, DuckDB, LAMMPS), check the catalog first. Browse `rockie skill catalog --search X --json`, pull into `.claude/skills/`, invoke immediately. Silently no-ops when the Rockie CLI is absent or logged out.
Rockielab/rockie-claude · ★ 20 · AI & Automation · score 76
Install: claude install-skill Rockielab/rockie-claude
# /find-skills — mine the Rockie skill catalog The Rockie platform ships ~300 skills. **They are deliberately not in your context.** Loading 300 descriptions at every session start would cost more than the skills are worth. Instead the catalog sits behind the CLI, and you pull the two or three that match the work in front of you. That is the whole design: **the catalog is your library card, not your bookshelf.** This skill is how you use it. A Rockie `SKILL.md` uses the same frontmatter Claude Code expects. A pulled skill is invocable in the same session — no restart, no registration step. ## When to reach for this - The task names a framework/library/tool you'd otherwise wing it on (vLLM, verl, Unsloth, TRL, SGLang, RDKit, Biopython, DuckDB, …). - You're about to write a long block of domain guidance from memory. - You're entering a domain the project hasn't touched before. - The user asks "is there a skill for X?" **Check the catalog before writing expert guidance from scratch.** A pulled skill is written by someone who has actually run the thing. ## Browse ```bash rockie skill catalog --search grpo --json rockie skill catalog --category ml-inference --json rockie skill catalog --json # everything ``` **Always use `--json`.** Not for parsing convenience — because the tab-delimited form omits a field you need. Shape: ```json {"skills": [{"name": "verl-rl-training", "catalog_id": "verl", "description": "...", "category": "ml-trai