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:

faf score --verbose

Or get it as structured data for programmatic use:

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:

# 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

{
  "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

{
  "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

{
  "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

{
  "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

{
  "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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