async-learning-teacher
SolidTransform saved links, papers, articles, posts, videos, and reference collections into approachable AI teaching artifacts for later study. Use when a user wants to queue learning material, create a readable explanation from a source, teach a paper or post step by step, or run an interactive tutor that validates understanding over multiple sessions.
Install
Quality Score: 85/100
Skill Content
Details
- Author
- tamdogood
- Repository
- tamdogood/builder-essential-skills
- Created
- 2 months ago
- Last Updated
- 3 weeks ago
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
teach
Teacher mode — turn a session recap / article / docs / concept / piece of code / bug into an incremental mini-course with comprehension checks, quizzes, and an auto-saved summary note. Invoke /teach [topic or URL]. Triggers — "explain it like a teacher", "walk me through what we did", "turn this into a lesson", "quiz me", "teach me", "let's learn this together".
ape-teach
Masterclass teacher that takes any concept, note, URL, paper, or write-up, expands on it if needed, and teaches it through and through, step by step. Uses real-world and engineering mental models, selective and intuitive analogies with breaking points only where needed, visual ASCII diagrams, minimal code snippets, in-between check questions, web research when required, and prompts to up the ante and go deeper until the user explicitly signals they are done. Trigger on "ape teach", "teach me", "masterclass on this", "explain this step by step", or when the user provides a concept, note, paper, or link and asks to learn or be taught it thoroughly.
adaptive-teacher
General-purpose adaptive teaching, for any topic — mathematics, Lean, programming, or anything else. Use when the user asks a clarifying or conceptual question ("what does X mean?", "why does this work?", "what's the difference between X and Y?"), asks to be taught a topic or walked through something step-by-step, asks for an explanation in simpler terms, requests exercises, or follows up on any explanation — including explanations produced by other skills (e.g. mathlib-api). Maintains a persistent, user-inspectable learner model (learner/) so teaching adapts to this user across sessions.