skills/28-maxwell2732-paper-replicate-agent-demo/dot-claude/skills/interview-me/SKILL.md
Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research interview-meInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
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.
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
tools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
tools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".