pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy +…
Utility commands — commit, compile, validate-bib, journal, context-status, deploy, learn. Replaces individual utility skills.
Claude Code
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill tools --agent claude-code
Codex
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill tools -a codex -y
Cursor
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill tools -a cursor -y
Gemini CLI
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill tools -a gemini-cli -y
GitHub Copilot
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill tools -a github-copilot -y
OpenCode
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill tools -a opencode -y
Windsurf
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill tools -a windsurf -y
name: tools description: Utility commands — commit, compile, validate-bib, journal, context-status, deploy, learn. Replaces individual utility skills. argument-hint: "[subcommand: commit | compile | validate-bib | journal | context | deploy | learn | upgrade] [args]" allowed-tools: Read,Grep,Glob,Write,Edit,Bash,Task
Utility subcommands for project maintenance and infrastructure.
**Input:** `$ARGUMENTS` — subcommand followed by any arguments.
---
Stage changes, create commit, optionally create PR and merge.
3-pass XeLaTeX + bibtex compilation.
For papers:
cd Paper && TEXINPUTS=../Preambles:$TEXINPUTS xelatex -interaction=nonstopmode [file] BIBINPUTS=..:$BIBINPUTS bibtex [file_base] TEXINPUTS=../Preambles:$TEXINPUTS xelatex -interaction=nonstopmode [file] TEXINPUTS=../Preambles:$TEXINPUTS xelatex -interaction=nonstopmode [file]
For talks:
cd Talks && TEXINPUTS=../Preambles:$TEXINPUTS xelatex -interaction=nonstopmode [file]
Cross-reference all \cite{} keys in paper and talk files against Bibliography_base.bib. Report: missing entries, unused entries, duplicate keys.
Regenerate the research journal timeline from quality reports and git history. Shows chronological record of agent actions, phase transitions, scores, decisions.
Show current context status and session health. Check context usage, whether auto-compact is approaching, what state will be preserved.
Render Quarto guide site and publish to GitHub Pages.
cd guide && quarto publish gh-pages --no-browser
Extract reusable knowledge from the current session. Auto-memory handles corrections automatically; this is for multi-step workflows worth turning into a full skill.
Upgrade an existing project to the latest clo-author architecture.
**What it does:** 1. Clone the latest clo-author release into a temp directory 2. Save the user's filled-in domain-profile.md and any custom journal profiles 3. Delete the old `.claude/` directory 4. Copy the new `.claude/` in 5. Restore the user's domain-profile.md and custom journal profiles 6. Optionally copy new `templates/` 7. Report what changed
**Workflow:**
Step 1: DOWNLOAD - Clone latest clo-author into /tmp/clo-author-upgrade - Or: gh release download --repo hugosantanna/clo-author Step 2: PRESERVE USER CUSTOMIZATIONS - Save .claude/references/domain-profile.md if filled in (not just placeholders) - Save any custom journal profiles the user added to journal-profiles.md - Save .claude/settings.json (user's permissions and hooks) - Save .claude/settings.local.json if it exists Step 3: REPLACE - Delete old .claude/ entirely - Copy new .claude/ from the downloaded release - Restore saved customizations from Step 2 Step 4: DO NOT TOUCH - paper/, scripts/, data/, explorations/, quality_reports/ - CLAUDE.md, Bibliography_base.bib, README.md, .gitignore - Any other user content Step 5: REPORT - List what was updated (new agents, skills, rules) - List what was preserved (domain profile, settings, custom profiles) - Clean up temp directory
**No git merge. No upstream remote. No conflicts.** Just delete and replace `.claude/`.
---
## 🔥 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…