# HyperTwist — API.md

## API philosophy

HyperTwist should use APIs to support the native runtime, not to replace it.
The system should remain primarily native-first and local-first where reasonable.

## Main API families

### Recognition API
- frame ingestion
- facelet/state detection
- confidence reporting
- corrective suggestions

### Replay API
- replay storage and export
- solve timeline annotations
- AI-commentary attachment

### Coaching API
- drill recommendations
- progression updates
- error clustering
- personalized next-step guidance

### Profile / progression API
- user settings
- training history
- unlocked modules
- performance metrics

### Curriculum API
- guided lesson packets
- method ladders
- hyper-specific modules
- school or educational variants if later needed

## Deployment posture

Keep local computation local where sensible.
Do not server-centralize everything just because an HTTP interface can be drawn.
