# ragu

> ragu — pmelander-ragu. Use this tool when you need to retrieve relevant passages and metadata from local PDF, TXT, and MD files to provide context for large language models. It solves problems of information retrieval and data sourcing by returning context and sources for further processing. Ideal for use cases where local document search and metadata extraction are required, with inputs of file types and search queries, and outputs of retrieved passages and source metadata.

Canonical page: https://skillsregistry.net/skills/pmelander-ragu  
JSON: https://api.skillsregistry.net/v1/skills/pmelander-ragu

## Description

Local document retrieval server for PDF, TXT, and MD files. ragU does not generate answers — it returns context (retrieved passages) and sources (metadata) for your LLM to use.

## Trust

- **Trust score (0–1):** 0.74
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/pmelander/ragu)

## 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": "pmelander-ragu"
    }
  }
}
```

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