# ContextSkeleton

> ContextSkeleton — msgtorahul-art-context-skeleton. Use this tool when you need to reduce the complexity of code implementations for AI agents, preserving essential signatures and interfaces while minimizing tokens. It solves problems of excessive code size and token costs, providing use cases for efficient AI processing and analysis. The ContextSkeleton server takes in repository code and outputs condensed structural skeletons, with options to unfold specific symbols and retrieve cost savings metrics.

Canonical page: https://skillsregistry.net/skills/msgtorahul-art-context-skeleton  
JSON: https://api.skillsregistry.net/v1/skills/msgtorahul-art-context-skeleton

## Description

An MCP server that folds function and class implementations into structural skeletons while preserving signatures, interfaces, and docstrings, reducing tokens by up to 90%+ for AI agents. Exposes tools to get repository skeletons, unfold specific symbols on demand, and retrieve exact token and prompt cost savings metrics.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/x8xk1mlumz)
- **Repository:** <https://github.com/msgtorahul-art/context-skeleton>

## 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": "msgtorahul-art-context-skeleton"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/msgtorahul-art-context-skeleton` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/msgtorahul-art-context-skeleton/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