by sotopia-lab · Agent Tool · ★ 334
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 334 |
| Forks | 50 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 69/100 |
| Open Issues | 17 |
| Last Updated | 2026-06-05 |
| Created | 2023-10-23 |
| Platforms | python |
| Est. Tokens | ~41487k |
Sotopia: an Open-ended Social Learning Environment News [05/2024] Sotopia was presented at ICLR 2024 as a spotlight ⭐! Introduction Sotopia is an open-ended social learning environment that allows
Looking for a sotopia alternative? If you're comparing sotopia with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
🦙 Integrating LLMs into structured NLP pipelines
🔍 LangKit: An open-source toolkit for monitoring Large Language Models (LLMs). 📚 Extracts signals from promp
历年ICLR论文和开源项目合集,包含ICLR2021、ICLR2022、ICLR2023、ICLR2024、ICLR2025.
Explore a comprehensive collection of resources, tutorials, papers, tools, and best practices for fine-tuning
🌱 A little course on Reinforcement Learning Environments for evaluating and training Language Models
Open-source calculator for LLM system requirements.
Explore other popular agent tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: