# rust-doctor

> rust-doctor — arthjean-rust-doctor. Use this tool when you need to identify and correct errors in Rust code written by AI agents, solving problems of code quality and reliability. It takes in poorly written Rust code as input and outputs corrected, functional code. Ideal for use in git-based development workflows where AI-generated code requires review and refinement.

Canonical page: https://skillsregistry.net/skills/arthjean-rust-doctor  
JSON: https://api.skillsregistry.net/v1/skills/arthjean-rust-doctor

## Description

Your agent writes bad Rust. This catches it.

## Trust

- **Trust score (0–1):** 0.44
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/arthjean/rust-doctor)

## 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": "arthjean-rust-doctor"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/arthjean-rust-doctor` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/arthjean-rust-doctor/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