# FACET_mcp

> FACET_mcp — rokoss21-facet-mcp. Use this tool when you need to optimize AI agent performance by delegating tasks to specialized tools, transforming them into reliable managers. FACET_mcp solves the problem of inconsistent AI output by streamlining task assignment, taking in AI workflows and outputting optimized task delegations. It integrates with git, making it ideal for use cases involving version-controlled AI projects.

Canonical page: https://skillsregistry.net/skills/rokoss21-facet-mcp  
JSON: https://api.skillsregistry.net/v1/skills/rokoss21-facet-mcp

## Description

Transform AI agents from "creative but unreliable assistants" into "high-performance managers" who delegate precise tasks to specialized tools.

## Trust

- **Trust score (0–1):** 0.54
- **Verification tier:** scanned
- **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/rokoss21/FACET_mcp)

## 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": "rokoss21-facet-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/rokoss21-facet-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/rokoss21-facet-mcp/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