agentleFS
Bbeierle12Bbeierle12/Skill-MCP-Claude/skills/3d-building-advanced/SKILL.md

building-mechanics

Skill9 starsChanged 6 months agoMITView on GitHub

Three.js 3D building system with spatial indexing, structural physics, and multiplayer networking. Use when creating survival games, sandbox builders, or any game with player-constructed structures. Covers performance optimization (spatial hash grids, octrees, chunk loading), structural validation (arcade/heuristic/realistic physics modes), and multiplayer sync (delta compression, client prediction, conflict resolution).

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Read these for detailed implementation guidance:

    line 29

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

3D Building Mechanics

Complete building system for Three.js games with performance optimization, structural physics, and multiplayer networking.

Quick Start

import { SpatialHashGrid } from './scripts/spatial-hash-grid.js';
import { HeuristicValidator } from './scripts/heuristic-validator.js';

// Spatial indexing for fast queries
const spatialIndex = new SpatialHashGrid(10);
spatialIndex.insert(piece, piece.position);
const nearby = spatialIndex.queryRadius(position, 15);

// Structural validation (Rust/Valheim style)
const validator = new HeuristicValidator({ mode: 'heuristic' });
validator.addPiece(piece);
const canPlace = validator.validatePlacement(newPiece);

Reference Files

Read these for detailed implementation guidance:

  • references/performance-at-scale.md - Spatial partitioning, chunk loading, instancing, LOD
  • references/structural-physics-advanced.md - Arcade vs heuristic vs realistic physics
  • references/multiplayer-networking.md - Authority models, delta sync, conflict resolution

Scripts

Performance (references/performance-at-scale.md)

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

Structural Physics (references/structural-physics-advanced.md)

  • scripts/heuristic-validator.js - Fast validation (Fortnite/Rust/Valheim modes)
  • scripts/stability-optimizer.js - Caching and batch updates
  • scripts/damage-propagation.js - Damage states, cascading collapse
  • scripts/physics-engine-lite.js - Optional realistic physics

Multiplayer (references/multiplayer-networking.md)

  • scripts/delta-compression.js - Only send changed state
  • scripts/client-prediction.js - Optimistic placement with rollback
  • scripts/conflict-resolver.js - Handle simultaneous builds
  • scripts/building-network-manager.js - Complete server/client system

Key Patterns

Spatial Indexing Selection

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

Physics Mode Selection

  • Arcade (Fortnite): Connectivity only, instant collapse, best for combat
  • Heuristic (Rust/Valheim): Stability %, predictable, best for survival
  • Realistic: Full stress/strain, expensive, best for engineering sims

Multiplayer Pattern

Server-authoritative with client prediction. Use delta compression for sync.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.