# Judges Panel

> Use this tool when you need to evaluate the security, cost, and quality of AI-generated code, leveraging a panel of 45 judges with built-in Abstract Syntax Tree (AST) analysis to provide comprehensive feedback. It solves problems related to code review, security auditing, and optimization, taking in AI-generated code as input and producing detailed evaluation reports as output. Ideal for use in software development, DevOps, and AI model deployment contexts.

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

## Description

35 judges that evaluate AI-generated code for security, cost, and quality with built-in AST.

## Trust

- **Trust score (0–1):** 0.85
- **Verification tier:** scanned

## Facts

- **Version:** 1.0.2
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** security
- **Updated:** 2026-06-16

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.KevinRabun%2Fjudges)
- **Repository:** <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": "io-github-kevinrabun-judges"
    }
  }
}
```

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