game-data-driven-design

Data-driven architecture translates game design concepts into per-entity data definitions and relationships, reducing ambiguity. It maps GDD scope to structured entity definitions, creating independent documents that maintain system scalability and minimize rework.

Generating entity definitions from a GDD involves applying a per-entity definition workflow to produce an OutputDirectory. This directory contains an _index.md file and individual {DefinitionTypeName}_Def.md files for each core game entity, visualizing architecture and supporting versioning.

Structuring data-driven entities requires mapping core game relationships and integrating them with chosen persistence formats. This approach satisfies the definition workflow by producing structured markdown documents that explicitly track version compatibility and engine integration.

Yes, the data-driven architecture approach applies to core game entities and their integration with chosen persistence formats and engines. It structures entity relationships to ensure compatibility within the specified engine environment.

You need independent definition documents per entity when translating GDD concepts into scalable data models. This per-entity workflow reduces ambiguity by generating structured definition files that support system architecture visualization and version control.

The approach requires providing clear system scope and entity requirements upfront to generate the OutputDirectory. Without explicit design intent and defined entity relationships, the generated definition documents and ER diagrams cannot accurately map the game architecture.