explaining-code
Explains code with visual diagrams and analogies. Use when explaining how code works, teaching about a codebase, or when the user asks "how does this work?"
explaining-code
Explains code with visual diagrams and analogies. Use when explaining how code works, teaching about a codebase, or when the user asks "how does this work?"
cpp-basics
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tech-manga-explainer
生成技术科普漫画，用对话形式解释复杂的技术概念。当用户请求「用漫画解释技术」「生成技术科普漫画」「把这个技术概念画成漫画」「漫画教程」「用漫画讲解 XXX」或类似需求时使用。适合 n8n、Kubernetes、AI、编程、架构等技术话题。通过 nanobanana + Gemini API 生成图片。
quiz-generator
This skill generates interactive multiple-choice quizzes for each chapter of an intelligent textbook, with questions aligned to specific concepts from the learning graph and distributed across Bloom's Taxonomy cognitive levels to assess student understanding effectively. Use this skill after chapter content has been written and the learning graph exists.
moving-rainbow
Generate MicroPython programs for the Moving Rainbow LED strip educational project using Raspberry Pi Pico with NeoPixel strips and button controls.
story-generator
This skill generates graphic novel narratives about physicists and scientists for intelligent textbooks. It creates compelling, historically-accurate stories with image prompts designed for high school students. Use this skill when the user wants to add a new scientist story to the Physics History Graphic Novels section of an MkDocs Material textbook, or when creating educational graphic novel content about historical scientists.
chapter-content-generator
This skill generates comprehensive chapter content for intelligent textbooks after the book-chapter-generator skill has created the chapter structure. Use this skill when a chapter index.md file exists with title, summary, and concept list, and detailed educational content needs to be generated at the appropriate reading level with rich non-text elements including diagrams, infographics, and MicroSims. (project, gitignored)
diagram-reports-generator
This skill generates comprehensive diagram and MicroSim reports for the geometry course by analyzing chapter markdown files and creating table and detail reports. Use this skill when working with an intelligent textbook (specifically geometry-course) that needs updated visualization of all diagrams and MicroSims across chapters, including their status, difficulty, Bloom's Taxonomy levels, and UI complexity.
course-description-analyzer
This skill analyzes or creates course descriptions for intelligent textbooks by checking for completeness of required elements (title, audience, prerequisites, topics, Bloom's Taxonomy outcomes) and providing quality scores with improvement suggestions. Use this skill when working with course descriptions in /docs/course-description.md that need validation or creation for learning graph generation.
learning-graph-generator
Generates a comprehensive learning graph from a course description, including 200 concepts with dependencies, taxonomy categorization, and quality validation reports. Use this when the user wants to create a structured knowledge graph for educational content.
faq-generator
This skill generates a comprehensive set of Frequently Asked Questions (FAQs) from the course description, course content, learning graphs, concept lists, MicroSims, and glossary terms to help students understand common questions and prepare content for chatbot integration. Use this skill after course description, learning graph, glossary, and at least 30% of chapter content exist.
book-chapter-generator
This skill generates a structured chapter outline for intelligent textbooks by analyzing course descriptions, learning graphs, and concept dependencies. Use this skill after the learning graph has been created and before generating chapter content, to design an optimal chapter structure that respects concept dependencies and distributes content evenly across 6-20 chapters.
reference-generator
This skill generates curated, verified reference lists for textbooks with level-appropriate resources (10 for junior-high, 20 for senior-high, 30 for college, 40 for graduate). References are formatted with links, publication details, and relevance descriptions. Use this skill when working with intelligent textbooks that need academic references, either book-level or chapter-level.
multi-agent-ai-projects
Guidelines for multi-agent AI and learning projects with lesson-based structures. Activate when working with AI learning projects, experimental directories like .spec/, lessons/ directories, STATUS.md progress tracking, or structured learning curricula with multiple modules or lessons.
learn-anything
Metalearning skill that helps master any topic efficiently by identifying critical 20% material, building expert vocabulary, and creating research-backed learning roadmaps. Auto-trigger when user says "learn [topic]", "help me learn [topic]", "I want to learn [topic]", or asks for guidance on understanding a new subject. Supports comprehensive plans, interactive guidance, or minimalist just-in-time delivery.
ship-learn-next
Transform learning content (like YouTube transcripts, articles, tutorials) into actionable implementation plans using the Ship-Learn-Next framework. Use when user wants to turn advice, lessons, or educational content into concrete action steps, reps, or a learning quest.
socratic-teaching-scaffolds
Use when teaching complex concepts (technical, scientific, philosophical), helping learners discover insights through guided questioning rather than direct explanation, correcting misconceptions by revealing contradictions, onboarding new team members through scaffolded learning, mentoring through problem-solving question frameworks, designing self-paced learning materials, or when user mentions "teach me", "help me understand", "explain like I'm", "learning path", "guided discovery", or "Socratic method".
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