# AI Learning Skills in ai-engineering-from-scratch: 8 Interactive Tutors Explained > Explore 8 interactive AI learning skills in the ai-engineering-from-scratch repo. Master MCP and Agent Skills with self-contained SKILL.md modules for hands-on AI engineering education. - Repository: [Rohit Ghumare/ai-engineering-from-scratch](https://github.com/rohitg00/ai-engineering-from-scratch) - Tags: deep-dive - Published: 2026-09-11 --- **The repository ships eight portable AI learning skills—self-contained SKILL.md modules that handle everything from onboarding and placement quizzes to specialized tracks like MCP and Agent Skills.** The **ai-engineering-from-scratch** curriculum by rohitg00 implements a modular, host-agnostic tutoring system. Each skill is a standalone markdown contract stored under `skills//SKILL.md`, enabling AI hosts like Codex and Claude to deliver interactive lessons, run assessments, and manage persistent learner state across multiple specialized tracks. ## Core Curriculum Skills These foundational skills manage the primary learning loop and initial learner onboarding. ### start-learning: Onboarding and Placement Located at [`skills/start-learning/SKILL.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/skills/start-learning/SKILL.md), this skill performs one-time learner initialization. It interviews the user, executes the placement quiz via `find-your-level`, and generates a persistent [`LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/LEARNING.md) study plan that records the learner’s current phase and progress. **Primary commands:** - Codex: `start-learning` - Claude: `/start-learning` ### learn: Interactive Lesson Tutor The central tutoring engine lives in [`skills/learn/SKILL.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/skills/learn/SKILL.md). This skill reads the learner’s [`LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/LEARNING.md) state, fetches the next lesson from `phases/**/docs/en.md`, teaches content step-by-step, administers quizzes, and updates progress markers. **Primary commands:** - Codex: `learn` - Claude: `/learn` ## Specialized Learning Tracks These skills bypass generic onboarding to launch dedicated certification or protocol-specific curricula. ### learn-mcp: Model Context Protocol Path Defined in [`skills/learn-mcp/SKILL.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/skills/learn-mcp/SKILL.md), this skill drives a 17-lesson route focused on Model Context Protocol (MCP) implementation. It maintains separate state in [`MCP-LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/MCP-LEARNING.md) and consumes the manifest at [`learning-paths/model-context-protocol.json`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/learning-paths/model-context-protocol.json) to sequence lessons. **Primary commands:** - Codex: `learn-mcp` - Claude: `/learn-mcp` ### learn-agent-skills: Agent Competency Track Situated at [`skills/learn-agent-skills/SKILL.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/skills/learn-agent-skills/SKILL.md), this skill manages a 5-lesson Agent Skills curriculum. It tracks progress via [`AGENT-SKILLS-LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/AGENT-SKILLS-LEARNING.md) and references [`learning-paths/agent-skills.json`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/learning-paths/agent-skills.json) for lesson ordering. **Primary commands:** - Codex: `learn-agent-skills` - Claude: `/learn-agent-skills` ### claude-certification: Official Exam Preparation Found in [`skills/claude-certification/SKILL.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/skills/claude-certification/SKILL.md), this skill orchestrates onboarding and progress tracking for Claude’s official certification exams. It maintains state in [`CLAUDE-CERTIFICATION.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/CLAUDE-CERTIFICATION.md) and provides structured preparation workflows aligned with Anthropic’s exam objectives. **Primary commands:** - Codex: `claude-certification` - Claude: `/claude-certification` ## Utility and Assessment Skills These supporting skills provide topic lookup, placement testing, and phase-specific quizzing. ### course-guide: Topic Navigation Implemented in [`skills/course-guide/SKILL.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/skills/course-guide/SKILL.md), this skill maps arbitrary topic names to exact lesson files. Given a concept like "attention", it directs the learner to the precise phase and document covering that material. **Primary commands:** - Codex: `course-guide ` - Claude: `/course-guide ` ### find-your-level: Placement Quiz Engine Stored in [`skills/find-your-level/SKILL.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/skills/find-your-level/SKILL.md), this skill administers a 10-question assessment across five knowledge areas. It calculates a score, maps it to an entry phase (1-18), and writes a placement section to the learner’s state file. **Primary commands:** - Codex: `find-your-level` - Claude: `/find-your-level` ### check-understanding: Phase-Level Assessment Located at [`skills/check-understanding/SKILL.