by telekinesis-ai · Agent Tool · ★ 87
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git clone https://github.com/telekinesis-ai/telekinesis-examples.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 | 87 |
| Forks | 6 |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 62/100 |
| Last Updated | 2026-11-06 |
| Created | 2025-12-19 |
| Est. Tokens | ~16k |
Telekinesis Docs • Discord • LinkedIn • X • Website Telekinesis Agentic OS Telekinesis is the Agentic OS for general-purpose robots. It provides a unified Python library that brings the entire Physical AI stack together: Vision-Language-Action models, World Models, perception, planning, hardware interfaces, and more.
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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: