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question-refiner

Transform raw research questions into structured, validated research prompts with automatic research

by yeheng|Open Source

Question Refiner

Overview

Transform vague research questions into structured, actionable research prompts through strategic clarifying questions with automatic research type detection and quality validation.

When to Use

  • User provides a raw, unstructured research question
  • Research scope is unclear or too broad
  • Need validated structured prompt for research-executor
  • Want to ensure prompt meets quality standards (≥8.0)

Core Approach

Progressive Questioning (2 rounds max):

  1. Round 1 (3 questions): Topic focus, output format, audience
  2. Round 2 (conditional): Scope, sources, special requirements
  3. Auto-detect research type → Select template → Generate & validate

Research Type Detection

TypeIndicatorsExample
Exploratory"what is", "overview", "landscape""What is the AI market like?"
Comparative"vs", "compare", "difference""Compare GPT-4 vs Claude"
Problem-Solving"how to", "solve", "fix""How to improve API performance"
Forecasting"future", "trend", "prediction""Future of quantum computing"
Deep Dive"technical", "architecture""How does BERT work internally"
Market Analysis"market", "industry", "competition""AI chip market analysis"

Output Structure

### RESEARCH TYPE
[auto-detected type]

### TASK
[Clear, specific research objective]

### CONTEXT/BACKGROUND
[Why this matters, who will use it]

### SPECIFIC QUESTIONS
1-7 concrete sub-questions

### KEYWORDS
[Search terms ≥5]

### CONSTRAINTS
- Timeframe: [e.g., 2020-present]
- Geography: [e.g., global]
- Source types: [academic, industry, news]

### OUTPUT FORMAT
- Type: [comprehensive_report|executive_summary|comparison_table]
- Citation style: [inline-with-url|footnotes]

### QUALITY SCORE
[0-10, must be ≥8.0]

Quality Validation

ComponentWeightCriteria
Completeness30%All required fields present
Specificity30%Questions are specific, not vague
Keyword Richness20%≥5 search terms with synonyms
Constraint Clarity20%Clear, realistic constraints

Process: Generate → Validate → If score < 8.0: Refine (max 2 attempts)

Token Optimization

📋 Reference: .claude/shared/constants/token_optimization.md

Context Budget: 10k tokens max

Error Handling

📋 Reference: .claude/shared/constants/error_codes.md

  • E001: Insufficient context → Ask clarifying questions
  • E003: Validation failed → Refine and retry
  • E004: Quality < 8.0 after retries → Request manual review

See also: Skill Base Template

Examples

See examples.md for detailed interaction patterns.

Detailed Instructions

See instructions.md for complete questioning strategy.

Download Skill