# Didactopus

This update adds a **learner-state progression engine scaffold**.

It models how mastery records can evolve over time from repeated evidence, with:
- score aggregation
- confidence reinforcement and decay
- prerequisite-gated advancement
- next-step recommendations

Current components:
- learner state model
- evidence application engine
- confidence update logic
- prerequisite-gated readiness checks
- recommendation engine
- tests and sample data
