No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by uditgoenka · Claude Skill · ★ 5.8k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is autoresearch safe to install? View the security audit →
Claude Autoresearch Skill Turn Claude Code into a relentless improvement engine. Based on Karpathy's autoresearch — the principle that constraint + mechanical metric + autonomous iteration = compounding gains. What Is This? A Claude Code skill that makes Claude iterate autonomously on ANY task with a measurable outcome — like Karpathy's autoresearch, but generalized beyond ML. The loop: LOOP (FOREVER or N times): Review current state + git history + results log Pick the next change (based on what worked, what failed, what's untried) Make ONE focused change Git commit (before verification) Run mechanical verification (tests, benchmarks, scores) If improved → keep. If worse → git revert. If crashed → fix or skip. Log the r
| Stars | 5,821 |
| Forks | 442 |
| Language | Shell |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 68.309535786371/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-12 |
| Created | 2026-03-13 |
| Platforms | claude-code, cli |
| Est. Tokens | ~20k |
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autoresearch is Claude Autoresearch Skill — Autonomous goal-directed iteration for Claude Code. Inspired by Karpathy's autoresearch. Modify → Verify → Keep/Discard → Repeat forever.. It is categorized as a Claude Skill with 5.8k GitHub stars.
autoresearch is primarily written in Shell. It covers topics such as ai, autonomous-agent, autoresearch.
You can find installation instructions and usage details in the autoresearch GitHub repository at github.com/uditgoenka/autoresearch. The project has 5.8k stars and 442 forks, indicating an active community.
autoresearch is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to autoresearch on Agent Skills Hub include claude-code-tips, openpencil, commands. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: