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 Egv2 · Agent Tool · ★ 85
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-agentos safe to install? View the security audit →
Awesome AgentOS A curated list of tools, frameworks, and platforms for building agentic operating systems — the path to autonomous AI. Contents Agent Frameworks & Orchestrators Computer-Use & Desktop Automation Web Agents & Browser Automation Voice & Conversational AI Visual & Creative AI Developer Tools & Code Assistants LLM Infrastructure & Model Serving Security & Offensive AI Data, Memory & Knowledge Productivity & Personal Assistants MCP & Tool Integration Research & Reference Agent Frameworks & Orchestrators Core frameworks for building, deploying, and managing multi-agent systems — the kernel of agentic operating systems. |
| Stars | 85 |
| Forks | 30 |
| Category | Agent Tool |
| License | CC0-1.0 |
| Quality Score | 54.5128365534881/100 |
| Open Issues | 12 |
| Last Updated | 2026-09-30 |
| Created | 2026-01-31 |
| Est. Tokens | ~16k |
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awesome-agentos is A curated list of awesome open source projects for creating agentic operating systems, AI agents, and tools for the future of autonomous computing.. It is categorized as a Agent Tool with 85 GitHub stars.
You can find installation instructions and usage details in the awesome-agentos GitHub repository at github.com/Egv2/awesome-agentos. The project has 85 stars and 30 forks, indicating an active community.
awesome-agentos is released under the CC0-1.0 license, making it free to use and modify according to the license terms.
The top alternatives to awesome-agentos on Agent Skills Hub include awesome-ai-agents-2026, Hephaestus, riseofmachine. 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: