Faf Go

---
name: faf-go
description: Guided interview to Gold Code (100% AI-Readiness). Use when helping users improve their .faf file through questions. Leverages Claude Code's AskUserQuestion for seamless integration. Just type /faf-go
category: Document Processing
source: antigravity
tags: [python, javascript, react, api, mcp, claude, ai, agent, workflow, template]
url: https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/faf-go
---


# FAF Go — Guided Path to 100% ✪

**"Just type /faf-go, answer questions till you're done. 100% target."**

`.faf` is an **IANA-registered context format** (`application/vnd.faf+yaml`) — a typed, portable file *you own*, readable by any AI. **faf-cli scores on 21 slots**; your `app_type` selects which are *active*, and **100% ✪ = every active slot filled**. This skill is the guided interview that gets you there: the AI fills what it can detect, then asks you — via Claude Code's AskUserQuestion — only for the gaps it can't source.

## When to Use This Skill

Activate when:
- User wants to improve their .faf score
- User mentions "Gold Code" or "100%"
- User has incomplete project context
- After `faf init` to fill in missing fields
- User says "help me with my .faf"

## Integration with Claude Code

FAF Go is built FOR Claude Code:
- **AskUserQuestion** - Native Claude Code UI for questions
- **multiSelect: true** - Allow multiple answers (e.g., "pytest + WJTTC")
- **TodoWrite** - Track progress through the interview
- **Structured output** - JSON that Claude Code understands
- **Bi-sync** - Answers flow to .faf AND CLAUDE.md

### multiSelect Support

Some questions allow multiple selections:
- `stack.testing` → "pytest + WJTTC"
- `stack.cicd` → "GitHub Actions + Cloud Build"
- `stack.frontend` → "React + Tailwind"
- `human_context.who` → "Developers + AI agents"

When `multiSelect: true`, user can pick 2+ options. Results are joined with " + ".

## Workflow

### Step 1: Check Current State

Run faf score to understand current position:

```bash
faf score --verbose
```

Or get it as structured data for programmatic use:

```bash
faf score --json
```

`--json` returns the score + per-slot breakdown — the empty slots are what you interview on (the priority order is in Step 2).

### Step 2: Ask Questions Using AskUserQuestion

For each missing field, use Claude Code's AskUserQuestion tool:

**Priority Order (most impactful first):**
1. `project.goal` - What does this project do?
2. `human_context.why` - Why does this exist?
3. `human_context.who` - Who uses this?
4. `human_context.what` - What problem does it solve?
5. `project.main_language` - Primary language
6. `stack.database` - Database choice
7. `stack.hosting` - Where is it deployed?
8. `stack.frontend` - Frontend framework
9. `stack.backend` - Backend framework
10. `human_context.where` - Environment
11. `human_context.when` - Timeline/phase
12. `human_context.how` - How the project is built (sourced from the stack)

### Step 3: Apply Answers

After collecting answers, update the .faf file:

```bash
# Read current .faf
cat project.faf

# Update fields (use Edit tool)
# Then verify:
faf score
```

### Step 4: Celebrate or Continue

If score >= 100: Celebrate Gold Code achievement
If score < 100: Continue with remaining questions

## Question Templates for AskUserQuestion

### Single-Select Questions (pick one)

#### project.goal
```json
{
  "question": "What does this project do? (one clear sentence)",
  "header": "Goal",
  "multiSelect": false,
  "options": [
    {"label": "Let me type it", "description": "I'll describe it myself"},
    {"label": "Help me write it", "description": "Guide me through it"}
  ]
}
```

#### human_context.why
```json
{
  "question": "Why does this project exist?",
  "header": "Why",
  "multiSelect": false,
  "options": [
    {"label": "Business need", "description": "Solving a business problem"},
    {"label": "Personal project", "description": "Learning or hobby"},
    {"label": "Open source", "description": "Community contribution"},
    {"label": "Let me explain", "description": "Custom reason"}
  ]
}
```

#### stack.database
```json
{
  "question": "What database do you use?",
  "header": "Database",
  "multiSelect": false,
  "options": [
    {"label": "PostgreSQL", "description": "Relational database"},
    {"label": "MongoDB", "description": "Document database"},
    {"label": "SQLite", "description": "File-based database"},
    {"label": "None", "description": "No database"}
  ]
}
```

#### stack.hosting
```json
{
  "question": "Where is this deployed?",
  "header": "Hosting",
  "multiSelect": false,
  "options": [
    {"label": "Vercel", "description": "Frontend/serverless"},
    {"label": "AWS", "description": "Amazon Web Services"},
    {"label": "Local only", "description": "Not deployed"},
    {"label": "Other", "description": "Different platform"}
  ]
}
```

### Multi-Select Questions (pick multiple, joined with " + ")

#### stack.testing
```json
{
  "question": "What testing tools/methodologies do you use?",
  "header": "Testing",
  "multiSelect": true,
  "options": [
    {"label": "pytest", "description": "Python testing framework"},
    {"label": "Jest", "description": "JavaScript testing"},
    {"label": "Vitest", "description": "Vite-native testing"},
    {"label": "WJTTC", "description": "Championship methodology (Layer 2)"}
  ]
}
```
**Result format:** `pytest + WJTTC` (industry first, WJTTC follows)

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