What problem does it solve? Learning a new topic with an AI assistant is usually stateless: every session starts from zero, prior knowledge gets re-taught, and exercises are disconnected from real goals. This Skill turns a directory into a persistent teaching workspace that tracks why the user is learning, what they already know, and what to teach next. ## Core Features & Use Cases - Stateful teaching workspace: Maintains MISSION.md, GLOSSARY.md, RESOURCES.md, and numbered learning records to ground every session in the user's goal and current understanding. - Zone of proximal development: Reads learning records to pick the next topic that challenges the user just enough, avoiding re-teaching or overwhelming jumps. - Knowledge, skills, and wisdom loop: Produces interactive HTML explainers with citations, designs feedback-driven exercises, and points users to trusted communities for real-world practice. - Use Case: A user wants to learn strength training. The Skill interviews them to write a mission, curates trusted resources, builds an explainer on progressive overload, quizzes them, and records what they understood so the next session builds on it. ## Quick Start Ask the assistant to teach you a topic, for example: teach me the fundamentals of strength training in this workspace.
