# Gemini FAF

> Use this tool when you need to standardize and manage project context in a vendor-neutral format, solving issues of compatibility and completeness across different programming languages and platforms. Gemini FAF provides a unified format for project context, taking in project details and outputting validated, scored, and platform-specific formats. It is ideal for use with Python, JavaScript/TypeScript, Rust, and Go projects, streamlining development and collaboration.

Canonical page: https://skillsregistry.net/skills/gh-wolfe-jam-gemini-faf  
JSON: https://api.skillsregistry.net/v1/skills/gh-wolfe-jam-gemini-faf

## Description

Provides a structured, vendor-neutral project context format (FAF - Foundational AI-context Format) that unifies CLAUDE.md, GEMINI.md, and AGENTS.md into a single IANA-registered .faf file. Includes tools for auto-detecting project stacks, validating completeness with a scoring system, and exporting to platform-specific formats. Supports Python, JavaScript/TypeScript, Rust, and Go projects.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/gh-wolfe-jam-gemini-faf)
- **Repository:** <https://github.com/wolfe-jam/gemini-faf-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": "gh-wolfe-jam-gemini-faf"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/gh-wolfe-jam-gemini-faf` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/gh-wolfe-jam-gemini-faf/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