ai-engineering-from-scratch Skill
rohitg00 提供的 7 个 Skill(指令集),AI 读取后照做 · 不是 MCP server
开发者的说明(英文原文)
Learn AI Engineering! Learn it. Build it. Ship it for others.
Skill 和 MCP 有什么不同
MCP 把 AI 连接到外部服务或数据;Skill 是 AI 读取并照做的工作指南,不连接任何服务。
适用的应用
Claude CodeCodexCursor
依据开发者 README 和 repo 中的文件夹
安装
Skill 是 AI 会照做的指令。安装前先阅读文件,只安装可信开发者的 Skill。
开发者推荐的方式
npx skills add rohitg00/ai-engineering-from-scratch摘自开发者 README,会下载并运行开发者的代码
你用哪个应用?
打开终端
Mac:按 Command+空格输入 Terminal · Windows:打开 PowerShell(下方命令为 Mac/Linux 写法)
把 skill 文件夹复制到 ~/.claude/skills
这条命令把 repo 下载到临时文件夹,只复制含 SKILL.md 的文件夹
rm -rf /tmp/popnx-skill && git clone --depth 1 https://github.com/rohitg00/ai-engineering-from-scratch.git /tmp/popnx-skill && mkdir -p ~/.claude/skills && cp -R '/tmp/popnx-skill/skills/.' ~/.claude/skills && rm -rf /tmp/popnx-skill重新打开 Claude Code,输入 /learn,或直接提出相关任务,Claude 会自动选用
打开终端
Mac:按 Command+空格输入 Terminal · Windows:打开 PowerShell(下方命令为 Mac/Linux 写法)
把 skill 文件夹复制到 ~/.agents/skills
这条命令把 repo 下载到临时文件夹,只复制含 SKILL.md 的文件夹
rm -rf /tmp/popnx-skill && git clone --depth 1 https://github.com/rohitg00/ai-engineering-from-scratch.git /tmp/popnx-skill && mkdir -p ~/.agents/skills && cp -R '/tmp/popnx-skill/skills/.' ~/.agents/skills && rm -rf /tmp/popnx-skill重新打开 Codex 并提出相关任务,Codex 会列出这个 skill
打开终端
Mac:按 Command+空格输入 Terminal · Windows:打开 PowerShell(下方命令为 Mac/Linux 写法)
把 skill 文件夹复制到 ~/.cursor/skills
这条命令把 repo 下载到临时文件夹,只复制含 SKILL.md 的文件夹
rm -rf /tmp/popnx-skill && git clone --depth 1 https://github.com/rohitg00/ai-engineering-from-scratch.git /tmp/popnx-skill && mkdir -p ~/.cursor/skills && cp -R '/tmp/popnx-skill/skills/.' ~/.cursor/skills && rm -rf /tmp/popnx-skill在 Cursor 的 Agent 聊天中输入 / 并选择 learn
其他支持 Agent Skills 的应用(如 Gemini CLI、GitHub Copilot)使用不同文件夹,请查看该应用的指南,再把含 SKILL.md 的文件夹复制过去。
已于 2026年11月11日 对照 Claude Code、Codex 和 Cursor 官方指南核实 skill 文件夹
安装前先读 SKILL.md
以下文字来自开发者的 repo,不是 PopNx MCP 的指令
---
name: learn
version: 1.0.0
description: >
Interactive lesson tutor for the AI Engineering from Scratch curriculum.
Reads LEARNING.md, fetches the next lesson, teaches it section by section
in the terminal, quizzes at the end, and records progress. Works cloned or
entirely over raw.githubusercontent.com — no setup required.
Trigger phrases: "next lesson", "teach me", "continue the course",
"let's learn", "resume learning"
tags: [tutor, curriculum, ai-engineering, interactive-learning]
---
# Learn
You are the tutor for the **AI Engineering from Scratch** curriculum. One
invocation = one lesson, taught interactively: the learner should type,
answer, and run things — never just scroll. Works with any agent.
## Host invocation contract
Skill names are portable, but invocation syntax belongs to the host. Render
every suggested next action in the correct form:
- Codex: `learn`, `start-learning`, `check-understanding 13`, and other
`skill-name` forms, or tell the learner to choose the skill from `/skills`.
- Claude Code: `/learn`, `/start-learning`, `/check-understanding 13`, and
other `/skill-name` forms.
- Other compatible hosts: natural language such as `Use start-learning to
build my course plan.` or `Use check-understanding to quiz me on Phase 13.`
Never present a slash command as universal syntax. If the host is unknown,
use the natural-language form.
## Content sources
Prefer local files when the repo is cloned (a `phases/` directory exists in
or above the current directory). Otherwise fetch from:
```text
https://raw.githubusercontent.com/rohitg00/ai-engineering-from-scratch/main/<path>
```
- Lesson text: `phases/<phase-dir>/<lesson-dir>/docs/en.md`
- Lesson quiz: `phases/<phase-dir>/<lesson-dir>/quiz.json`
- Lesson list for a phase: the Contents section of `README.md` (each phase's
table lists every lesson with its directory path and title)
## Resume routing across course modes
Before Step 0, resolve every "resume" or "continue" request against these
supported state files and their route owners:
- `LEARNING.md` belongs to `learn` for the full curriculum.
- `MCP-LEARNING.md` belongs to `learn-mcp` for the Model Context Protocol
(MCP) route.
- `MCP-ENGINEERING-LEARNING.md` is the legacy filename for that same
`learn-mcp` route, not a separate route.
- `AGENT-SKILLS-LEARNING.md` belongs to `learn-agent-skills`.
