Security audit of brycewang-stanford/Auto-Empirical-Research-Skills · Agent Tool by brycewang-stanford · ★ 4.9k
Yes — Auto-Empirical-Research-Skills passed AgentSkillsHub's rule-based security scan with no dangerous patterns detected. As with any third-party skill, confirm what credentials it requests before production use.
What it is: 🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文，并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.
No dangerous patterns were detected: no credential exfiltration, no obfuscated downloads, no sandbox-escape attempts, no prompt-injection markers.
| Security grade | ✓ SAFE |
| Quality score | 56/100 |
| GitHub stars | 4.9k |
| Language | Stata |
| License | NOASSERTION |
| Last updated |
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This is AgentSkillsHub's free basic audit: an automated rule-based scan with 42 published rules built on SlowMist's agent-security taxonomy (credential theft, obfuscated payloads, privilege escalation, covert instructions to the agent, and more) across 186,000+ open-source AI agent skills and MCP servers, refreshed every 8 hours. A SAFE grade is a scan result, not a guarantee — deep 5-dimension audits (code · credentials · vendor · supply-chain · operational) are available for enterprise. Audited: .