# universal-code-review-graph

> universal-code-review-graph — cybernoman-universal-code-review-graph. Use this tool when you need to optimize AI code reviews and reduce token usage. The universal-code-review-graph builds a structural call graph to streamline the review process, compatible with various AI assistants like Claude, Kimi, and ChatGPT. It integrates with git, accepting code repositories as input and generating efficient review graphs as output.

Canonical page: https://skillsregistry.net/skills/cybernoman-universal-code-review-graph  
JSON: https://api.skillsregistry.net/v1/skills/cybernoman-universal-code-review-graph

## Description

Save 6-8× tokens on AI code reviews. Builds a structural call graph via Tree-sitter + MCP. Works with Claude, Kimi, Gemini, ChatGPT, Cursor, Windsurf — any AI assistant.

## 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:** MIT
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/cyberNoman/universal-code-review-graph)

## 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": "cybernoman-universal-code-review-graph"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/cybernoman-universal-code-review-graph` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/cybernoman-universal-code-review-graph/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