by ryoungj · Agent Tool · ★ 223
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/ryoungj/ToolEmu.gitTaken from the project's README on GitHub.
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 | 223 |
| Forks | 23 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 76/100 |
| Open Issues | 2 |
| Last Updated | 2024-03-22 |
| Created | 2023-09-26 |
| Platforms | python |
| Est. Tokens | ~275k |
ToolEmu: Identifying the Risks of LM Agents with an LM-Emulated Sandbox [📃 Paper] [🌐 Website] [🎮 Demo] [🐦 Twitter] Recent advances in Language Model (LM) agents and tool use, exemplified by applications like ChatGPT Plugins, enable a rich set of capabilities but also amplify potential risks—such as leaking private data or causing...
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This is the repository for the Tool Learning survey.
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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: