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interview-me

Develop a research idea through a structured conversation, then turn the answers into a written research specification. Clarify the question, testable hypothesis, data needs, methods for assessing cause and effect, expected findings, and feasibility.

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Structured conversational interview to formalise a research idea or extension into a concrete specification with hypotheses and empirical strategy. This skill should be used when asked to "interview me", "help me think through an idea", "formalise this idea", or "start fresh" on a new research direction.

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Good for

  • Turning an early research idea into a concrete plan
  • Exploring a new research direction from scratch
  • Identifying data needs and threats to causal interpretation
  • Documenting hypotheses, methods, and unresolved questions

Files included (1)

  • SKILL.md4.0 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Research Interview

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

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


How This Works

This is a conversational skill. Ask questions one at a time, probe deeper based on answers, and build toward a structured research specification.

Ask questions directly in text responses, one or two at a time. Wait for the user to respond before continuing.


Interview Structure

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?"

For this project, also probe:

  • Can this be answered with the existing EDM + Land Registry + Zoopla data?
  • Does this require new data (e.g. water company financials, bathing water quality, health data)?

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?"

After the Interview

Once enough information is gathered (typically 5-8 exchanges), produce:

Research Specification Document

# Research Specification: [Title]
**Date:** YYYY-MM-DD

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

## Data
- **Primary dataset:** [Name, source, coverage]
- **Key variables:** [Treatment, outcome, controls]
- **Sample:** [Unit of observation, time period, N]
- **Available in project:** [Yes/No — what exists vs what's needed]

## 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]

## Feasibility Assessment
- Data availability: [Ready / Partially available / Needs collection]
- Infrastructure reuse: [What from the existing pipeline can be reused]
- Estimated effort: [Low / Medium / High]

Save to output/log/research_spec_[topic].md.


Interview Style

  • Be curious, not prescriptive. Draw out the researcher's thinking, don't impose ideas.
  • Probe weak spots gently. "What would a sceptic say about...?" rather than "This won't work."
  • 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.
  • Project-aware. Connect ideas to the existing sewage project infrastructure where relevant.

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