# context-compose

> Use this tool when you need to define and manage task-specific contexts for AI-powered development, ensuring consistent and high-quality results. It solves problems of context inconsistency and poor output quality by providing a systematic approach to context composition. The context-compose system takes in task definitions and context parameters as inputs and outputs composed contexts for AI model execution.

Canonical page: https://skillsregistry.net/skills/lazylagom-context-compose-mcp  
JSON: https://api.skillsregistry.net/v1/skills/lazylagom-context-compose-mcp

## Description

A system for defining, composing, and managing task-specific contexts for AI-powered development, enabling consistent, high-quality results.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** productivity
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/i3x1e3dbyd)
- **Repository:** <https://github.com/lazylagom/context-compose-mcp>

## 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": "lazylagom-context-compose-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/lazylagom-context-compose-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/lazylagom-context-compose-mcp/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