Requirement Clarification Skill
Purpose
Transform ambiguous user requests into clear, implementable requirements.
When to Use
- After research phase completes
- Before planning phase begins
- When user requirements are unclear
- For non-technical user requests
Question Templates
For Scope Clarification
See question-templates/scope-questions.md
Common patterns:
- "Should [feature] also handle [edge case]?"
- "When [condition], what should happen?"
- "Is [assumption] correct, or do you need [alternative]?"
For Technical Decisions
See question-templates/technical-questions.md
Common patterns:
- "Do you have a preference between [A] and [B] for [purpose]?"
- "Should this integrate with [existing system]?"
- "What level of [performance/security] is required?"
For Constraints
See question-templates/constraint-questions.md
Common patterns:
- "Is there a deadline for this?"
- "Are there any [technology/approach] restrictions?"
- "Who will be using this feature?"
Question Quality Checklist
Each question must be:
Question Priority Levels
Must Answer (Blocking)
- Questions that block planning if unanswered
- Maximum 10 blocking questions
- Always provide defaults
Should Answer (Important)
- Questions that improve implementation quality
- Can proceed with defaults if not answered
Could Answer (Nice to Have)
- Questions for optimization
- Low impact on core implementation
Validation Script
Run scripts/validate-requirements.py to check:
- All blocking questions answered
- No contradictory requirements
- Technical feasibility confirmed
- Confidence levels assigned
python scripts/validate-requirements.py <session-id>
Output Location
- Questions:
docs/specs/questions-{session}.md
- Requirements:
docs/specs/requirements-{session}.md
Integration with Workflow
- Research phase produces findings in
docs/research/
- This skill generates questions from those findings
- User answers questions
- Validated requirements document is produced
- Planning phase can begin