# ctxlint

> ctxlint — yawlabs-ctxlint. Use this tool when you need to ensure consistency and accuracy in your AI agent context files, such as CLAUDE.md and AGENTS.md, by linting them against your codebase to catch errors and discrepancies. It solves problems like outdated or mismatched information, and provides outputs like error reports and corrections. It takes your codebase and context files as inputs, making it ideal for use during git-based development and deployment workflows.

Canonical page: https://skillsregistry.net/skills/yawlabs-ctxlint  
JSON: https://api.skillsregistry.net/v1/skills/yawlabs-ctxlint

## Description

Lint your AI agent context files (CLAUDE.md, AGENTS.md, etc.) against your codebase

## 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:** 2026-09-24

## Source

- **Source listing:** [GitHub](https://github.com/YawLabs/ctxlint)

## 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": "yawlabs-ctxlint"
    }
  }
}
```

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

---
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