simplify-topic

# Purpose Reframe a concept at a lower abstraction so the learner builds accurate intuition before encountering technical complexity. Simplification is choosing the right abstraction for the learner's mental model, then re-injecting complexity once the foundation is stable. # Activation - Learner says "I don't understand" or "explain like I'm new." `check-understanding` reveals prior explanation was too abstract/jargon-heavy. Cross-domain learner needs an analogy bridge. `teach-concept` was used and learner still can't state the core intuition. - **Skip if**: learner understands basics and needs depth → `deep-dive`. Confusion is from a misconception → `misconception-detector`. Concept is simple enough already. - **Routing**: after successful simplification, use `teach-concept` to re-introduce correct technical terminology. Never leave learner permanently at simplified level. # Inputs - Concept to simplify, learner's background domain, abstraction level where understanding broke, specific unclear aspect. # Abstraction Levels - **Level 0 (Everyday)**: household/daily life analogy, zero technical vocab → absolute beginner. - **Level 1 (Domain-Adjacent)**: analogy from learner's known field → practitioner switching domains. - **Level 2 (Simplified Technical)**: correct terms, simplified mechanism → beginner with some background. - **Level 3 (Full Technical)**: precise mechanism with edge cases → standard `teach-concept` level. # Workflow 1. **Detect** — Ask one question to identify where understanding breaks (terminology? mechanism? motivation?). Identify learner's domain for analogy selection. Select starting level (0, 1, or 2). 2. **Build Analogy** — One analogy from the learner's known domain. State explicitly where it holds AND where it breaks down — oversimplified analogies create new misconceptions. 3. **Simplified Explanation** — Deliver at selected level using the analogy as scaffold. One core idea per step. No technical vocabulary at level 0; introduce terms one at a time at level 2. 4. **Intuition Check** — Ask learner to restate in their own words using the analogy. If wrong: identify failure point and rebuild with a different analogy. 5. **Complexity Re-Injection** — Introduce one layer of technical accuracy on top of confirmed intuition. Replace analogy language with correct terms, one at a time. Confirm at each step. 6. **Handoff** — When learner articulates using correct vocabulary: hand off to `teach-concept` or `deep-dive`. # Rules - DO: always state where the analogy breaks down — analogies that never fail create misconceptions. - DO: complexity re-injection is mandatory — simplification is a bridge, not a destination. - DO: confirm the analogy domain is familiar to the learner before using it. - DON'T: use multiple analogies simultaneously — pick the best one until it fails. - DON'T: discard a failing analogy until after 2 attempts; then switch. - DON'T: leave the session at simplified level — at minimum introduce correct vocabulary. - DON'T: simplify a concept the learner already understands correctly — probe first. # Output Responses should contain: context (concept + confusion level + learner background + selected level), analogy (with explicit limits), simplified explanation, intuition check prompt, complexity re-injection steps, and handoff plan. Format naturally. # Checklist - [ ] Analogy grounded in learner's known domain and limits stated. - [ ] Learner restates concept using analogy before re-injection. - [ ] Complexity re-injection introduces correct technical vocabulary. - [ ] Session does not end at simplified level.