pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy +…
Run holistic pedagogical review on lecture slides. Checks narrative arc, student prerequisites, worked examples, notation clarity, and deck pacing.
Claude Code
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill pedagogy-review --agent claude-code
Codex
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill pedagogy-review -a codex -y
Cursor
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill pedagogy-review -a cursor -y
Gemini CLI
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill pedagogy-review -a gemini-cli -y
GitHub Copilot
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill pedagogy-review -a github-copilot -y
OpenCode
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill pedagogy-review -a opencode -y
Windsurf
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill pedagogy-review -a windsurf -y
name: pedagogy-review description: Run holistic pedagogical review on lecture slides. Checks narrative arc, student prerequisites, worked examples, notation clarity, and deck pacing. argument-hint: "[QMD or TEX filename]" allowed-tools: ["Read", "Grep", "Glob", "Write", "Task"]
Perform a comprehensive pedagogical review.
1. **Identify the file** specified in `$ARGUMENTS`
2. **Launch the pedagogy-reviewer agent** with the full file path
3. **The agent produces a report** saved to: `quality_reports/[FILENAME_WITHOUT_EXT]_pedagogy_report.md`
4. **Present summary to user:**
## 🔥 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
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