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spatial_data_structures

Implement spatial indexing for ECS collision detection and neighborhood queries.

2|Updated Jul 2, 2026
Search Tags:#collision detection#ecs#octree#bvh#quadtree#spatial hashing#chunk management
One-click install
npx skills add https://github.com/Xyrces/godot-ecs-gamedev-playbook --skill spatial-data-structures
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: spatial_data_structures
Source: https://github.com/Xyrces/godot-ecs-gamedev-playbook/tree/main/skills/spatial_data_structures
Command: npx skills add https://github.com/Xyrces/godot-ecs-gamedev-playbook --skill spatial-data-structures

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you organize game world data so collision checks, nearby-object searches, and chunk loading stay fast as your ECS game scales.

Core Features & Use Cases

  • Spatial hashing for uniform, high-speed broad-phase lookup in 2D and flat 3D spaces.
  • Quadtree and octree structures for variable-density worlds that need adaptive partitioning.
  • BVH support for raycasting and complex overlap queries in dynamic 3D scenes.
  • Chunk grid management for tile worlds, open-world streaming, and loaded-area queries.
  • ECS integration patterns for rebuilding spatial indices each tick and generating collision candidate pairs.
  • Use case: a large action game can use a spatial hash for moving enemies, a chunk grid for world streaming, and a BVH for weapon raycasts.

Quick Start

Ask for a spatial index design that matches your game world, then generate the ECS-facing data structure and query flow for collision and neighbor searches.

Frequently Asked Questions about spatial_data_structures

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize broad-phase collision detection in an ECS game?▼

Broad-phase collision detection in an ECS game is optimized by implementing spatial indexing structures like spatial hashing, quadtrees, or octrees to quickly filter non-colliding pairs before narrow-phase checks.

What is the best spatial data structure for variable-density 2D and 3D worlds?▼

Quadtrees and octrees are the best spatial data structures for variable-density worlds because they provide adaptive partitioning, unlike uniform spatial hashing. BVHs are also effective for complex overlap and raycast queries in dynamic 3D scenes.

Can I use spatial hashing and chunk grids for open-world streaming?▼

Yes, you can use spatial hashing for high-speed uniform broad-phase lookup and chunk grid management for open-world streaming, handling tile worlds and loaded-area queries efficiently.

How do I perform deterministic high-performance neighborhood queries in ECS?▼

Deterministic high-performance neighborhood queries in ECS are performed by rebuilding spatial indices each tick using GC-free unmanaged structures. Static-dynamic partitioning separates non-moving geometry to maintain deterministic simulation outputs.

When should I use a BVH instead of an octree for raycasting?▼

You should use a BVH instead of an octree for raycasting and complex overlap queries in dynamic 3D scenes. Octrees excel at adaptive partitioning for variable-density worlds, while BVHs provide faster raycast performance for dynamic geometry.

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