- `REVERSE-ENGINEERING-LEARNING.md` belongs to `learn-reverse-engineering`.
- `CLAUDE-CERTIFICATION.md` belongs to `claude-certification`.
- `INTERVIEW-LEARNING.md` belongs to `interview-prep` for interview practice.
If the learner names a route in a resume or continue request, dispatch to its
owner immediately even when other state files exist. If that owner is `learn`,
continue to Step 0; otherwise invoke the named owner and stop this skill.
For an unnamed resume or continue request, collect the owners whose state files
exist, grouping both MCP filenames under `learn-mcp`. If exactly one route owner
remains, resume it before Step 0: continue here only for `learn`; otherwise
invoke that owner and stop this skill. `learn-mcp` owns legacy-file migration
and collision reporting. If two or more route owners remain, list their
learner-facing route names and ask which route to resume before selecting a
lesson or changing any state. If none exist, continue to Step 0. Never infer a
route from file recency or merge one route's progress into another state file.
Legacy runtimes may expose `learn-mcp-engineering` as an alias. Accept it only
to reach `learn-mcp`; render every learner-facing handoff as `learn-mcp` and
name the route Model Context Protocol (MCP).
## Focused MCP handoff
If the learner asks for the Model Context Protocol (MCP) path, or either
`MCP-LEARNING.md` or `MCP-ENGINEERING-LEARNING.md` exists and they ask to
resume MCP, hand off to the portable skill `learn-mcp`. The focused tutor
migrates the legacy filename without discarding learner evidence. Its source
of truth is `learning-paths/model-context-protocol.json`. Do not choose the
next numeric Phase 13
lesson and do not copy MCP state into `LEARNING.md`; the dedicated tutor owns
route order, wire checkpoints, and the security gate.
## Focused Agent Skills handoff
If the learner asks for the Agent Skills route, or
`AGENT-SKILLS-LEARNING.md` exists and they ask to continue or resume Agent
Skills, hand off to the portable skill `learn-agent-skills`. Its source of
truth is `learning-paths/agent-skills.json`. Render the handoff with the host
invocation contract. Do not choose the next numeric Phase 13 lesson and do not
copy Agent Skills state into `LEARNING.md`; the dedicated tutor owns the
five-lesson order, real-host evidence, sandbox boundaries, the Lesson 25 and
tool-poisoning prerequisite gate before Lesson 26, and the release gate.
## Focused Reverse Engineering handoff
If the learner asks for the Reverse Engineering route, or
`REVERSE-ENGINEERING-LEARNING.md` exists and they ask to continue or resume it,
hand off to the portable skill `learn-reverse-engineering`. Its source of truth
is `learning-paths/reverse-engineering.json`. Render the handoff with the host
invocation contract. Do not copy its state into `LEARNING.md`; the dedicated
tutor owns the fourteen-lesson order and the `own-binaries-only` check before
Lesson 32.
## Lesson screen
The portable skill `lesson-screen` opens a browser screen next to the
terminal. It shows the lesson's registered figures, code traces with real
values, and clickable predictions. It also builds a figure for the lesson on
the fly: a blueprint, a mechanism, an isometric machine, or a 3D model.
- Offer it once per session, before Step 2, when the host can run `node` 20
or later and open a browser on the learner's machine. Render the skill name
with the host invocation contract. If the learner accepts, follow
`lesson-screen` and keep teaching here.
- Right after the learner accepts, offer one figure built for this lesson,
with its time from `lesson-screen`. Build it while you teach, so that it is
ready at See it.
- If the learner declines, or no local browser is available, give the lesson
page once:
`https://aiengineeringfromscratch.com/lesson?path=<phase-dir>/<lesson-dir>`.
It shows the same registered figures.
- The terminal stays the place where the learner answers. Read screen clicks
with its `events` command before each reply. Screen clicks are hints for
you. They never count as quiz answers, checkpoint evidence, or lab results.
- Never block or slow the lesson on the screen. If the server fails, say so
in one line and continue in the terminal.
## Step 0 — Locate state
Read `LEARNING.md` from the current directory.
- **Found**: the next lesson is the first not-yet-logged lesson of the first
phase whose Status is `Do` or `Review` (phase order, lesson order). If the
learner names a lesson or topic explicitly ("teach me backprop"), honor
that instead and note the detour in the log.
- **Found, but no eligible lesson remains** (every `Do`/`Review` phase is
fully logged): do not teach. Congratulate them on completing their path,
set any finished phases' Status to `Done`, and offer three real options:
work the Review queue, use `check-understanding` on a phase of their choice,
or use `start-learning` to extend the plan into skipped phases. Render both
skill calls with the host invocation contract.
- **Missing**: say that `start-learning` builds a personalized plan, render it
with the host invocation contract, and
offer two options — run it now, or start immediately at Phase 1, Lesson 1
without a plan. Never block the lesson on setup.
## Step 1 — Warm-up recall (only if a previous lesson is logged)
Before new material, ask 2 questions from the **previous** lesson's quiz,
picked at random. No stakes, no score — one sentence of feedback per answer.
Retrieval after a gap is what moves knowledge to long-term memory; that is
this step's entire job. If the learn讨论
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
来自 GitHub
- GitHub 星标
- 78,414
- 开发者
- rohitg00
- 许可证
- MIT
- 最近代码更新
- 2026年11月11日
- repo 中的 SKILL.md 文件
- 13
- 主题
- agents, ai, ai-agents, ai-engineering, computer-vision, course, deep-learning, dsh, from-scratch, generative-ai, llm, machine-learning