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 ai4s-research · Claude Skill · ★ 167
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ai4s-skills safe to install? View the security audit →
Seven agent skills for AI-for-Science research — turn a research direction into literature surveys, runnable experiments, publication-grade papers, and integrity audits, with every citation, number, and figure traceable to its source. English · 中文 Contents 🧩 The skills 🔗 How they connect ✅ Authenticity 🔬 Example 📦 Install 🚀 Usage 🗂️ Repository layout 🛠️ Included tools 🤝 Contributing ⚖️ License 🙏 Acknowledgments The skills | [ai4s-agent](skills/a
| Stars | 167 |
| Forks | 17 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 73.9279372854071/100 |
| Last Updated | 2026-07-28 |
| Created | 2026-06-27 |
| Platforms | claude-code, python |
| Est. Tokens | ~15k |
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ai4s-skills is Open-source agent skills for AI for Science: topic exploration, literature survey, experiments, paper writing, and integrity audit — driven by any coding agent.. It is categorized as a Claude Skill with 167 GitHub stars.
ai4s-skills is primarily written in Python. It covers topics such as agent-skills, ai-agent, ai-for-science.
You can find installation instructions and usage details in the ai4s-skills GitHub repository at github.com/ai4s-research/ai4s-skills. The project has 167 stars and 17 forks, indicating an active community.
ai4s-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ai4s-skills on Agent Skills Hub include Light-skills, Auto-Research-Skills, awesome-academic-research-skills. 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: