faf-wizard
Done-for-you .faf generator. One-click AI context for any project - new, legacy, or famous. Auto-detects stack, scores readiness, works everywhere.
Best use case
faf-wizard is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Done-for-you .faf generator. One-click AI context for any project - new, legacy, or famous. Auto-detects stack, scores readiness, works everywhere.
Teams using faf-wizard should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/faf-wizard/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How faf-wizard Compares
| Feature / Agent | faf-wizard | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Done-for-you .faf generator. One-click AI context for any project - new, legacy, or famous. Auto-detects stack, scores readiness, works everywhere.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# FAF Wizard - One-Click AI Intelligence
**The pit crew for your projects.** Point it at any codebase and get scored, AI-ready context in 60 seconds.
Transform any project - new, legacy, famous OSS, or forgotten side projects - into an AI-intelligent workspace with persistent context that works across all AI tools.
## The Problem It Solves
**Even React.js scores 0% AI-readiness.** Famous repositories have no AI context.
| What Exists | What It Tells AI |
|-------------|------------------|
| README.md | "What this does" (for humans) |
| docs/ | "How to use it" (for humans) |
| **project.faf** | "How to help build this" (for AI) |
Documentation tells humans how to use your code. AI context tells AI how to help you build it. **They're completely different things.**
## Works on ANY Project
| Project Type | What FAF Wizard Does |
|-------------|----------------------|
| **Brand new** | Perfect AI context from line one |
| **Legacy nightmare** | AI finally understands the archaeology |
| **Famous OSS** | Even React doesn't have this |
| **Side projects** | Stop re-explaining every session |
| **Client handoffs** | Portable context for any AI tool |
| **Team projects** | Shared context that everyone can use |
## Real Success Stories
### Before/After: Legacy E-commerce Platform
```
Before: "This 50k-line PHP codebase from 2015..."
AI: "I don't understand this architecture"
After: 60 seconds with FAF Wizard
AI: "I see this is a Laravel-based e-commerce system with
payment processing, inventory management, and multi-tenant
architecture. Here's how I can help..."
```
### Before/After: Modern React App
```
Before: Every AI session starts with context explanation
Time lost: 5-10 minutes per session
After: project.faf exists
AI: Instant understanding, productive from message one
Time saved: 2+ hours per day
```
## The 60-Second Workflow
### Step 1: Detection (10 seconds)
```bash
faf auto
# Scans manifest files, directory structure, dependencies
# Detects: React + TypeScript + Tailwind + Vercel
```
### Step 2: Generation (30 seconds)
```yaml
# Auto-generated project.faf
project:
name: my-saas-dashboard
goal: Customer analytics platform
stack:
frontend: react-18
css: tailwind
deployment: vercel
human_context:
who: Solo founder
what: SaaS analytics dashboard
why: Customer insights for small businesses
```
### Step 3: Scoring & Report (20 seconds)
```
✅ Generated: project.faf
🏆 AI-Readiness: 87% Bronze - Production ready
Filled: 9/11 active slots
Ignored: 22 slots (not applicable)
To reach Silver (95%):
+ Add API documentation (+5%)
+ Define deployment details (+3%)
```
## Performance Data (Real Numbers)
**Analyzed 8,400+ Projects:**
- ✅ **99.2% detection accuracy** across 153+ formats
- ✅ **Average generation time**: 12.3 seconds
- ✅ **Bronze tier or higher**: 94% of projects
- ✅ **Zero manual configuration**: Works out of the box
### Format Support
Automatically detects and configures:
- **JavaScript**: React, Vue, Angular, Svelte, Next.js, Nuxt
- **Python**: Django, Flask, FastAPI, Jupyter, Poetry
- **TypeScript**: All JS frameworks + native TS projects
- **Rust**: Cargo projects, CLI tools, web servers
- **Go**: Modules, Docker, microservices
- **Java**: Maven, Gradle, Spring Boot
- **+147 more formats**
## Universal Compatibility
### Works With Every AI Tool
- ✅ **Claude Code** - Reads .faf natively
- ✅ **Cursor** - Auto-syncs to .cursorrules
- ✅ **Gemini CLI** - Converts to GEMINI.md
- ✅ **Windsurf** - Syncs to .windsurfrules
- ✅ **ChatGPT** - Readable YAML format
- ✅ **Any AI** - Universal format support
### Migration Support
Already have AI context files?
```bash
# Migrates existing context
faf migrate --from .cursorrules
faf migrate --from CLAUDE.md
faf migrate --from README.md
# One format, works everywhere
faf sync --target all
```
## Installation Options
### Option 1: CLI (Recommended)
```bash
npm install -g faf-cli
cd your-project
faf auto
```
### Option 2: MCP Server (Claude Code)
```json
{
"mcpServers": {
"faf": {
"command": "npx",
"args": ["-y", "claude-faf-mcp@latest"]
}
}
}
```
### Option 3: Browser Extension
Install from Chrome Web Store - works on any Git repository.
## Three-Phase Intelligence
### Phase 1: Stack Detection
- Scans `package.json`, `Cargo.toml`, `pyproject.toml`, etc.
- Analyzes directory structure and file patterns
- Identifies frameworks, deployment targets, testing setup
### Phase 2: Context Mining
- Extracts project description from README
- Identifies architecture patterns from code structure
- Pulls dependency information for AI context
### Phase 3: Optimization
- Generates focused 33-slot IANA format
- Validates against format specification
- Scores AI-readiness with improvement suggestions
## Success Metrics by Project Type
| Project Type | Avg Score | Time to Bronze | Detection Rate |
|-------------|-----------|----------------|----------------|
| **React/Vue** | 89% | Instant | 99.8% |
| **Python Django** | 91% | Instant | 99.5% |
| **Rust CLI** | 85% | Instant | 99.1% |
| **Legacy PHP** | 76% | 30 seconds | 94.2% |
| **Monorepo** | 82% | 45 seconds | 91.8% |
## When to Use faf-expert Instead
Use `faf-wizard` for:
- ✅ Quick project onboarding
- ✅ Automatic everything
- ✅ "Just make it work"
- ✅ Time-constrained scenarios
Use `faf-expert` for:
- 🎯 Fine-tuned championship scoring (95%+)
- 🎯 Complex MCP server configuration
- 🎯 Multi-platform sync management
- 🎯 Enterprise deployment patterns
## Validation & Security
**Enterprise-Grade Standards:**
- ✅ **800+ comprehensive tests** across CLI and MCP
- ✅ **No credentials ever stored** in .faf files
- ✅ **YAML format validation** prevents malformed files
- ✅ **IANA-registered format** (application/vnd.faf+yaml)
- ✅ **MIT licensed** - safe for commercial use
## Getting Started
### For Your Current Project
```bash
# One command, done forever
npx faf-cli auto
# Check the results
cat project.faf
```
### For Any GitHub Repository
Install the browser extension and click "Generate FAF" on any repo.
### For Teams
```bash
# Set up team-wide MCP server
faf mcp install --team
faf sync --target all --watch
```
## Community & Support
- **Website**: https://faf.one
- **Chrome Extension**: 4.8★ rating, Google approved
- **Downloads**: 52k+ across ecosystem
- **Discord**: Active community of 1000+ developers
- **Documentation**: Comprehensive guides and examples
---
*Stop explaining your project every session. FAF Wizard - because AI should understand your project as well as you do.*
## 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.Related Skills
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