ranbot-ai/awesome-skills

faf-expert

Advanced .faf (Foundational AI-context Format) specialist. IANA-registered format, MCP server config, championship scoring, bi-directional sync.

First seen Jun 26, 2026

Installation

$ npx skills add ranbot-ai/awesome-skills --skill faf-expert

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Declared
Gemini CLI Declared
Cline Not declared
OpenCode Not declared

Also listed on

Alternate registries and mirrors of this skill.

Repository health

Stars 6
License MIT
Default branch main
Open issues 3
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code cursor windsurf gemini antigravity

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,448 B
  • docs SUMMARY.md 162 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

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:

  • .fafCLAUDE.md
  • .faf.cursorrules
  • .fafGEMINI.md
  • .fafAGENTS.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
  • 🎯 E