/interview-me
Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill interview-me --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/interview-me
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The summary Claude sees to decide when to auto-load this skill.
Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy
SKILL.md
interview-me.SKILL.mdname: interview-me
description: Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy
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.
---
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**:
# 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.
Read more
name: interview-me description: Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy 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.
---
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**:
# 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.
📌 文档结构(2026-07-22 起): 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md(扩展正文,总表行内的 → 直接跳转到对应锚点)。 English version: README-en.md · 中文扩展正文:docs/CONTENT_ZH.md · README-zh-CN.md 已弃用(重定向占位) 🌐 语言: English |
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