skill

Answer Collector Skill

Purpose: Incrementally collect and validate product assessment responses in structured JSON format.

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When to Use

• Evaluating new product ideas with rigorous criteria
• Conducting go/no-go assessments before committing resources
• Building a decision audit trail for product decisions
• Gathering structured input from teams or stakeholders
• Progressive refinement of product hypotheses

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How It Works

1. Reading Questions

Questions are organized in 4 sections (questions.md):

• WHY (4 Q's): Problem, strategy, resources, timing
• WHO (4 Q's): User, access, economics, scale
• WHAT (5 Q's): Outcome, monetization, success metrics, fit, risk
• GO/NO-GO (4 criteria): Checklist for final decision

Each question is numbered 1-17.

2. Writing JSON Incrementally

Start with a template and add answers one at a time:

{
  "metadata": {
    "product_name": "Your Product Name",
    "created_at": "2025-11-03T00:00:00Z",
    "status": "in_progress"
  },
  "answers": {
    "why_section": {
      "q1_problem_evidence": "Answer here..."
    }
  }
}

Build incrementally:

• Add one answer per interaction
• Preserve all previous answers
• Update last_updated timestamp
• Track completion_percentage in metadata

3. Validation Logic

Auto-calculate:

• answered_questions: Count non-empty answers
• completion_percentage: (answered_questions / 17) × 100
• go_no_go_result: "go" if all 4 checklist items true, else "no_go" or "pending"

Validation rules:

• All text answers must be non-empty and substantive
• Checklist items (q14-q17) must be boolean (true/false)
• Metadata fields (product_name) required to start
• All timestamps in ISO 8601 format

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Quick Reference

Section	Questions	Type
WHY	1-4	Text
WHO	5-8	Text
WHAT	9-13	Text
GO/NO-GO	14-17	Boolean

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Usage Pattern

1. Initialize: Create JSON with metadata and product_name
2. Collect: Answer one question, validate, save
3. Review: Check completion_percentage and go_no_go_result
4. Decide: When all answers complete, review go_no_go_result