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Performance At Scale

  • 55 installs
  • 8 repo stars
  • Updated August 4, 2026
  • bbeierle12/skill-mcp-claude

performance-at-scale is a Claude skill that provides spatial indexing and world streaming to optimize Three.js building games with thousands of pieces.

About

This skill provides spatial indexing and world streaming for Three.js building games with thousands of pieces. It ships a spatial hash grid, an octree, a chunk manager for streaming large maps, and a performance profiler, plus a selection guide for choosing the right structure by piece count and distribution. A developer uses it to optimize spatial queries and performance in large building systems.

  • Spatial hash grid for O(1) queries on uniform distributions
  • Octree for adaptive queries on clustered objects
  • Chunk manager for world streaming plus a performance profiler

Performance At Scale by the numbers

  • 55 all-time installs (skills.sh)
  • Ranked #155 of 247 Game Development skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
At a glance

performance-at-scale capabilities & compatibility

Capabilities
multiplayer building · platform building
Use cases
debugging
From the docs

What performance-at-scale says it does

Spatial indexing and world streaming for Three.js building games with thousands of pieces.
SKILL.md
npx skills add https://github.com/bbeierle12/skill-mcp-claude --skill performance-at-scale

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Listed on Skillselion
Installs55
repo stars8
Last updatedAugust 4, 2026
Repositorybbeierle12/skill-mcp-claude

What it does

Optimize Three.js building games with thousands of pieces using spatial hash grids, octrees, chunk streaming, and benchmarking tools.

Who is it for?

Optimizing spatial queries and streaming in large Three.js building games

Skip if: Small scenes under a thousand pieces where a plain array suffices

When should I use this skill?

Optimizing building games, implementing spatial queries, chunk loading, or profiling performance

What you get

Fast spatial queries and streamed worlds via the right indexing structure

  • Spatial hash grid
  • Octree
  • Chunk manager

By the numbers

  • 4 bundled scripts (hash grid, octree, chunk manager, profiler)
  • 4-row selection guide by piece count

Files

SKILL.mdMarkdownGitHub ↗

Performance at Scale

Spatial indexing and world streaming for large-scale building systems.

Quick Start

import { SpatialHashGrid } from './scripts/spatial-hash-grid.js';
import { Octree } from './scripts/octree.js';

// Uniform distribution - use hash grid
const grid = new SpatialHashGrid(10);
grid.insert(piece, piece.position);
const nearby = grid.queryRadius(position, 15);

// Clustered bases - use octree
const octree = new Octree(bounds, { maxDepth: 8 });
octree.insert(piece);
const inBox = octree.queryBox(min, max);

Reference

See references/performance-at-scale.md for detailed guidance on:

  • Spatial partitioning selection (when to use grid vs octree)
  • Chunk loading strategies
  • Instancing and LOD
  • Memory management

Scripts

  • scripts/spatial-hash-grid.js - O(1) queries for uniform distribution
  • scripts/octree.js - Adaptive queries for clustered objects
  • scripts/chunk-manager.js - World streaming for large maps
  • scripts/performance-profiler.js - Benchmarking utilities

Selection Guide

PiecesDistributionUse
<1,000AnyArray
1-5kUniformSpatialHashGrid
1-5kClusteredOctree
5k+AnyChunkManager + Octree per chunk

Related skills

FAQ

When should I use a hash grid vs an octree?

Use a spatial hash grid for uniform distributions and an octree for clustered objects, per the selection guide.

How does it handle very large maps?

It provides a chunk manager for world streaming, combined with an octree per chunk for 5k+ pieces.

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