# CookieGli

> CookieGli — lovecookieee-java-cookiegli. Use this tool when you need to compress high-density codebases and evolve autonomous AI agent memories using Bayesian Darwinian principles. It solves problems of codebase optimization and AI memory management, accepting code repositories as input and outputting compressed genomes with evolved memories. Ideal for use in git-based projects requiring efficient and adaptive AI agent development.

Canonical page: https://skillsregistry.net/skills/lovecookieee-java-cookiegli  
JSON: https://api.skillsregistry.net/v1/skills/lovecookieee-java-cookiegli

## Description

🍪 High-density codebase genome compressor (≤600 tokens) & Bayesian Darwinian memory evolution for autonomous AI agents.

## Trust

- **Trust score (0–1):** 0.46
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/LoveCookieee-java/CookieGli)

## 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": "lovecookieee-java-cookiegli"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/lovecookieee-java-cookiegli` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/lovecookieee-java-cookiegli/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