# context-builder

> context-builder — igorls-context-builder. Use this tool when you need to generate optimized codebase context for large language models (LLMs) from any directory. It solves the problem of manually creating context for LLMs by automatically processing directory inputs and producing optimized codebase context outputs. Ideal for use cases where efficient LLM integration is required, such as AI model training and development.

Canonical page: https://skillsregistry.net/skills/igorls-context-builder  
JSON: https://api.skillsregistry.net/v1/skills/igorls-context-builder

## Description

Generate LLM-optimized codebase context from any directory using context-builder CLI.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/igorls-context-builder)

## 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": "igorls-context-builder"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/igorls-context-builder` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/igorls-context-builder/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