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 InternScience · Codex Skill · ★ 507
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Awesome-Scientific-Skills safe to install? View the security audit →
Awesome Scientific Skills An open, curated collection of Agent Skills for scientific research — clone it, use it, extend it. 中文说明 / Chinese README: readmeCN.md Latest News We open-sourced Skiller — an automated tool that turns conversation logs or plain-text requirements into standards-compliant skill packages. We released skill-metric — a skills evaluation framework that screens high-quality skill repos across three dimensions. Results can also be found in /skills-metric. ⭐ Star us on GitHub! Your support means the world to us! 🙏😊 Why this repo? · Skill Sources · Categories · Quick Start · Contributing The Problem Thousands of Agent Skills are scattered across official registries and community repos. A researcher who needs to run a gene ontology enrichment, draft a
| Stars | 507 |
| Forks | 38 |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 65.2525642626722/100 |
| Open Issues | 7 |
| Last Updated | 2026-08-13 |
| Created | 2026-03-03 |
| Est. Tokens | ~19k |
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Awesome-Scientific-Skills is An open, curated collection of Agent Skills for scientific research — clone it, use it, extend it!. It is categorized as a Codex Skill with 507 GitHub stars.
You can find installation instructions and usage details in the Awesome-Scientific-Skills GitHub repository at github.com/InternScience/Awesome-Scientific-Skills. The project has 507 stars and 38 forks, indicating an active community.
Awesome-Scientific-Skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Awesome-Scientific-Skills on Agent Skills Hub include awesome-agent-skills, claudepro-directory, awesome-autoresearch. 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: