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ai-engineering-from-scratch Skill

von rohitg00★ 78.4147 Skills

Installieren

7 Skills (Anweisungssammlungen) von rohitg00, die eine KI liest und befolgt · kein MCP-Server

Beschreibung des Anbieters (englisches Original)

Learn AI Engineering! Learn it. Build it. Ship it for others.

Was einen Skill von MCP unterscheidet

MCP verbindet eine KI mit einem externen Dienst oder Daten. Ein Skill ist eine Arbeitsanleitung, die die KI liest und befolgt; er verbindet sich mit nichts.

Funktioniert mit

Claude CodeCodexCursor

Laut README des Anbieters und den Ordnern im Repo

Installieren

Ein Skill sind Anweisungen, denen die KI folgt. Lies die Dateien vor der Installation und installiere nur von vertrauenswürdigen Anbietern.

Vom Anbieter empfohlen

npx skills add rohitg00/ai-engineering-from-scratch

Aus dem README des Anbieters; lädt den Code des Anbieters herunter und führt ihn aus

Welche App nutzt du?

  1. Terminal öffnen

    Mac: Command+Leertaste und Terminal tippen · Windows: PowerShell öffnen (der Befehl unten ist für Mac/Linux)

  2. Skill-Ordner nach ~/.claude/skills kopieren

    Lädt das Repo in einen temporären Ordner und kopiert nur Ordner mit einer SKILL.md

    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
  3. Claude Code neu starten, dann /learn tippen oder eine passende Aufgabe stellen; Claude nutzt den Skill

  1. Terminal öffnen

    Mac: Command+Leertaste und Terminal tippen · Windows: PowerShell öffnen (der Befehl unten ist für Mac/Linux)

  2. Skill-Ordner nach ~/.agents/skills kopieren

    Lädt das Repo in einen temporären Ordner und kopiert nur Ordner mit einer SKILL.md

    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
  3. Codex neu starten und eine passende Aufgabe stellen; Codex listet den Skill

  1. Terminal öffnen

    Mac: Command+Leertaste und Terminal tippen · Windows: PowerShell öffnen (der Befehl unten ist für Mac/Linux)

  2. Skill-Ordner nach ~/.cursor/skills kopieren

    Lädt das Repo in einen temporären Ordner und kopiert nur Ordner mit einer SKILL.md

    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
  3. Im Agent-Chat von Cursor / tippen und learn wählen

Andere Apps mit Agent Skills (etwa Gemini CLI oder GitHub Copilot) nutzen andere Ordner. Sieh in deren Anleitung nach und kopiere den Ordner mit der SKILL.md dorthin.

Auf GitHub ansehen ↗

Skill-Ordner am 11. Nov. 2026 mit den offiziellen Anleitungen von Claude Code, Codex und Cursor geprüft

SKILL.md vor der Installation lesen

Der folgende Text stammt aus dem Repo des Anbieters, nicht von PopNx MCP

---
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

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Von GitHub

GitHub-Sterne
78.414
Anbieter
rohitg00
Letzte Codeänderung
11. Nov. 2026
SKILL.md-Dateien im Repo
13
Themen
agents, ai, ai-agents, ai-engineering, computer-vision, course, deep-learning, dsh, from-scratch, generative-ai, llm, machine-learning