Borrowing it
Nothing to install: this file belongs to lianxhcn/stata-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lianxhcn/stata-ai/main/CLAUDE.mdgit clone --depth 1 https://github.com/lianxhcn/stata-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/lianxhcn/stata-ai/claude-md)<a href="https://agentmods.dev/instructions/lianxhcn/stata-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/lianxhcn/stata-ai/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/lianxhcn/stata-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/lianxhcn/stata-ai/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01255 | $0.01255 |
| Opus 5 | $0.00628 | $0.00628 |
| Sonnet 5 | $0.00251 | $0.00251 |
| Haiku 4.5 | $0.00126 | $0.00126 |
Grade A, and why
stata-ai CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — stata-ai 项目指南
本文件是本项目中 AI Agent(Claude Code / Codex)的总指南。开始任何工作前先读完本文件, 再按
working/00-PLAN.md的流水线逐个执行任务。
1. 项目是什么
- 这是连玉君老师 2026-07-12 公开课「Stata 简介与 AI 辅助实证」的课程仓库。
- 用 Quarto book 编译,通过 GitHub Pages 发布,网址形如 https://lianxhcn.github.io/stata-ai 。
- 仓库有三重身份:课程主页、听众课后自学的配置手册、可下载复现的演示项目(demo/)。
- 风格基准:与 ci-policy 仓库(本地路径见
_materials/三个仓库的本地路径.md)保持一致—— 简体中文、导航结构、页脚 lianxh.cn 链接、克制的 emoji 使用。
2. 目录约定
stata-ai/
├── CLAUDE.md # 本文件(不推送远程)
├── working/ # 过程文档:任务书、规格、真值记录(不推送远程)
├── _task/ # 老师自己的任务备忘(不推送远程)
├── _materials/ # 原始素材与收割文件(不推送远程)
├── _quarto.yml # T2 生成
├── index.qmd 等 # T2 生成的正式页面
├── lectures/ # 四讲讲义
├── appendix/ # 附录 A-D
├── demo/ # 演示项目(T3 生成,随仓库发布)
└── images/ # 图片
永远不推送远程的内容:working/、_task/、_materials/、CLAUDE.md。
T2 任务中会写入 .gitignore 固化这条规则;任何 git 操作前先确认 .gitignore 生效。
3. 硬性规则
- 中文写作。全站简体中文;术语与命令名保留英文原文(如 dofile、csdid)。
- 素材可直接使用(
_materials/blogs/推文,以及 ci-policy、stata101、ds2026 三个 仓库里的文字与图片,均为老师本人版权,无版权顾虑):- 文字:可直接采用,不必只做改写;觉得原文不够好时可自行改写、润色。
- 图片:直接复制原仓库 markdown 里的
图床链接使用,不必把图片 文件另存到本仓库(图床 URL 版权同属老师)。 - 链接(作用类似论文参考文献,目的是让读者深入了解):只截取段落性文字放入书稿时 不必标注原文链接;截取后读者若需了解更深内容可附原文链接;涉及基础设施配置、 软件安装等因 80 分钟课时不便展开的内容,应给出 ds2026 等仓库的完整链接, 让读者按链接了解完整过程。
- 不发明事实。课程时间、价格、大纲等信息只能来自
_materials/misc/中的文件; 拿不准就留<!-- TODO -->注释并在任务结束时汇报。 - 只读源仓库。对 ci-policy、stata101、ds2026 三个本地仓库只有读权限,绝不修改。
- 每个任务结束必须汇报:做了什么、产出在哪、遇到什么问题、哪些 TODO 待人工确认。 得到确认后才进入下一个任务。
demo/_dgp/存放数据生成代码。在 T4 演示分析时,扮演分析者的 agent 不得读取 该文件夹与working/(防止"偷看答案"),README 与任务提示词中已有约束。
4. 工具与环境
- 系统:Windows;在 VS Code 终端中运行。
- Quarto:用
quarto render编译全站;报错先修复再继续。 - Stata:批处理模式调用,形如
"C:\Program Files\Stata19\StataMP-64.exe" /e do 文件名.do。 Stata 安装路径不确定时,先在C:\Program Files\下搜索Stata*;找不到就停下来问人。 - 生成 PDF 用 Quarto 的 typst 引擎(免装 LaTeX),中文字体用 SimSun,详见 demo README。
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 73 lines · 1,255 tokens per session scan A e3d07422df3f
stata-ai CLAUDE.md is an instructions file published in the GitHub repository lianxhcn/stata-ai (23 stars, last pushed 1mo ago), licensed MIT. It adds 1,255 tokens to every session, about $0.0063 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.