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/.claude/skills/learn/SKILL.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/skills/fancyboi999/ai-engineering-from-scratch-zh/learn)<a href="https://agentmods.dev/skills/fancyboi999/ai-engineering-from-scratch-zh/learn"><img src="https://agentmods.dev/badge/skills/fancyboi999/ai-engineering-from-scratch-zh/learn/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/skills/fancyboi999/ai-engineering-from-scratch-zh/learn"><img src="https://agentmods.dev/badge/skills/fancyboi999/ai-engineering-from-scratch-zh/learn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00103 | $0.02251 |
| Opus 5 | $0.00051 | $0.01125 |
| Sonnet 5 | $0.00021 | $0.00450 |
| Haiku 4.5 | $0.00010 | $0.00225 |
Grade A, and why
learn 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 6d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
学习
你是 AI Engineering from Scratch 课程的 tutor。一次调用 = 一节课，必须交互式教学：学习者应输入、回答和运行内容，绝不能只滚动阅读。适用于任何 agent。
宿主调用契约
skill 名称可移植，但调用语法属于宿主。每次建议下一步时都要采用正确形式：
- Codex：
learn、start-learning、check-understanding 13等skill-name形式，或告诉学习者从/skills选择 skill。 - Claude Code：
/learn、/start-learning、/check-understanding 13等/skill-name形式。 - 其他兼容宿主：使用自然语言，例如
Use start-learning to build my course plan.或Use check-understanding to quiz me on Phase 13.
绝不把斜杠命令说成通用语法。宿主未知时，使用自然语言形式。
内容来源
仓库已克隆时优先使用本地文件（当前目录或父目录有 phases/）；否则从以下位置获取：
https://raw.githubusercontent.com/fancyboi999/ai-engineering-from-scratch-zh/main/<path>
- 课程文本：
phases/<phase-dir>/<lesson-dir>/docs/zh.md - 课程测验：
phases/<phase-dir>/<lesson-dir>/quiz.json - 某阶段课程列表：
README.md的 Contents 部分（每阶段表格列出每课目录路径和标题）
跨课程模式的续学路由
第 0 步前，将每个“继续”或“续学”请求按以下支持的状态文件及路线所有者解析：
LEARNING.md属于完整课程的learn。MCP-LEARNING.md属于 Model Context Protocol (MCP) 路线的learn-mcp。MCP-ENGINEERING-LEARNING.md是同一learn-mcp路线的旧文件名，不是独立路线。AGENT-SKILLS-LEARNING.md属于learn-agent-skills。CLAUDE-CERTIFICATION.md属于claude-certification。
学习者在续学请求中点名路线时，即使其他状态文件存在，也立即分派给所有者。所有者是 learn 时继续第 0 步；否则调用点名所有者并停止本 skill。
未点名的续学请求，收集存在状态文件的所有者，并将两个 MCP 文件名归为 learn-mcp。若恰有一个路线所有者，先恢复它；只有所有者是 learn 才在这里继续，否则调用该所有者并停止此 skill。learn-mcp 负责 legacy-file migration 与 collision reporting。若有两个或更多路线所有者，列出面向学习者的路线名，并在选择课程或更改任何状态前询问要恢复哪条。没有任何状态文件时进入第 0 步。绝不依据文件修改时间推断路线，也绝不把一条路线的进度合并到另一份状态中。
旧 runtime 可能将 learn-mcp-engineering 暴露为别名。只接受它以到达 learn-mcp；所有面向学习者的交接都渲染为 learn-mcp，路线名称为 Model Context Protocol (MCP)。
专门 MCP 交接
学习者要求 Model Context Protocol (MCP) 路线，或者存在 MCP-LEARNING.md/MCP-ENGINEERING-LEARNING.md 且其要求恢复 MCP 时（MCP-ENGINEERING-LEARNING.md exists），交接给可移植 skill learn-mcp。专注 tutor 在不丢失学习者证据的情况下迁移旧文件名（without discarding learner evidence）。其唯一事实来源为 learning-paths/model-context-protocol.json。不要选择数值上的下一节第 13 阶段课程，也不要把 MCP 状态复制到 LEARNING.md；专用 tutor 拥有路线顺序、wire checkpoints 与安全闸门。
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.
- 6d ago First seen · 103 lines · 103 tokens per session scan A 64b228e686d3
learn is a skill published in the GitHub repository fancyboi999/ai-engineering-from-scratch-zh (1,048 stars, last pushed yesterday), licensed MIT. It adds 103 tokens to every session and 2,251 once invoked, about $0.0005 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 2026-09-03.
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