What problem does it solve? Learning a new topic with an AI is usually stateless and unstructured — each session starts from zero, with no memory of what you already know or why you are learning. This Skill turns a directory into a persistent teaching workspace that tracks your mission, progress, and resources across sessions. ## Core Features & Use Cases - Stateful teaching workspace: Maintains MISSION.md, RESOURCES.md, GLOSSARY.md, NOTES.md, and numbered learning records to track goals, trusted sources, and demonstrated understanding. - HTML lessons and references: Produces short, self-contained HTML lessons in ./lessons/ plus printable reference documents in ./reference/, built from reusable components in ./assets/. - Zone of proximal development: Uses learning records to pick the next lesson at the right difficulty, applying retrieval practice, spacing, and interleaving for long-term retention. - Use Case: You want to learn strength training over several weeks. The Skill interviews you to write a mission, curates trusted resources, then generates a sequence of interactive HTML lessons with quizzes, recording each milestone so future sessions build on what you have proven you know. ## Quick Start Ask the agent to teach you a topic, for example: "Teach me the basics of Rust ownership over the next few sessions."
