pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy +…
Start a new research project by conducting a structured interview to formalize a research idea, then generates research questions with identification strategies and a project spec. Make sure to use this skill whenever the user wants to develop or document a new research idea —
Claude Code
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill new-project --agent claude-code
Codex
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill new-project -a codex -y
Cursor
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill new-project -a cursor -y
Gemini CLI
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill new-project -a gemini-cli -y
GitHub Copilot
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill new-project -a github-copilot -y
OpenCode
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill new-project -a opencode -y
Windsurf
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill new-project -a windsurf -y
name: new-project description: >- Start a new research project by conducting a structured interview to formalize a research idea, then generates research questions with identification strategies and a project spec. Make sure to use this skill whenever the user wants to develop or document a new research idea — not to search for literature or data. Triggers include: "new project", "start research", "I have an idea", "help me develop this", "I want to study X", "help me formalize this idea", "what's my research question", "what identification strategy should I use", "write up my project idea", or when the user describes a topic they want to turn into a paper. argument-hint: "[brief topic or 'start fresh']" allowed-tools: ["Read", "Grep", "Glob", "Write"]
Formalize a research idea into a concrete project specification with testable hypotheses and empirical strategies.
**Input:** `$ARGUMENTS` — a topic, phenomenon, dataset, or "start fresh" for open-ended exploration.
This skill runs in **three phases**. Phase 1 is conversational — ask one or two questions at a time and wait for responses. Phases 2 and 3 run automatically after the interview.
---
**Goal:** Draw out the researcher's thinking and establish a clear research question.
Ask questions **one or two at a time**. Build on each answer before moving to the next phase. Do NOT use AskUserQuestion — ask directly in your response. A good interview runs 4–6 exchanges.
**The Puzzle (start here):**
**Why It Matters:**
**Theoretical Motivation:**
**Data and Setting:**
**Identification:**
**Expected Results + Contribution:**
Move to Phase 2 when you have:
If after 3 exchanges the user keeps giving vague answers, move to Phase 2 anyway and flag the open questions.
---
**Goal:** Generate 3–5 structured research questions covering the full range from descriptive to causal.
Announce the transition: *"Great — I have enough to generate a structured set of research questions. Let me build that out now."*
Then generate **3–5 research questions** ordered by type:
| Type | What It Asks | |------|-------------| | **Descriptive** | What are the patterns? How has X evolved? | | **Correlational** | What factors are associated with X, controlling for Z? | | **Causal** | What is the causal effect of X on Y? | | **Mechanism** | Through what channel does X affect Y? | | **Policy** | Would intervention X improve outcome Y? |
**For each RQ, develop:**
**Rank the questions** by feasibility × contribution:
| RQ | Feasibility | Contribution | Priority | |----|-------------|-------------|----------| | 1 | High | High | ★★★ | | 2 | High | Medium | ★★ | | ... | ... | ... | ... |
---
Produce the unified project spec document and save it.
**Save to:** `quality_reports/project_spec_[sanitized_topic].md`
# Research Project: [Working Title] **Date:** [YYYY-MM-DD] **Researcher:** [from CLAUDE.md if available] --- ## Research Question [Single clear sentence] ## Motivation [2–3 paragraphs: why this matters, theoretical context, policy relevance, what the answer would change] ## Research Questions ### RQ1: [Question] — Priority: ★★★ (Feasibility: High / Contribution: High) **Type:** Causal **Hypothesis:** [Testable prediction with expected sign] **Identification Strategy:** - **Method:** [e.g., Staggered DiD with Sun–Abraham estimator] - **Treatment:** [What varies and when] - **Control group:** [Comparison units] - **Key assumption:** [e.g., Parallel pre-trends conditional on controls] - **Robustness:** [Pre-trends test, placebo outcomes, alternative control groups] **Data Requirements:** - [Dataset or data type needed] - [Key variables: treatment proxy, outcome, controls] - [Time period and geography] **Key Pitfalls:** 1. [Threat + mitigation] 2. [Threat + mitigation] **Related Work:** [Author (Year)], [Author (Year)] --- [Repeat for RQ2–RQ5] --- ## Priority Empirical Strategy [1 paragraph recommending the single highest-priority RQ and why, with the specific identification approach] ## Open Questions [Issues raised in the interview that need fur
## 🔥 力荐 · StatsPAI — Stata 与 R 的 Python 平替,为 AI Agent 而生 🔁 Stata / R 平替:reghdfe、csdid、rdrobust、synth、fixest、did 等常用命令在 Python 中一站式替代,一个 import statspai as sp 搞定 DID / RD / IV / SCM / DML / matching 🤖 面向 Agent 设计:结构化结果对象 + 内置 MCP Server,Claude / Codex
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy +…
Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics…
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy +…
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid +…
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem — dplyr + tidyr + haven +…
Systematic writing framework for philosophy and interdisciplinary academic papers from optimized outline to submission-ready…
Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work. Also covers…
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling…