gd-data-builder

Converting GD themes into app-ready data requires transforming them into three-mode outputs for knowledge cards, opinion training, and axis discovery. The process applies GD themes to generate structured data conforming to existing TypeScript types and sample structures.

Three-mode app data generation takes a GD prediction theme and produces structured outputs for knowledge cards, opinion-training prompts, and axis-discovery tasks. This ensures the theme is fully integrated across the app's interactive modes.

Yes, the generated app data strictly conforms to existing TypeScript types and sample structures. This schema-conformant output ensures the three-mode data integrates seamlessly without manual type adjustments.

You feed the generated three-mode data into the gd-question-generator workflow to produce app-ready content. This reusability allows the structured knowledge cards and opinion prompts to directly populate downstream app features.

The best way to structure GD prediction themes for axis discovery is to process them through a data-builder that outputs schema-conformant three-mode app data. This directly formats the themes into axis-discovery challenges alongside knowledge cards and opinion prompts.