skills/41-sticerd-eee-sewage-econometrics-check/skills/interview-me/SKILL.md
Structured conversational interview to formalise a research idea or extension into a concrete specification with hypotheses and empirical strategy. This skill should be used when asked to "interview me", "help me think through an idea", "formalise this idea", or "start fresh" on a new research direction.
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 formalise 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. Ask questions one at a time, probe deeper based on answers, and build toward a structured research specification.
Ask questions directly in text responses, one or two at a time. Wait for the user to respond before continuing.
For this project, also probe:
Once enough information is gathered (typically 5-8 exchanges), produce:
# Research Specification: [Title]
**Date:** YYYY-MM-DD
## 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]
- **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]
- **Available in project:** [Yes/No — what exists vs what's needed]
## 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]
## Feasibility Assessment
- Data availability: [Ready / Partially available / Needs collection]
- Infrastructure reuse: [What from the existing pipeline can be reused]
- Estimated effort: [Low / Medium / High]
Save to output/log/research_spec_[topic].md.
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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".