# io.github.rog0x/lint

> Use this tool when you need to analyze and improve the quality of AI agent code, as it provides style checks, naming conventions, and complexity analysis to ensure maintainable and efficient code. It solves problems related to code readability, consistency, and performance, making it ideal for development and testing phases. The tool takes in AI agent code as input and outputs detailed reports on style, naming, and complexity issues.

Canonical page: https://skillsregistry.net/skills/io-github-rog0x-lint  
JSON: https://api.skillsregistry.net/v1/skills/io-github-rog0x-lint

## Description

Style check, naming, complexity analysis for AI agents

## Trust

- **Trust score (0–1):** 0.98
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.2
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.rog0x%2Flint)
- **Repository:** <https://github.com/rog0x/mcp-lint-tools>

## 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-rog0x-lint"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-rog0x-lint` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-rog0x-lint/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