What problem does it solve? AI agents implementing game code often miss project-specific conventions, engine lifecycle rules, and performance constraints, producing inconsistent code. This Skill captures those unobvious implementation rules into a single optimized project-context.md file that every agent reads before writing code. ## Core Features & Use Cases - Project Discovery: Scans engine files (Unity ProjectSettings, Unreal .uproject, Godot project.godot), package manifests, and existing code to identify the technology stack with exact versions. - Collaborative Rule Generation: Walks through engine-specific, performance, organization, testing, and platform rule categories with the user, validating each section before saving. - LLM-Optimized Output: Produces a lean, scannable project-context.md focused on anti-patterns and gotchas agents would otherwise miss. - Use Case: A Unity game team runs this workflow once so that every subsequent AI-assisted story implementation follows their assembly definition rules, coroutine patterns, and frame budget constraints. ## Quick Start Ask the agent to generate project context for your game project, then follow the guided discovery and rule confirmation steps.
