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Updated today

by brycewang-stanford

StatsPAI

StatsPAI is the first Agent-native Python library for causal inference and applied econometrics — unified API, broad cross-method coverage, structured result objects, machine-readable schemas, Skills, an MCP server, and R/Stata parity validation.

  • Active — Updated in the last 14 days
View on GitHub (opens in a new tab)

340 GitHub stars (340)

+12 in 16 days

Stars gained per day · daily snapshots since Sep 30
Stars gained per day, Sep 30 to Oct 16: +12 in total; the busiest day was Oct 13 with +4 stars.Oct 1: 0 starsOct 2: 0 starsOct 3: +1 starsOct 4: +1 starsOct 5: 0 starsOct 6: 0 starsOct 7: +1 starsOct 8: +1 starsOct 9: −1 starsOct 10: +1 starsOct 11: 0 starsOct 12: +2 starsOct 13: +4 starsOct 14: 0 starsOct 15: +2 starsOct 16: 0 stars
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Oct 160
  • 2 skills (2 skills found in its SKILL.md files)
  • 72 forks (72 forks)
  • Today last update (Last updated today)

Install

Skills CLI

npx skills add brycewang-stanford/StatsPAI

Asks which skills and agents to install. Just one: npx skills add brycewang-stanford/StatsPAI --skill StatsPAI_skill — add -g for every project.

Claude Code

git clone https://github.com/brycewang-stanford/StatsPAIcp -r "StatsPAI/StatsPAI_full_data_analysis_skill" ~/.claude/skills/

Copies the StatsPAI_skill skill into ~/.claude/skills/ for every project (use .claude/skills/ for one project). Repeat for the other skills listed below.

Plugin

/plugin marketplace add brycewang-stanford/StatsPAI

Run inside Claude Code if the repository ships a plugin marketplace, then pick plugins from /plugin.

Skills can run code on your machine — read the SKILL.md first.

What it does

In the author's own words, from each skill's SKILL.md.

  • StatsPAI_skill

    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 / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 / Table 2 / event-study figure / robustness gauntlet — OR in epidemiology / public health style (target-trial emulation, IPTW…

    StatsPAI_full_data_analysis_skill/SKILL.md on GitHub (opens in a new tab)

  • statspai-analysis

    Run a full empirical / causal analysis in Python with StatsPAI (import statspai as sp) — applied-economics style (DID / RD / IV / synthetic control / DML / matching with estimating equation, identifying assumption, Table 1, main table, event-study figure, robustness gauntlet, Word / Excel / LaTeX export), epidemiology style (target-trial emulation, IPTW + g-formula + TMLE, Mendelian randomization…

    src/statspai/agent/_skill/SKILL.md on GitHub (opens in a new tab)

Review before you install

A skill is a set of instructions and scripts your agent will follow, and it can run code on your machine. Read the SKILL.md and any scripts first — this listing is not a security review.