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/interview-me

Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy

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auto-empirical-research-skills
3.3k200 skills146 agents
Install
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill interview-me --agent claude-code

How 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

Context preview

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.md
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.
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Ships withauto-empirical-research-skills

📌 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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