research-ideation

name: research-ideation description: Generate structured research questions, testable hypotheses, and empirical strategies from a topic or dataset. disable-model-invocation: true argument-hint: "[topic, phenomenon, or dataset description]"

Research Ideation

Generate structured research questions, testable hypotheses, and empirical strategies.

Input: $ARGUMENTS -- a topic, phenomenon, or dataset description.

Steps

1. Understand the input. Read $ARGUMENTS and any referenced files. Check the knowledge base in .claude/rules/knowledge-base.md.

2. Generate 3-5 research questions ordered from descriptive to causal:

   • Descriptive: What are the patterns?
   • Correlational: What factors are associated?
   • Causal: What is the effect?
   • Mechanism: Why does the effect exist?
   • Policy: What are the implications?

3. For each question, develop:

   • Hypothesis: Testable prediction with expected sign/magnitude
   • Identification strategy: How to establish causality
   • Data requirements: What data is needed
   • Key assumptions: What must hold
   • Potential pitfalls: Threats to identification
   • Related literature: 2-3 papers

4. Rank by feasibility and contribution.

5. Save to quality_reports/research_ideation_[sanitized_topic].md

Principles

• Be creative but grounded. Every suggestion must be empirically feasible.
• Think like a top [Target Journal] referee. For each causal question, immediately identify the identification challenge and whether the contribution is clearly differentiated from the existing [your field] literature.
• Consider data availability. A brilliant question with no available data is not actionable.