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.
This repository also configures its own agents. See what StatsPAI tells them →
Skill Claude CodeCodex
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…
Skill Claude CodeCodex
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…