interview-me

name	interview-me
description	Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy
disable-model-invocation	true
argument-hint	[brief topic or 'start fresh']
allowed-tools	["Read","Write"]

Research Interview

Conduct a structured interview to help formalize a research idea into a concrete specification.

Input: $ARGUMENTS — a brief topic description or "start fresh" for an open-ended exploration.

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How This Works

This is a conversational skill. Instead of producing a report immediately, you conduct an interview by asking questions one at a time, probing deeper based on answers, and building toward a structured research specification.

Do NOT use AskUserQuestion. Ask questions directly in your text responses, one or two at a time. Wait for the user to respond before continuing.

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Interview Structure

Phase 0: Project Type (always first — 1 question)

Ask this before anything else:

"Before we dig into your research question, it helps to understand what kind of paper you're aiming to write. Which of these best describes it?

(A) Reduced-Form Empirical — You want to identify causal effects using data (DiD, RDD, IV, event study, etc.). The core deliverable is an estimated causal effect.

(B) Pure Theory — You want to build a formal model: propositions, proofs, comparative statics. No data or estimation required.

(C) Structural Estimation — You want to build a formal model AND estimate its parameters using data (MLE, GMM, SMM, BLP, etc.). Theory and empirics are tightly coupled.

(D) Empirical + Motivating Theory — Primarily empirical, but with a formal theory section that generates testable predictions motivating your empirical design.

There's no wrong answer — this just determines which tools and agents we'll use."

Wait for the user to choose before proceeding to Phase 1. Record the answer as project_type (one of: empirical, theory, structural, empirical+theory).

Phase routing based on project type:

• theory: Skip Phase 3 (Data) and Phase 4 (Identification). Probe model structure deeply in Phase 2.
• structural: Keep all phases. In Phase 3, add: "What will you estimate? What are the key structural parameters?"
• empirical+theory: Keep all phases. In Phase 2, probe how the theory generates testable predictions.
• empirical: Run all phases as normal.

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Phase 1: The Big Picture (1-2 questions)

• "What phenomenon or puzzle are you trying to understand?"
• "Why does this matter? Who should care about the answer?"

Phase 2: Theoretical Motivation (1-2 questions)

• "What's your intuition for why X happens / what drives Y?"
• "What would standard theory predict? Do you expect something different?"

Phase 3: Data and Setting (1-2 questions)

• "What data do you have access to, or what data would you ideally want?"
• "Is there a specific context, time period, or institutional setting you're focused on?"

Phase 4: Identification (1-2 questions)

• "Is there a natural experiment, policy change, or source of variation you can exploit?"
• "What's the biggest threat to a causal interpretation?"

Phase 5: Expected Results (1-2 questions)

• "What would you expect to find? What would surprise you?"
• "What would the results imply for policy or theory?"

Phase 6: Contribution (1 question)

• "How does this differ from what's already been done? What's the gap you're filling?"

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After the Interview

Once you have enough information (typically 5-8 exchanges), produce TWO outputs:

Output 1: Domain Profile

If .claude/rules/domain-profile.md still contains placeholders, fill it in based on the interview. This calibrates all agents to the researcher's field:

• Field & adjacent subfields — inferred from the topic
• Target journals — ranked by tier for this field
• Common data sources — datasets typical for this area
• Common identification strategies — designs used in this literature
• Field conventions — estimation quirks, outcome transformations, clustering norms
• Seminal references — papers every referee will expect you to cite
• Field-specific referee concerns — the "gotcha" questions referees always ask

Save directly to .claude/rules/domain-profile.md (overwrite the template).

If the domain profile is already filled (from a previous interview or manual entry), confirm with the user whether to update or keep the existing one.

Output 2: Research Specification Document

Produce a Research Specification Document:

# Research Specification: [Title]

**Date:** [YYYY-MM-DD]
**Researcher:** [from conversation context]

## Project Type
[empirical / theory / structural / empirical+theory]

## Recommended Pipeline
[List the relevant commands for this type — see .claude/WORKFLOW_QUICK_REF.md]

## Research Question

[Clear, specific question in one sentence]

## Motivation

[2-3 paragraphs: why this matters, theoretical context, policy relevance]

## Hypothesis

[Testable prediction with expected direction]

## Empirical Strategy
<!-- Skip this section for type = theory -->

- **Method:** [e.g., Difference-in-Differences with staggered adoption]
- **Treatment:** [What varies]
- **Control:** [Comparison group]
- **Key identifying assumption:** [What must hold]
- **Robustness checks:** [Pre-trends, placebo tests, etc.]

## Theoretical Model
<!-- Fill this section for type = theory, structural, or empirical+theory -->

- **Model type:** [e.g., principal-agent, search, spatial, dynamic discrete choice]
- **Key agents/players:** [Who decides what]
- **Core mechanism:** [The economic logic to be formalized]
- **Main predictions:** [Propositions you expect to derive]
- **Structural parameters (if applicable):** [What will be estimated]

## Data
<!-- Skip this section for type = theory -->

- **Primary dataset:** [Name, source, coverage]
- **Key variables:** [Treatment, outcome, controls]
- **Sample:** [Unit of observation, time period, N]

## Expected Results

[What the researcher expects to find and why]

## Contribution

[How this advances the literature — 2-3 sentences]

## Open Questions

[Issues raised during the interview that need further thought]

Save to: quality_reports/research_spec_[sanitized_topic].md

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Interview Style

• Be curious, not prescriptive. Your job is to draw out the researcher's thinking, not impose your own ideas.
• Probe weak spots gently. If the identification strategy sounds fragile, ask "What would a skeptic say about...?" rather than "This won't work because..."
• Build on answers. Each question should follow from the previous response.
• Know when to stop. If the researcher has a clear vision after 4-5 exchanges, move to the specification. Don't over-interview.