/faf-expert

name: faf-expert
description: "Advanced .faf (Foundational AI-context Format) specialist. IANA-registered format, MCP server config, championship scoring, bi-directional sync."
category: coding
risk: safe
source: community
source_repo: Wolfe-Jam/faf-skills
source_type: community
date_added: "2026-04-07"
author: wolfejam
tags: [faf, ai-context, project-management, mcp, iana]
tools: [claude, cursor, gemini, windsurf]

FAF Expert - Advanced AI Context Architecture

**Master the IANA-registered format that makes AI understand your projects.**

Transform any codebase into an AI-intelligent project with persistent context that survives across sessions, tools, and AI platforms. Expert-level control over the foundational layer that powers modern AI development workflows.

When to Use This Skill

Use FAF Expert when you need:

| Scenario | What FAF Expert Provides | |----------|---------------------------| | **Complex project setup** | Expert configuration of .faf files and MCP servers | | **Championship scoring** | Achieve 85%+ AI-readiness scores for production projects | | **Multi-AI workflows** | Universal context that works across Claude, Cursor, Gemini, Windsurf | | **Legacy codebase revival** | Transform archaeology into AI-readable project DNA | | **Team collaboration** | Standardized context format for consistent AI assistance | | **Enterprise deployment** | Professional MCP server configuration and management |

Real-World Examples

Example 1: Legacy Enterprise Java System

# Achieved: 92% Gold tier with FAF Expert
project:
  name: enterprise-payment-api
  goal: Mission-critical payment processing system
  
stack:
  backend: java-spring
  database: oracle
  runtime: java-11
  deployment: kubernetes
  
human_context:
  where: AWS EKS production cluster
  when: Legacy system from 2018, modernizing 2026
  how: Spring Boot 2.7, Oracle 19c, Docker containerization

Example 2: Modern React Dashboard

# Achieved: 97% Gold tier performance
project:
  name: analytics-dashboard
  goal: Real-time analytics for SaaS platform
  
stack:
  frontend: react-18
  css_framework: tailwind
  state: zustand
  build: vite
  testing: vitest
  deployment: vercel

Core Capabilities

🏆 Championship Scoring System

• **Gold Tier (95%+)**: Production-ready AI context
• **Silver Tier (85%+)**: Professional development standard
• **Bronze Tier (70%+)**: Solid foundation for AI assistance

🔧 MCP Server Configuration

Expert setup of claude-faf-mcp with 33 tools:

{
  "mcpServers": {
    "faf": {
      "command": "npx",
      "args": ["-y", "claude-faf-mcp@latest"]
    }
  }
}

🔄 Bi-Directional Sync

Keep context synchronized across platforms:

• `.faf` ↔ `CLAUDE.md`
• `.faf` ↔ `.cursorrules`
• `.faf` ↔ `GEMINI.md`
• `.faf` ↔ `AGENTS.md`

📊 Mk4 Architecture Framework

33-slot IANA format for comprehensive project context:

• Project identity and goals
• Technical stack detection
• Human context (who/what/why/where/when/how)
• Architecture patterns
• Deployment configuration

Getting Started

Quick Installation

# Install FAF CLI
npm install -g faf-cli

# Initialize your project
faf init

# Score AI-readiness
faf score --details

# Set up MCP server
faf mcp install

Expert Commands

# Advanced scoring with breakdown
faf score --championship --verbose

# Multi-platform sync
faf bi-sync --target all

# Validate format compliance
faf validate --strict

# Enhanced AI optimization
faf enhance --model claude --focus completeness

Success Metrics

**Real Performance Data:**

• **52k+ downloads** across FAF ecosystem
• **800+ comprehensive tests** (CLI + MCP)
• **IANA-registered format** (application/vnd.faf+yaml)
• **153+ validated formats** supported
• **Championship-grade performance** (<50ms execution)

Platform Compatibility

Supported AI Tools

• ✅ **Claude Code** - Native MCP integration
• ✅ **Cursor** - .cursorrules sync
• ✅ **Gemini CLI** - GEMINI.md sync
• ✅ **Windsurf** - .windsurfrules support
• ✅ **Universal** - Works with any AI that reads YAML

MCP Servers Available

• `claude-faf-mcp` - 33 tools, 391 tests
• `grok-faf-mcp` - xAI/Grok optimized
• `rust-faf-mcp` - Native performance (4.3MB binary)
• `gemini-faf-mcp` - Google Gemini integration

Advanced Patterns

Enterprise Configuration

faf_version: "3.0"
project:
  name: enterprise-platform
  tier: production
  
human_context:
  team_size: 50+
  compliance: SOC2, HIPAA
  deployment: multi-region
  
stack:
  architecture: microservices
  orchestration: kubernetes
  monitoring: datadog
  security: vault

Legacy System Revival

# Transform 10-year-old codebase to AI-ready
project:
  archaeology: true
  modernization_target: 2026
  
stack:
  legacy: php-5.6
  migration_path: laravel-11
  database_upgrade: mysql-8

Expert Resources

• **Documentation**: https://faf.one
• **MCP Registry**: Official Anthropic steward
• **CLI Reference**: `faf --help`
• **Community**: Discord server with 1000+ developers
• **Enterprise**: Professional support available

When to Use faf-wizard Instead

Use `faf-wizard` for:

• ✅ Quick project setup
• ✅ One-click generation
• ✅ Beginner-friendly workflow
• ✅ Automated stack detection

Use `faf-expert` for:

• 🎯 Fine-tuned configuration
• 🎯 Championship scoring optimization
• 🎯 Multi-platform sync management
• 🎯 Enterprise deployment patterns
• 🎯 Advanced MCP server setup

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*Master the format that makes AI understand your projects. FAF Expert - for when you need championship-grade AI context architecture.*

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.