# fornix

> fornix — zga2519-fornix. Use this tool when you need to manage project memory for AI coding agents, storing knowledge in your repository alongside code. It solves version control and collaboration problems by integrating with git, allowing branches, merges, and reviews. Ideal for AI development workflows, fornix accepts code and git commands as input and outputs updated project memory, streamlining the coding process for MCP clients.

Canonical page: https://skillsregistry.net/skills/zga2519-fornix  
JSON: https://api.skillsregistry.net/v1/skills/zga2519-fornix

## Description

Project memory for AI coding agents, stored in your repo. Branches, merges and gets reviewed with the code. Any MCP client.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-11-05

## Source

- **Source listing:** [GitHub](https://github.com/ZGA2519/fornix)

## 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": "zga2519-fornix"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/zga2519-fornix` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/zga2519-fornix/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