What problem does it solve? Game projects often fail because architectural decisions are made inconsistently or left implicit, causing AI agents and developers to produce conflicting implementations. This Skill guides a structured, step-by-step discovery workflow that produces a complete architecture document covering engine choice, rendering, physics, networking, save systems, and deployment. ## Core Features & Use Cases - Guided Decision Workflow: Walks through critical decision categories (engine, rendering pipeline, physics, networking, input, AI, save persistence, UI, asset pipeline, deployment) using a decision catalog with composability relationships and opinionated stacks. - Engine-Specific Knowledge: Loads deep knowledge fragments for Godot, Unity, Unreal, Phaser, and Roblox only when that engine is selected, covering coding conventions, performance optimization, plugins, and licensing. - MCP Tooling Recommendations: Suggests Model Context Protocol servers for the chosen engine so AI agents can inspect and edit the game project directly. - Use Case: A solo developer planning a 2D roguelike uses this Skill to decide between Godot and Unity, select a save system, define implementation patterns, and produce an architecture document that keeps all future AI-assisted coding consistent. ## Quick Start Ask the AI to design the game architecture for your project by describing your game concept and target platforms.