# Software Documentation Analysis

> Use this tool when you need to analyze and improve software documentation, such as evaluating README structure and quality. It solves problems like disorganized project documentation and inconsistent formatting, providing outputs like parsed Markdown and extracted key sections through its interface with the Model Context Protocol. It is particularly useful for developers, technical writers, and AI assistants looking to standardize documentation across repositories.

Canonical page: https://skillsregistry.net/skills/sunwood-ai-labs-documind  
JSON: https://api.skillsregistry.net/v1/skills/sunwood-ai-labs-documind

## Description

This MCP server for evaluating README structure, developed by an unnamed author, integrates with the Model Context Protocol to provide AI assistants with tools for analyzing and improving documentation. Built with TypeScript and leveraging libraries like Cheerio and Marked, it offers capabilities for parsing Markdown, extracting key sections, and assessing overall document structure. The server abstracts the complexities of README analysis, allowing AI systems to easily incorporate documentation evaluation into their workflows. It's particularly useful for developers, technical writers, and AI assistants focused on improving software documentation, enabling use cases like automated README quality checks, content organization suggestions, and standardization of project documentation across repositories.

## Trust

- **Trust score (0–1):** 0.90
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/sunwood-ai-labs-documind)
- **Repository:** <https://github.com/sunwood-ai-labs/documind-mcp-server>

## 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": "sunwood-ai-labs-documind"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sunwood-ai-labs-documind` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sunwood-ai-labs-documind/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