# AgentOS

> AgentOS — cuistrex-agentos. Use this tool when you need to create a zero-pollution workspace for AI coding agents like Claude, Cursor, and Windsurf, streamlining their development process and integrating with git for seamless version control. AgentOS solves problems of code pollution and context switching, providing a clean architecture for AI agents to operate efficiently. It takes in coding tasks and outputs optimized, pollution-free code, ideal for use in collaborative AI development environments.

Canonical page: https://skillsregistry.net/skills/cuistrex-agentos  
JSON: https://api.skillsregistry.net/v1/skills/cuistrex-agentos

## Description

zero-pollution workspace architecture and context engine for AI coding agents (Claude, Cursor, Windsurf).

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/CuisTreX/AgentOS)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "cuistrex-agentos"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/cuistrex-agentos` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/cuistrex-agentos/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt