interview-me
Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy
Best use case
interview-me is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy
Teams using interview-me should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/interview-me/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How interview-me Compares
| Feature / Agent | interview-me | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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. --- ## 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. --- ## 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?" ### 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 you have enough information (typically 5-8 exchanges), produce a **Research Specification Document**: ```markdown # Research Specification: [Title] **Date:** [YYYY-MM-DD] **Researcher:** [from conversation context] ## 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 with staggered adoption] - **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] ## 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` --- ## 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.
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