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AI-optimized PRD creation with 100-point scoring framework
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Smoke-test fixture for the stdio MCP integration tests. Returns a constant body when called.
Multi-AI requirements scoping using Codex and Gemini CLIs (Double Diamond Define phase). Use when: AUTOMATICALLY ACTIVATE when user requests clarification or scoping:. "define the requirements for X". "clarify the scope of Y"
Multi-AI validation, scoring, and review using Codex and Gemini CLIs (Double Diamond Deliver phase). Use when: AUTOMATICALLY ACTIVATE when user requests validation, scoring, or review:. "review X" or "validate Y" or "test Z". "score this", "quality check", "validate before shipping"
Multi-AI implementation using Codex and Gemini CLIs (Double Diamond Develop phase). Use when: AUTOMATICALLY ACTIVATE when user requests building or implementation:. "build X" or "implement Y" or "create Z". "develop a feature for X"
Multi-AI research using Codex and Gemini CLIs (Double Diamond Discover phase). Use when: AUTOMATICALLY ACTIVATE when user requests research or exploration:. "research X" or "explore Y" or "investigate Z". "what are the options for X" or "what are my choices for Y"
NLSpec authoring — structured specification from multi-AI research
| name | skill-prd |
| version | 1.0.0 |
| description | AI-optimized PRD creation with 100-point scoring framework |
DO NOT call Skill() again. DO NOT load any more skills. Execute directly.
Before writing ANY PRD content, you MUST ask the user these questions:
I need to understand your requirements before creating the PRD.
1. **Target Users**: Who will use this? (developers, end-users, admins, etc.)
2. **Core Problem**: What specific pain point does this solve? Any metrics?
3. **Success Criteria**: How will you measure if this succeeds?
4. **Constraints**: Any technical, budget, or timeline constraints?
5. **Existing Context**: Is this greenfield or integrating with existing systems?
Please answer these (even briefly) so I can create a more targeted PRD.
WAIT for user response before proceeding to Phase 1.
If user says "skip" or provides the feature description inline, extract what you can and note assumptions.
Only search if topic is unfamiliar. Limit to 2 web searches max:
Do NOT over-research. 60 seconds max for this phase.
Structure:
After drafting the PRD but BEFORE self-scoring, dispatch the draft to a second provider for adversarial review. A single-model PRD has blind spots — cross-provider challenge surfaces wrong assumptions, uncovered scenarios, and contradictory requirements.
Dispatch the PRD draft to a different provider (Codex, Gemini, or Sonnet as fallback) with this prompt:
"Challenge this PRD. What assumptions are wrong? What user scenarios are missing? What requirements contradict each other? What will the first user complaint be? What risk does this PRD ignore?"
After receiving the challenge:
Adversarial review: appliedSkip with --fast or when user requests speed over thoroughness. See prd.md command for full dispatch syntax.
Score against 100-point framework:
Write to user-specified filename or generate based on feature name.
START WITH PHASE 0 CLARIFICATION QUESTIONS NOW.