interview-me

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

857 stars

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

$curl -o ~/.claude/skills/interview-me/SKILL.md --create-dirs "https://raw.githubusercontent.com/pedrohcgs/claude-code-my-workflow/main/.claude/skills/interview-me/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/interview-me/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How interview-me Compares

Feature / Agentinterview-meStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/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.

Related Guides

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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