# judges

> judges — kevinrabun-judges. Use this tool when you need to evaluate the quality and security of AI-generated code, solving problems such as identifying vulnerabilities, optimizing costs, and ensuring scalability and cloud readiness. It takes in AI-generated code via git and outputs a comprehensive assessment of its security, cost, scalability, cloud readiness, and adherence to best practices. This tool is ideal for use cases where code quality and security are paramount, such as in production environments or mission-critical applications.

Canonical page: https://skillsregistry.net/skills/kevinrabun-judges  
JSON: https://api.skillsregistry.net/v1/skills/kevinrabun-judges

## Description

MCP server with specialized judges to evaluate AI-generated code for security, cost, scalability, cloud readiness, and best practices.

## 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:** security
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/KevinRabun/judges)

## 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": "kevinrabun-judges"
    }
  }
}
```

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