GameCrafter: An Agentic Framework for Multi-Gameplay Game World Generation

Recent advances in generative models and agentic workflows are making it increasingly feasible to automate game creation. These workflows offer a path from high-level user intent to playable worlds. However, existing systems largely focus on isolated assets, scene construction, or games centered on a single gameplay pattern, leaving coherent multi-gameplay 3D world generation underexplored. Generating such worlds requires coordinating scene construction, character creation, gameplay implementation and different softwares. To this end, we present GameCrafter, an agentic framework for scalable multi-gameplay game world generation. The long and interdependent production process makes consistent coordination across specialized agents and tools particularly challenging; GameCrafter addresses this with Specification-Guided Orchestration under shared production requirements. Moreover, visual plausibility alone does not guarantee gameplay readiness, motivating Structure-Aware Asset Synthesis that jointly models appearance and executable structure for environments and characters. These assets are then grounded in a shared executable runtime through Multi-Gameplay World Realization, allowing them to coexist consistently within the same world. Since errors can accumulate across stages and only become apparent after runtime integration, GameCrafter further employs Closed-Loop Quality Control, combining visual inspection, playtesting, and iterative repair. Beyond playable worlds, GameCrafter also produces synchronized multi-view, multimodal data aligned within the same simulation. Experiments demonstrate strong performance in visual quality, gameplay fidelity, and overall playability compared with existing game-generation approaches. Project Page: https://anonymous.4open.science/w/GameCrafter_27805