# Matryoshka

> Matryoshka — zpatel4761-matryoshka. Use this tool when you need to efficiently analyze large documents using minimal tokens, leveraging REPL state for optimized processing. Matryoshka solves problems related to resource-intensive document analysis, providing a scalable solution for MCP servers. It accepts document inputs and returns analyzed outputs, ideal for use cases involving large-scale text processing, such as data mining or information retrieval, with integration capabilities via git.

Canonical page: https://skillsregistry.net/skills/zpatel4761-matryoshka  
JSON: https://api.skillsregistry.net/v1/skills/zpatel4761-matryoshka

## Description

MCP server for token-efficient large document analysis via the use of REPL state

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-10-16

## Source

- **Source listing:** [GitHub](https://github.com/zPatel4761/Matryoshka)

## 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": "zpatel4761-matryoshka"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/zpatel4761-matryoshka` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/zpatel4761-matryoshka/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