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 framerslab · Agent Tool · ★ 673
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agentos safe to install? View the security audit →
AgentOS · TypeScript AI Agent Framework Agents that remember, forge their own tools, and survive long-running sessions. Persistent cognitive memory, optional HEXACO personality, multi-agent orchestration, and one dispatch interface across 11 LLM providers. Apache-2.0. [](
| Stars | 673 |
| Forks | 97 |
| Language | TypeScript |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 68.248868264457/100 |
| Open Issues | 11 |
| Last Updated | 2026-09-18 |
| Created | 2025-10-28 |
| Platforms | node |
| Est. Tokens | ~18k |
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agentos is TypeScript AI agent framework: cognitive memory, runtime tool forging, multi-agent orchestration, 11 LLM providers.. It is categorized as a Agent Tool with 673 GitHub stars.
agentos is primarily written in TypeScript. It covers topics such as agent-framework, agent-memory, agentic-ai.
You can find installation instructions and usage details in the agentos GitHub repository at github.com/framerslab/agentos. The project has 673 stars and 97 forks, indicating an active community.
agentos is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to agentos on Agent Skills Hub include agentos, swarmclaw, mcp-memory-service. 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: