# joint-chiefs

> joint-chiefs — djfunboy-joint-chiefs. Use this tool when you need to streamline AI code reviews and improve model reliability through a hub-and-spoke debate framework. It solves problems of inconsistent code quality and inefficient review processes by orchestrating multi-model reviews, taking Git repositories as input and producing actionable feedback as output. Ideal for use in collaborative AI development environments where code quality and model performance are critical.

Canonical page: https://skillsregistry.net/skills/djfunboy-joint-chiefs  
JSON: https://api.skillsregistry.net/v1/skills/djfunboy-joint-chiefs

## Description

Multi-model AI code review orchestrator with hub-and-spoke debate

## Trust

- **Trust score (0–1):** 0.96
- **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/djfunboy/joint-chiefs)

## 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": "djfunboy-joint-chiefs"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/djfunboy-joint-chiefs` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/djfunboy-joint-chiefs/pull`

---
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