# CodeAgora

> CodeAgora — bssm-oss-codeagora. Use this tool when you need to automate code review processes and leverage AI-driven discussions to improve code quality. CodeAgora solves problems related to manual code review inefficiencies by utilizing five models to argue and provide insights, streamlining the development process. It integrates with git, taking in code submissions and outputting review suggestions and recommendations.

Canonical page: https://skillsregistry.net/skills/bssm-oss-codeagora  
JSON: https://api.skillsregistry.net/v1/skills/bssm-oss-codeagora

## Description

Code review, but with 5 models arguing first.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/bssm-oss/CodeAgora)

## 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": "bssm-oss-codeagora"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/bssm-oss-codeagora` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/bssm-oss-codeagora/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