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Check Understanding

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rohitg00
check-understanding

Phase quiz for AI Engineering from Scratch. Trigger with "quiz me", "test phase", "check my understanding", "do I know phase 3", or `/check-understanding <phase>`.

Overview

Publisherrohitg00
Repositoryai-engineering-from-scratch
Skill namecheck-understanding
Stars
54.9K
Forks
9.6K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by rohitg00 on GitHub. Read the source before you install it.

Installation

Install the Check Understanding AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/rohitg00/ai-engineering-from-scratch.git /tmp/ai-engineering-from-scratch
mkdir -p .claude/skills
cp -r /tmp/ai-engineering-from-scratch/skills/check-understanding .claude/skills/check-understanding
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Check Understanding in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Check Understanding on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Check Understanding is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Check Understanding

Test your knowledge of a completed phase from the AI Engineering from Scratch course.

Activation

This skill activates when the user says things like:

  • /check-understanding 3 or /check-understanding deep-learning
  • "quiz me on phase 2"
  • "test phase 1"
  • "check my understanding of transformers"
  • "do I know phase 3"
  • "am I ready for the next phase"

Input

Accepts a phase number (0-19) or a phase name as argument. If no argument is provided, ask the user which phase they want to be tested on by listing all 20 phases.

Phase Map

Map the argument to the correct phase directory under phases/:

InputDirectoryPhase Name
0, setup, tooling00-setup-and-toolingSetup & Tooling
1, math, math-foundations01-math-foundationsMath Foundations
2, ml, ml-fundamentals02-ml-fundamentalsML Fundamentals
3, deep-learning, dl03-deep-learning-coreDeep Learning Core
4, cv, computer-vision, vision04-computer-visionComputer Vision
5, nlp05-nlp-foundations-to-advancedNLP -- Foundations to Advanced
6, speech, audio06-speech-and-audioSpeech & Audio
7, transformers07-transformers-deep-diveTransformers Deep Dive
8, generative, gen-ai, genai08-generative-aiGenerative AI
9, rl, reinforcement-learning09-reinforcement-learningReinforcement Learning
10, llms, llm, llms-from-scratch10-llms-from-scratchLLMs from Scratch
11, llm-engineering, llm-eng11-llm-engineeringLLM Engineering
12, multimodal12-multimodal-aiMultimodal AI
13, tools, protocols, mcp13-tools-and-protocolsTools & Protocols
14, agents, agent-engineering14-agent-engineeringAgent Engineering
15, autonomous15-autonomous-systemsAutonomous Systems
16, multi-agent, swarms16-multi-agent-and-swarmsMulti-Agent & Swarms
17, infrastructure, production, infra17-infrastructure-and-productionInfrastructure & Production
18, ethics, safety, alignment18-ethics-safety-alignmentEthics, Safety & Alignment
19, capstone, projects19-capstone-projectsCapstone Projects

Procedure

Step 1: Resolve the Phase

Parse the argument. If it is a number, validate it is between 0 and 19 inclusive. If the number is out of range, tell the user: "Phase [N] does not exist. Valid phases are 0-19." and show the full list for them to pick from. If it is a name or keyword, look it up in the Phase Map above. If the keyword does not match any entry in the map, tell the user: "Unknown phase '[keyword]'. Pick from the list below:" and present all 20 phases. If no argument is provided, ask the user to pick from the full list.

Step 2: Read the Phase Content

If the repo is cloned (a phases/ directory exists in or above the current directory), find all lesson directories under phases/<phase-dir>/ and read each lesson's docs/en.md. If it is not cloned, get the phase's lesson list from the Contents section of the README (fetch https://raw.githubusercontent.com/rohitg00/ai-engineering-from-scratch/main/README.md), then fetch each lesson's docs/en.md from the same raw base URL. These documents contain the teaching material you will generate questions from.

Read as many lesson docs as needed to cover the full breadth of the phase. If a phase has many lessons (15+), prioritize reading a representative spread: first few, middle, and last few.

Step 3: Generate 8 Questions

Create exactly 8 multiple-choice questions drawn from the lesson content you just read:

Questions 1-4: Conceptual (What/Why) These test understanding of ideas, definitions, and reasoning. Examples:

  • "What is the purpose of X?"
  • "Why does Y happen when Z?"
  • "Which statement best describes the relationship between A and B?"
  • "What problem does X solve?"

