# brain

> brain — raulvalverdeleal-brain. Use this tool when you need to optimize AI coding agent performance by loading only necessary skill sections on demand. It solves the problem of inefficient memory usage by allowing agents to fetch specific skills as needed, rather than loading entire libraries. The brain tool takes in skill requests and outputs token-efficient responses, making it ideal for use cases where memory and token limits are a concern.

Canonical page: https://skillsregistry.net/skills/raulvalverdeleal-brain  
JSON: https://api.skillsregistry.net/v1/skills/raulvalverdeleal-brain

## Description

Lazy loading for AI coding agent skills. A token-efficient MCP server that lets agents fetch only the skill sections they need, when they need them — without loading entire skill libraries into context.

## 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:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/Raulvalverdeleal/brain)

## 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": "raulvalverdeleal-brain"
    }
  }
}
```

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