autoresearch-toolfinderlisted

Find the right autonomous-research / autoresearch tool, framework, port, or skill for a research or engineering task. Searches a local cached index of two curated awesome-autoresearch lists (alvinreal + yibie, 550+ entries) and returns only the few matching tools, never loading the whole catalog into context. Use when the user wants to pick, compare, or set up an autoresearch loop, an AI-scientist / research-agent system, a domain or hardware port (Apple Silicon, RTX, RL, trading, materials, bio, vision, kernels...), or an evaluation harness, or asks "is there an autoresearch tool for X".
jajupmochi/claude-config · ★ 0 · AI & Automation · score 78

Install: claude install-skill jajupmochi/claude-config

# autoresearch-toolfinder Recommends tools from two curated **awesome-autoresearch** catalogs (550+ entries) WITHOUT reading the whole list into context. You run a search script and read back only the top matches. ## How to use (token-efficient — follow this; do NOT cat the index) The catalog is large. **Never read `data/index.json` directly** (that defeats the purpose). Run the query script from the skill directory; it returns only the top candidates: ```bash python3 scripts/query.py "<keywords from the user's task>" # options: --source alvinreal|yibie --category "<substring>" --limit 8 --json python3 scripts/query.py --list-categories # see sections + counts first ``` Examples: - Apple-Silicon / MLX port: `python3 scripts/query.py "apple silicon mlx mac metal"` - End-to-end AI scientist: `python3 scripts/query.py "ai scientist paper literature review" --source alvinreal` - RL post-training loop: `python3 scripts/query.py "reinforcement learning grpo post-training"` - Trading strategy search: `python3 scripts/query.py "trading strategy backtest" --source yibie` - Browse a whole section: `python3 scripts/query.py "" --category "Evaluation"` Then: read the handful of `name + url + one-liner` results, pick the best 1-3 for the user's actual context, and say why. Open a specific repo URL (WebFetch) only if the user wants depth. ## When to activate (auto) Activate when the user is **choosing / comparing / setting up**: an autoresearch or self-