How do I install the Autoresearch Toolfinder skill?

Run npx skillmds@latest add jajupmochi/autoresearch-toolfinder-2 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Autoresearch Toolfinder safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Autoresearch Toolfinder?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Autoresearch Toolfinder free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Autoresearch Toolfinder?

jajupmochi (@jajupmochi) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Autoresearch Toolfinder by jajupmochi

Name: Autoresearch Toolfinder
Author: jajupmochi

Autoresearch Toolfinder

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 Updated Sep 17, 2026

File contents

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:

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-improvement loop; an AI-scientist or research-agent system; a hardware/platform port; a domain adaptation (bio, materials, finance, vision, RL, kernels, robotics...); or an eval harness — or asks "what should I use for autonomous research / overnight experiments on X".

Not this skill: to actually run a full autonomous research project end-to-end, use the sibling autoresearch orchestration skill. This skill is the catalog / finder only.

Keeping it current (update tracking)

data/state.json stores each upstream repo's commit SHA + sync time.

python3 scripts/check_updates.py     # cheap: 1 API call/repo, compares SHA, exits 1 if stale
python3 scripts/update_index.py      # re-fetch + re-parse both repos, rewrite the index

A weekly user systemd timer (systemd/autoresearch-index.timer) refreshes automatically; query.py also prints a hint when the local index is older than 30 days.

Sources

---name: autoresearch-toolfinder-2description: 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".license: MIT---# autoresearch-toolfinderRecommends tools from two curated **awesome-autoresearch** catalogs (550+ entries) WITHOUTreading 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:```bashpython3 scripts/query.py "<keywords from the user's task>"# options: --source alvinreal|yibie --category "<substring>" --limit 8 --jsonpython3 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'sactual 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 orself-improvement loop; an AI-scientist or research-agent system; a hardware/platform port; adomain adaptation (bio, materials, finance, vision, RL, kernels, robotics...); or an evalharness — or asks "what should I use for autonomous research / overnight experiments on X".Not this skill: to actually *run* a full autonomous research project end-to-end, use thesibling `autoresearch` orchestration skill. This skill is the **catalog / finder** only.## Keeping it current (update tracking)`data/state.json` stores each upstream repo's commit SHA + sync time.```bashpython3 scripts/check_updates.py # cheap: 1 API call/repo, compares SHA, exits 1 if stalepython3 scripts/update_index.py # re-fetch + re-parse both repos, rewrite the index```A weekly user systemd timer (`systemd/autoresearch-index.timer`) refreshes automatically;`query.py` also prints a hint when the local index is older than 30 days.## Sources- [alvinreal/awesome-autoresearch](https://github.com/alvinreal/awesome-autoresearch) (CC0)- [yibie/awesome-autoresearch](https://github.com/yibie/awesome-autoresearch)

Frequently asked questions