ai-engineering-from-scratch-zh is a Chinese-language adaptation of a course that teaches AI engineering by implementing algorithms, tools, and agents from the ground up. It is for learners following a 20-stage path across mathematics, machine learning, agent systems, and production topics, with lessons using Python, TypeScript, Rust, and Julia. The catalogue entries provide agent skills and instructions associated with the course.
Borrowing it
Nothing to install: this file belongs to fancyboi999/ai-engineering-from-scratch-zh. 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/fancyboi999/ai-engineering-from-scratch-zh/main/AGENTS.mdgit clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zhWrote 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/fancyboi999/ai-engineering-from-scratch-zh/agents-md)<a href="https://agentmods.dev/instructions/fancyboi999/ai-engineering-from-scratch-zh/agents-md"><img src="https://agentmods.dev/badge/instructions/fancyboi999/ai-engineering-from-scratch-zh/agents-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/fancyboi999/ai-engineering-from-scratch-zh/agents-md"><img src="https://agentmods.dev/badge/instructions/fancyboi999/ai-engineering-from-scratch-zh/agents-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 | $0.01862 | $0.01862 |
| Opus 5 | $0.00931 | $0.00931 |
| Sonnet 5 | $0.00372 | $0.00372 |
| Haiku 4.5 | $0.00186 | $0.00186 |
Grade A, and why
ai-engineering-from-scratch-zh AGENTS.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 5d 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
本文档是贡献者和 AI agent 修改本仓库时的操作手册。开 PR 前必须阅读。
这是一套课程，不是 SaaS 应用。课程内容就是产品。中文翻译以 TRANSLATION.md 为唯一权威契约。
定位
核心课程包含 20 个阶段、503 节课。每个算法都先从原始数学构建，再使用生产框架完成同一操作。 你会亲手写出反向传播、分词器、注意力机制和 agent 循环，所以当 PyTorch 或其他库登场时，它们不再是黑盒。
certifications/claude/ 是独立的 Claude 认证备考层，包含 4 条路线、33 节认证课、诊断和原创模拟题。
它不计入 503 节核心课程，也不进入 EPUB/PDF 图书流程。
仓库结构
phases/
NN-phase-slug/
NN-lesson-slug/
docs/zh.md # 中文课程正文
code/ # 实现与测试
quiz.json # 6 道题
outputs/ # 可复用产物
certifications/claude/
program.json # 项目声明、核验日期、官方链接
tracks/*.json # 考试蓝图、路线和学习计划
lessons/NN-slug/ # 认证课程
assessments/<exam-code>/ # 诊断和完整模拟题
glossary/terms.md # 术语表唯一数据源
site/ # 纯静态站点
scripts/ # 审计和构建工具
.github/workflows/build.yml # 中文站 CI
强制规则
- 新增课程时，每个 lesson 目录用一个原子提交。上游同步或批量翻译可按可审查的逻辑批次提交。
- 提交标题使用约定式前缀且不超过 72 字符；本中文镜像优先使用
sync(zh):、i18n(quiz):、feat(site):、fix(site):。 - 图表只使用 Mermaid、SVG 或站点注册的
figure机制，不用 ASCII/绘图字符假装图表。 - 所有代码围栏必须带语言标记。
- 不使用外部 LLM API 做翻译；不提交考题泄露内容、机密题目或包过承诺。
- 代码保持 stdlib-first，不为满足形式而伪造 provider API 集成。
- 不直接 push
main；所有更改走 PR。 - 不提交构建产物
site/sitemap.xml、site/llms.txt、site/build-meta.js、site/certification-data.js、site/lessons/。 site/data.js是中文仓跟踪的构建产物；课程、术语或站点数据变动后必须重建并与源文件一起提交。
依赖约束
| 语言 | 允许的依赖 |
|---|---|
| Python | numpy、torch、h5py、zstandard、safetensors、标准库 |
| TypeScript | hono、zod、ws（只在需要 WebSocket 时）、@hono/node-server、Node 20+ 标准库 |
| Rust | 标准库，单文件 rustc --edition 2021 |
| Julia | Random、Statistics、LinearAlgebra、Printf |
课程契约
docs/zh.md
# <标题>
> <一句话摘要>
**类型：** <Learn | Build | Reference>
**语言：** <与 code/main.* 匹配的语言>
**前置要求：** <课程链接或“无”>
**预计时间：** <分钟>
## 学习目标
- <4–6 条以动词开头的目标>
**语言：** 必须与 code/ 中的 main.* 一致。中文正文完成后删除 docs/zh.md。
quiz.json
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.
- 5d ago Changed · +1 tokens per session 47ddfbcc14db
- 9d ago First seen · 145 lines · 1,861 tokens per session scan A e0596c431dc5
ai-engineering-from-scratch-zh AGENTS.md is an instructions file published in the GitHub repository fancyboi999/ai-engineering-from-scratch-zh (1,042 stars, last pushed today), licensed MIT. It adds 1,862 tokens to every session, about $0.0093 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).
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.
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.