check-understanding — Claude Code skill: what it does, how to install
Runs an eight-question quiz on topics from the AI Engineering from Scratch curriculum. Tests your conceptual and practical grasp before moving to the next phase.
npx skills add rohitg00/ai-engineering-from-scratch --skill check-understanding -a claude-codeWhat check-understanding does
The skill accepts a phase index from 0 to 19 or a topic keyword, mapping it across 20 curriculum modules. If the repository is not present on disk, it fetches lesson files directly from GitHub.
Each quiz delivers 8 multiple-choice questions labeled A through D. Four questions test theoretical concepts, while the remaining four evaluate implementation knowledge. Questions appear one at a time. The skill keeps answers hidden until you respond.
At the end, it grades your score from Mastered down to Start Over. For incorrect answers, the skill pinpoints the exact lesson documents to revisit.
What it helps with
- test knowledge before advancing to the next curriculum phase
- pinpoint failed topics to specific lesson documentation
- take engineering quizzes without keeping a local repository clone
Example prompts for the agent
- /check-understanding 3
- quiz me on phase 2
- /check-understanding deep-learning
How to install check-understanding
1Skills CLI (Vercel)
npx skills add rohitg00/ai-engineering-from-scratch --skill check-understanding -a claude-code2Manually: put the files in place
~/.claude/skills/check-understanding/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/check-understanding/
1Skills CLI (Vercel)
npx skills add rohitg00/ai-engineering-from-scratch --skill check-understanding -a codex2Manually: put the files in place
.agents/skills/check-understanding/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add rohitg00/ai-engineering-from-scratch --skill check-understanding -a cursor2Manually: put the files in place
.cursor/skills/check-understanding/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install rohitg00/ai-engineering-from-scratch check-understanding2Manually: put the files in place
.github/skills/check-understanding/SKILL.md1Skills CLI (Vercel)
npx skills add rohitg00/ai-engineering-from-scratch --skill check-understanding -a gemini-cli2Platform CLI
gemini skills install https://github.com/rohitg00/ai-engineering-from-scratch --path skills/check-understandingManually: put the files in place
.devin/skills/check-understanding/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add rohitg00/ai-engineering-from-scratch --skill check-understanding -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about check-understanding
How do I install check-understanding in Claude Code?
Run npx skills add rohitg00/ai-engineering-from-scratch --skill check-understanding -a claude-code in your terminal.
What does check-understanding do?
It builds an 8-question multiple-choice quiz covering a selected phase of the AI Engineering course.
Does check-understanding require a local copy of the repository?
No. When a local phases/ directory is absent, it retrieves the necessary lesson markdown files over GitHub.
Source text
SKILL.md · MIT
--- name: check-understanding version: 1.0.0 description: 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>`. --- # 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/`: | Input | Directory | Phase Name | |-------|-----------|------------| | 0, setup, tooling | `00-setup-and-tooling` | Setup & Tooling | | 1, math, math-foundations | `01-math-foundations` | Math Foundations | | 2, ml, ml-fundamentals | `02-ml-fundamentals` | ML Fundamentals | | 3, deep-learning, dl | `03-deep-learning-core` | Deep Learning Core | | 4, cv, computer-vision, vision | `04-computer-vision` | Computer Vision | | 5, nlp | `05-nlp-foundations-to-advanced` | NLP -- Foundations to Advanced | | 6, speech, audio | `06-speech-and-audio` | Speech & Audio | | 7, transformers | `07-transformers-deep-dive` | Transformers Deep Dive | | 8, generative, gen-ai, genai | `08-generative-ai` | Generative AI | | 9, rl, reinforcement-learning | `09-reinforcement-learning` | Reinforcement Learning | | 10, llms, llm, llms-from-scratch | `10-llms-from-scratch` | LLMs from Scratch | | 11, llm-engineering, llm-eng | `11-llm-engineering` | LLM Engineering | | 12, multimodal | `12-multimodal-ai` | Multimodal AI | | 13, tools, protocols, mcp | `13-tools-and-protocols` | Tools & Protocols | | 14, agents, agent-engineering | `14-agent-engineering` | Agent Engineering | | 15, autonomous | `15-autonomous-systems` | Autonomous Systems | | 16, multi-agent, swarms | `16-multi-agent-and-swarms` | Multi-Agent & Swarms | | 17, infrastructure, production, infra | `17-infrastructure-and-production` | Infrastructure & Production | | 18, ethics, safety, alignment | `18-ethics-safety-alignment` | Ethics, Safety & Alignment | | 19, capstone, projects | `19-capstone-projects` | Capstone 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."
© rohitg00 · MIT · rohitg00/ai-engineering-from-scratch