# mezzanine

> mezzanine — llvator-mezzanine. Use this tool when you need to visualize and analyze your codebase's complexity and dependencies. Mezzanine provides a unified map of your code, solving problems related to code maintenance, optimization, and collaboration, and accepts git repositories as input, outputting metrics and graphs through its CLI and VS Code interfaces. It's ideal for use cases involving multi-language codebases, supporting ten languages with its Rust engine.

Canonical page: https://skillsregistry.net/skills/llvator-mezzanine  
JSON: https://api.skillsregistry.net/v1/skills/llvator-mezzanine

## Description

Give humans and AI agents the same map of your codebase: dependency graph, complexity and code-smell metrics, MCP server. Ten languages, Rust engine, VS Code + CLI.

## Trust

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

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** AGPL-3.0
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/llvator/mezzanine)

## 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": "llvator-mezzanine"
    }
  }
}
```

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