# io.github.Alberto-Codes/docvet

> Use this tool when you need to ensure high-quality Python docstrings, as it vets their quality through enrichment, freshness, coverage, and presence checks, solving problems of outdated or missing documentation. This tool takes Python code as input and outputs a report on docstring quality, providing insights for improvement. It is ideal for use during code reviews or development to maintain well-documented and maintainable codebases.

Canonical page: https://skillsregistry.net/skills/io-github-alberto-codes-docvet  
JSON: https://api.skillsregistry.net/v1/skills/io-github-alberto-codes-docvet

## Description

Docstring quality vetting for Python -- enrichment, freshness, coverage, and presence checks

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.10.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-19

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.Alberto-Codes%2Fdocvet)
- **Repository:** <https://github.com/Alberto-Codes/docvet>

## 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-alberto-codes-docvet"
    }
  }
}
```

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