pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest +…
Full autonomous research workflow — brainstorm, plan, implement, review, and document
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill lfg --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/lfgContext preview
The summary Claude sees to decide when to auto-load this skill.
Full autonomous research workflow — brainstorm, plan, implement, review, and document
name: lfg description: Full autonomous research workflow — brainstorm, plan, implement, review, and document argument-hint: "[research task, estimation problem, or methodological improvement]" disable-model-invocation: true
Run these 5 slash commands in order. Do not do anything else. Do not stop between steps — complete every step through to the end.
1. `/workflows:brainstorm $ARGUMENTS` 2. `/workflows:plan` 3. `/workflows:work` 4. `/workflows:review` 5. `/workflows:compound`
**Hard gates:**
Start with step 1 now.
📌 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 |
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest +…
Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud /…
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest +…
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Systematic writing framework for philosophy and interdisciplinary academic papers from optimized outline to submission-ready manuscript. Use when users want…