本项目包含两项Claude代码技能：

1. Stata — 一个全面参考资料，教Claude如何使用Stata。涵盖核心语法、数据管理、计量经济学、因果推断、图形和20+社区包。

2. Stata C 插件 — 一项技能，教 Claude 如何编写使用 C 插件完成任务的 Stata 代码。它包含 Claude 可以用来将现有包转换为 C 插件的信息，这些插件可以从 Stata 调用。这非常有用，因为这意味着你可以做一些在 Stata 里很难做到的事情。

只要你能找到现有的包，你就可以让Claude去查看现有的Python包，这项技能提供了一个工作流程，Claude可以用来开发用Python、R或其他语言实现的复制，运行在Stata上，并使用C插件。在很多情况下，如果不是大多数，你应该能在Stata中获得至少和原语言一样快，甚至更快的东西。

安装

在Claude Code中将此仓库添加为市场：

然后安装适合你需求的选项：

Stata Skills for Claude Code

This project contains two Claude Code skills:

1. Stata — A comprehensive reference that tells Claude how to use Stata. Covers core syntax, data management, econometrics, causal inference, graphics, and 20+ community packages.

2. Stata C Plugins — A skill that tells Claude how to make Stata code that uses C plugins to do things. It includes information that Claude can use to translate existing packages into C plugins that can be called from Stata. This is very useful because it means you can do things in Stata that you wouldn’t otherwise be able to do very easily.

As long as you can find an existing package somewhere, you can just let Claude go look at the existing Python package and this skill provides a workflow that Claude can use to develop a replication of whatever it is, implemented in Python or R or whatever, that runs in Stata and uses a C plugin. In many if not most cases, you should be able to get something that runs at least as fast in Stata as it did in the original language, if not faster.

Installation

Add this repo as a marketplace in Claude Code:

/plugin marketplace add dylantmoore/stata-skill

Then install whichever option fits your needs:

You can also find this and other plugins via the claude-plugins collection.

What’s Included

Skill 1: Stata

37 core reference files covering:

• Data import/export, management, and cleaning
• Linear regression, panel data, time series
• Limited dependent variables, survival analysis, SEM
• Causal inference: DiD, RD, matching, treatment effects
• Mata programming and matrix operations
• Graphics, tables, and reporting
• Workflow best practices

20 community package guides including:

• reghdfe — high-dimensional fixed effects
• estout / outreg2 — publication-quality tables
• csdid, did_multiplegt — modern DiD estimators
• rdrobust — regression discontinuity
• psmatch2 — propensity score matching
• synth — synthetic control
• ivreg2 / xtabond2 — IV and dynamic panel GMM
• And more (binsreg, coefplot, grstyle, winsor2, gtools, …)

Skill 2: Stata C Plugins

Reference files covering:

• Stata plugin SDK (stplugin.h) setup and data flow
• Memory safety, debugging, and common failure modes
• .ado wrapper patterns (preserve/merge, plugin loading)
• Cross-platform compilation (macOS, Linux, Windows)
• Performance optimization (pthreads, pre-sorted indices, XorShift RNG)
• Packaging and distribution via net install
• Translation workflow for porting Python/R packages to Stata
• Testing strategy with correlation-based validation against reference implementations

How It Works