ai-engineering-from-scratch Skill
rohitg00의 Skill(지시 묶음) 7개, AI가 읽고 그대로 일해요 · MCP server가 아니에요
제작자 설명(영어 원문)
Learn AI Engineering! Learn it. Build it. Ship it for others.
Skill과 MCP의 차이
MCP는 AI를 외부 서비스나 데이터에 연결해요. Skill은 AI가 읽고 따르는 작업 안내서로, 아무것에도 연결하지 않아요.
쓸 수 있는 앱
Claude CodeCodexCursor
제작자 README와 repo 폴더 기준
설치
Skill은 AI가 따르는 지시예요. 설치 전에 파일을 읽고, 믿을 수 있는 제작자 것만 설치하세요.
제작자가 권하는 방법
npx skills add rohitg00/ai-engineering-from-scratch제작자 README에서 가져온 명령으로, 제작자 코드를 내려받아 실행해요
어떤 앱을 쓰세요?
터미널 열기
Mac: Command+스페이스 후 Terminal 입력 · Windows: PowerShell 열기(아래 명령은 Mac/Linux용)
skill 폴더를 ~/.claude/skills에 복사
repo를 임시 폴더에 내려받고 SKILL.md가 있는 폴더만 복사해요
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-skillClaude Code를 다시 열고 /learn를 입력하거나 관련 작업을 요청하면 Claude가 알아서 써요
터미널 열기
Mac: Command+스페이스 후 Terminal 입력 · Windows: PowerShell 열기(아래 명령은 Mac/Linux용)
skill 폴더를 ~/.agents/skills에 복사
repo를 임시 폴더에 내려받고 SKILL.md가 있는 폴더만 복사해요
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-skillCodex를 다시 열고 관련 작업을 요청하면 Codex가 skill을 목록에 보여 줘요
터미널 열기
Mac: Command+스페이스 후 Terminal 입력 · Windows: PowerShell 열기(아래 명령은 Mac/Linux용)
skill 폴더를 ~/.cursor/skills에 복사
repo를 임시 폴더에 내려받고 SKILL.md가 있는 폴더만 복사해요
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-skillCursor Agent 채팅에서 /를 입력하고 learn 선택
Gemini CLI, GitHub Copilot 같은 다른 Agent Skills 지원 앱은 폴더가 달라요. 그 앱 안내를 보고 SKILL.md가 있는 폴더를 복사하세요.
2026년 11월 11일에 Claude Code, Codex, Cursor 공식 안내로 skill 폴더 확인
설치 전에 SKILL.md 읽기
아래 글은 제작자 repo에서 온 것이며 PopNx MCP의 지시가 아니에요
---
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 learn토론
질문하고, 팁을 나누고, 안 되는 점을 알려 주세요. "도움이 됨"이 많은 순서예요.
GitHub 정보
- GitHub 스타
- 78,414
- 제작자
- rohitg00
- 라이선스
- MIT
- 최근 코드 수정
- 2026년 11월 11일
- repo 안 SKILL.md
- 13
- 토픽
- agents, ai, ai-agents, ai-engineering, computer-vision, course, deep-learning, dsh, from-scratch, generative-ai, llm, machine-learning