Skip to content
Get packs

Three.js Enemy Systems Builder

Designs data-driven enemy definitions, move timing and placeholder fallbacks for Three.js action games

Source Download skill
Repository
MengTo/Skills
Stars
7,187
Licence
MIT
Files
2 files

What it does

This skill teaches an AI agent how to structure enemies in a Three.js action game as reusable data definitions rather than hard-coded logic. When it is active, the agent separates enemy content (stats, moves, IDs) from runtime state (health, timers, positions), defines each attack as timed data with hit windows and cooldowns, normalizes 3D models to a shared contract, and falls back to clearly marked placeholders when a model is missing. It also suggests test fixtures and playthrough checks for validating the result.

Great for

  • Indie or hobby developers building a Three.js action or combat game who want maintainable enemy systems
  • Game programmers refactoring enemy code into shared, data-driven archetypes
  • Teams that want a checklist for validating enemy content, timing and contact logic before shipping

Skip it if

  • Non-developers or people not building a Three.js game, since the guidance assumes an existing codebase and game engine concepts
  • Projects using a different engine (Unity, Godot, Unreal) where Three.js-specific conventions would not apply
  • Users expecting the skill to produce finished 3D art or animations; it only sets structural rules and conventions

Try asking

  • “Refactor my hard-coded enemy classes into reusable data-driven archetypes for my Three.js game”
  • “Design a move definition schema with startup, active windows, recovery and per-target hit limits for a melee boss”
  • “Set up a placeholder fallback for enemy models that are not yet exported, keeping hitboxes and timing intact”
  • “Write deterministic test fixtures for enemy spawn, interrupt, stagger and death in my Three.js project”
Step-by-step guide: how to use Three.js Enemy Systems BuilderInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 2 original files, the MIT licence and an attribution note.

    build-threejs-enemy-systems.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip build-threejs-enemy-systems.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip build-threejs-enemy-systems.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Give the agent your existing enemy code and current model conventions so it can map them onto the defined contracts rather than inventing new ones
  • Ask for the content schema and validation rules first, then the move definitions, then tests, to keep changes reviewable
  • Expect the agent to also suggest running browser playthroughs; these depend on your own repository's tooling, which the skill does not provide

What's inside

  • agents/openai.yaml
  • SKILL.md

Redistributed unmodified from MengTo/Skills under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.