/prd-score

command: prd-score
disable-model-invocation: true
description: Score an existing PRD against the 100-point AI-optimization framework
arguments:
  - name: file
    description: Path to the PRD file to score (relative or absolute)
    required: true

STOP - DO NOT INVOKE /skill OR Skill() AGAIN

This command is already executing. The PRD file to score is: **$ARGUMENTS.file**

Instructions

Score the PRD against the 100-point AI-optimization framework.

Step 1: Load the PRD

Read the file at `$ARGUMENTS.file` using the Read tool.

Step 2: Evaluate Against Framework

Score each category:

Category A: AI-Specific Optimization (25 points)

• Sequential Phases: 0-10 pts (phases ordered by dependencies, each 5-15 min work)
• Explicit Non-Goals: 0-8 pts (dedicated Non-Goals section with explicit boundaries)
• Structured Format: 0-7 pts (FR codes, consistent headings, Given-When-Then criteria)

Category B: Traditional PRD Core (25 points)

• Problem Statement: 0-7 pts (quantified pain points, metrics)
• Goals & Metrics: 0-8 pts (SMART goals, P0/P1 priorities)
• User Personas: 0-5 pts (named personas with scenarios)
• Technical Specs: 0-5 pts (architecture, integrations, data models)

Category C: Implementation Clarity (30 points)

• Functional Requirements: 0-10 pts (FR codes, P0/P1/P2, acceptance criteria)
• Non-Functional Requirements: 0-5 pts (security, performance, reliability)
• Architecture: 0-10 pts (diagrams, data flow, API contracts)
• Phased Implementation: 0-5 pts (clear phases, time estimates, deliverables)

Category D: Completeness (20 points)

• Risk Assessment: 0-5 pts (3-5 risks with mitigations)
• Dependencies: 0-3 pts (external and internal)
• Examples: 0-7 pts (code snippets, API examples)
• Documentation Quality: 0-5 pts (formatting, ToC, glossary)

Step 3: Generate Score Report

Output:

## PRD Score Report: [PRD Title]

### Overall Score: XX/100 ([Grade])

Grade Scale: A+ (90-100), A (80-89), B (70-79), C (60-69), D (<60)

| Category | Score | Max |
|----------|-------|-----|
| A. AI-Specific Optimization | XX | 25 |
| B. Traditional PRD Core | XX | 25 |
| C. Implementation Clarity | XX | 30 |
| D. Completeness | XX | 20 |

### Top 3 Improvement Recommendations
1. [Highest impact fix] - +X points
2. [Second priority] - +X points
3. [Third priority] - +X points

### Verdict
[1-2 sentence summary of PRD quality and AI-readiness]

Step 4: Offer Scoring Mode

After initial scoring, you MUST use AskUserQuestion to offer the user a choice:

AskUserQuestion({
  questions: [
    {
      question: "Would you like a rigorous multi-AI scoring pass?",
      header: "Scoring Rigor",
      multiSelect: false,
      options: [
        {label: "Standard (done)", description: "Single-model score — already complete above"},
        {label: "Rigorous", description: "Multi-AI scoring — 2-3 providers score independently, then consensus synthesis"}
      ]
    }
  ]
})

**WAIT for the user's answer before proceeding.**

**If Rigorous mode selected:**

🐙 **CLAUDE OCTOPUS ACTIVATED** — Multi-AI PRD Scoring

Providers: 🔴 Codex CLI — Implementation feasibility bias (catches vague technical specs) 🧭 Antigravity CLI — Completeness and industry standards bias (catches missing sections) 🔵 Claude — AI-optimization and structure bias (catches poor phasing)

**Rigorous workflow:** 1. Dispatch the PRD to 2-3 available providers, each scoring independently using the same 100-point framework 2. Collect individual scores and category breakdowns 3. Synthesize consensus: highlight where providers agree (high confidence) and where they diverge (areas to investigate) 4. Present combined score with per-provider variance

**Why this works:** Different models flag different weaknesses. Codex catches implementation gaps, Antigravity catches industry-standard omissions, and consensus scoring reduces single-model bias.

Step 5: Offer Improvements

After scoring, offer: 1. Revise the PRD - Apply top recommendations 2. Add missing sections - Generate specific missing content 3. Reformat for AI - Convert to AI-optimized structure 4. Export score - Save report to a file

**BEGIN NOW - read and score the PRD at: $ARGUMENTS.file**