Questions 5-8: Practical (How/Build) These test applied knowledge and implementation awareness. Examples:

  • "How would you implement X?"
  • "Which approach correctly solves Y?"
  • "What is the correct order of steps to build Z?"
  • "If you observe X during training, what should you do?"

Each question must have exactly 4 answer options labeled A, B, C, and D. Exactly one option is correct. The wrong options should be plausible but clearly incorrect to someone who studied the material.

Tag each question with the specific lesson it draws from (e.g., "Lesson 03: Matrix Transformations").

Step 4: Present Questions One at a Time

Use the AskUserQuestion tool (or equivalent interactive prompt) to present each question individually. Format:

text
Question 1/8 (Conceptual) -- from Lesson 03: Matrix Transformations

What is the geometric interpretation of an eigenvalue?

A) The angle of rotation applied by the matrix
B) The factor by which the eigenvector is scaled during transformation
C) The determinant of the transformation matrix
D) The rank of the matrix after transformation

Wait for the user's answer before moving to the next question.

Answer isolation

Keep the correct option and explanation private until the learner answers the current question. Never use a real answer letter, a likely answer, or the generated answer distribution in a reply-format hint. When a plain-text hint is needed, use exactly: Reply with one letter: <A|B|C|D>.

Step 5: Track and Score

Keep a running tally:

  • Total correct out of 8
  • For each wrong answer, record: the question number, the user's answer, the correct answer, and which lesson it came from

Step 6: Show Results

After all 8 questions, display the score and grade:

7-8 correct: Mastered If the phase is 19 (Capstone Projects): "You have mastered Phase 19, the final phase." Add "Congratulations, you have completed the entire curriculum." only when you can verify the rest of the curriculum is done (a LEARNING.md in the current directory whose Path table shows Phases 0-18 as Done or Skip); a single phase quiz does not prove full completion. Otherwise: "You have a strong grasp of Phase N. You are ready to move on to Phase N+1: [next phase name]."

5-6 correct: Almost "Solid foundation. Review these specific areas before moving on:" Then list the lessons tied to the missed questions.

3-4 correct: Developing "You are building understanding but need to revisit some lessons:" Then list each missed question with the lesson to re-read.

0-2 correct: Start Over "This phase needs more time. Work through the lessons again from the beginning, focusing on:" Then list all missed topics.

Step 7: Wrong Answer Breakdown

For every question the user got wrong, show:

text
Question N: [question text, abbreviated]
Your answer: B
Correct answer: C -- [the correct option text]
Why: [1-2 sentence explanation of why C is correct]
Review: Lesson NN -- [lesson name] (phases/<phase-dir>/NN-<lesson-slug>/docs/en.md)

Step 8: What Next?

End by offering three choices:

  1. Retake this quiz -- generate a fresh set of 8 questions from the same phase
  2. Try another phase -- pick a different phase to test
  3. Explain a topic -- ask about any concept from the questions you missed

Wait for the user's choice and act accordingly.

Rules

  • Avoid repeating questions on retakes until the question pool is exhausted. Once exhausted, reshuffle or rephrase questions for subsequent retakes.
  • Questions must be directly grounded in the lesson docs, not general knowledge.
  • Do not show the correct answer until after the user responds.
  • Do not include literal answer letters in examples of how the learner should reply; use <A|B|C|D> as the placeholder.
  • Keep question text concise. One or two sentences max.
  • Wrong options must be plausible. No joke answers.
  • If a phase has no lesson docs written yet (no en.md files found), tell the user: "Phase N does not have lesson content yet. Pick a completed phase to quiz on."

Frequently asked questions

What does the Check Understanding AI skill do?

Phase quiz for AI Engineering from Scratch. Trigger with "quiz me", "test phase", "check my understanding", "do I know phase 3", or `/check-understanding <phase>`.

Why use Check Understanding on TypingMind?

Because you install it once and use it with any model. Check Understanding is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Check Understanding in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rohitg00/ai-engineering-from-scratch/tree/main/skills/check-understanding. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Check Understanding?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Check Understanding?

As many as you like. As long as a model supports skills, you can use Check Understanding with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Check Understanding AI skill free?

Yes. It is published on GitHub by rohitg00 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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