跳到主要内容
知仓学习社ZHICANG

faf-expert

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

不碰外部(只输出文字)无严重或高危命中sickn33/agentic-awesome-skills

它会碰到什么

扫了多少1 个文本文件,6 KB
它会碰到什么不碰外部(只输出文字)
命中总数0 处
命中统计严重 0 · 高 0 · 中 0 · 低 0

这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。

技能内容

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
  • 🎯 Enterprise deployment patterns
  • 🎯 Advanced MCP server setup

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.

想直接用这个技能?

本站把开放许可(MIT / Apache 等)的技能按仓库打包整理到网盘,点一下转存到你自己的网盘,不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接,不打包。

同名技能的其他版本

有 3 个不同仓库或目录里都有叫 faf-expert 的技能。它们内容并不相同,别混用: