AI Engineering from Scratch is a free, open-source curriculum that teaches people to build AI systems through lessons and reusable artifacts such as prompts, skills, agents, and MCP servers. It is for learners who want practical foundations or want to create AI applications, and the catalogue skills support parts of that curriculum.
Borrowing it
Nothing to install: this file belongs to rohitg00/ai-engineering-from-scratch. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/rohitg00/ai-engineering-from-scratch/main/.claude/skills/check-understanding/SKILL.mdgit clone --depth 1 https://github.com/rohitg00/ai-engineering-from-scratchWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/rohitg00/ai-engineering-from-scratch/check-understanding)<a href="https://agentmods.dev/skills/rohitg00/ai-engineering-from-scratch/check-understanding"><img src="https://agentmods.dev/badge/skills/rohitg00/ai-engineering-from-scratch/check-understanding/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/rohitg00/ai-engineering-from-scratch/check-understanding"><img src="https://agentmods.dev/badge/skills/rohitg00/ai-engineering-from-scratch/check-understanding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.02023 |
| Opus 5 | $0.00022 | $0.01012 |
| Sonnet 5 | $0.00009 | $0.00405 |
| Haiku 4.5 | $0.00004 | $0.00202 |
Grade A, and why
check-understanding scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 3or/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 |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 168 lines · 44 tokens per session scan A c6e2e985794e
check-understanding is a skill published in the GitHub repository rohitg00/ai-engineering-from-scratch (52,899 stars, last pushed yesterday), licensed MIT. It adds 44 tokens to every session and 2,023 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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