What problem does it solve? RTS games collapse under scale when movement systems, neighbor queries, pathfinding, and ECS iteration use inefficient patterns like O(n²) algorithms, per-frame allocations, and hidden memory churn. This Skill provides concrete performance rules for building simulations that remain stable at 20x current scale. ## Core Features & Use Cases - Bottleneck Identification: Pinpoints the real RTS bottlenecks—movement systems, neighbor queries, pathfinding, ECS iteration, visibility checks, draw calls, and memory churn—rather than blaming graphics alone. - Hot Loop Rules: Enforces for loops, cached references, and reusable buffers while banning map/filter/reduce, closures, temporary vectors, and object spreading in hot paths. - Scalability Patterns: Prescribes object pooling, flat arrays, spatial partitioning, batched updates, and reusable vector memory to keep frametimes stable and GC pressure low. - Use Case: When your unit movement system stutters at 5,000 units, apply these rules to replace per-entity allocations with pooled flat arrays and spatial partitioning for neighbor queries. ## Quick Start Review my RTS movement and neighbor query systems using the rts-performance skill and rewrite the hot loops to eliminate per-frame allocations.