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/skills/check-understanding/SKILL.md), this skill executes comprehensive quizzes for specific phases. It reads `phases//quiz.json` files and evaluates mastery before permitting progression. **Primary commands:** - Codex: `check-understanding ` - Claude: `/check-understanding ` ## How to Invoke AI Learning Skills All skills follow a portable contract, allowing identical invocation across CLI, chat interfaces, and natural-language contexts. ### Codex CLI Style ```bash # Initialize learner profile and study plan start-learning # Resume standard curriculum learn # Access specialized tracks learn-mcp learn-agent-skills claude-certification # Navigation and assessment course-guide transformers find-your-level check-understanding 13 ``` ### Claude Code Slash Commands ```text /start-learning /learn /learn-mcp /learn-agent-skills /claude-certification /course-guide attention /find-your-level /check-understanding 13 ``` ### Natural Language Invocation ```text Use start-learning to create my study plan. Use learn to continue the next lesson. Use course-guide to show me the RAG lesson. Use find-your-level to place me in the right phase. Use check-understanding 13 to quiz me on Phase 13. Use learn-mcp to start the Model Context Protocol path. ``` ## Skill Architecture and State Management The curriculum engine operates on a **state-first resolution** pattern. When invoked, each skill first checks for existing state files in the working directory: - [`LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/LEARNING.md) → Resume via `learn` - [`MCP-LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/MCP-LEARNING.md) → Resume via `learn-mcp` - [`AGENT-SKILLS-LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/AGENT-SKILLS-LEARNING.md) → Resume via `learn-agent-skills` - [`CLAUDE-CERTIFICATION.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/CLAUDE-CERTIFICATION.md) → Resume via `claude-certification` If no state exists, `start-learning` executes automatically, running the placement quiz from `find-your-level` before handing control to the generic `learn` skill. Specialized routes (`learn-mcp`, `learn-agent-skills`) skip generic onboarding and immediately initialize their dedicated state files and JSON manifests. ## Summary - **Eight portable skills** drive the entire ai-engineering-from-scratch tutoring experience, each defined in isolated [`SKILL.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/SKILL.md) files. - **Core skills** (`start-learning`, `learn`) handle onboarding and daily lesson delivery, reading from [`LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/LEARNING.md) and `phases/**/docs/en.md`. - **Specialized tracks** (`learn-mcp`, `learn-agent-skills`, `claude-certification`) maintain separate state files and JSON manifests for protocol-specific or certification curricula. - **Utility skills** (`course-guide`, `find-your-level`, `check-understanding`) provide topic lookup, placement testing, and phase-level assessment by reading [`quiz.json`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/quiz.json) files. - **Host-agnostic design** allows identical skill invocation across Codex CLI, Claude Code, and natural-language interfaces without code changes. ## Frequently Asked Questions ### How does the repository determine which AI learning skill to run first? The skill engine checks for existing state files ([`LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/LEARNING.md), [`MCP-LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/MCP-LEARNING.md), etc.) in the working directory. If a state file exists, the corresponding skill resumes automatically. If no state exists, `start-learning` runs the onboarding interview and placement quiz before transferring control to the generic `learn` skill. ### Can I switch between the general curriculum and specialized tracks like MCP or Agent Skills? Yes. Each track maintains its own state file (e.g., [`MCP-LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/MCP-LEARNING.md) for the MCP path). Invoking `learn-mcp` or `learn-agent-skills` initializes the dedicated track and its separate progression log. You can resume the general curriculum later by invoking `learn`, which reads the original [`LEARNING.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/LEARNING.md). ### What file format stores the lesson content and quizzes consumed by these skills? Lesson content resides in `phases//docs/en.md` as markdown documents. Quizzes are stored as structured JSON in `phases//quiz.json`. The `learn` and `check-understanding` skills parse these files to deliver content and evaluate responses. ### Are these AI learning skills compatible with AI hosts other than Codex and Claude? Yes. The skills are implemented as portable SKILL.md contracts that any host supporting the "skill" pattern can execute. The repository demonstrates usage for Codex (CLI commands) and Claude (slash commands), but the same markdown definitions work with any compatible tutoring engine that respects the skill contract.