ReddRadar
Agent skill
game-development
Game development orchestrator. Routes to platform-specific skills based on project needs.
Install this agent skill to your Project
npx add-skill https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/creative-design/game-development
SKILL.md
Game Development
Orchestrator skill that provides core principles and routes to specialized sub-skills.
When to Use This Skill
You are working on a game development project. This skill teaches the PRINCIPLES of game development and directs you to the right sub-skill based on context.
Sub-Skill Routing
Platform Selection
| If the game targets... | Use Sub-Skill |
|---|---|
| Web browsers (HTML5, WebGL) | game-development/web-games |
| Mobile (iOS, Android) | game-development/mobile-games |
| PC (Steam, Desktop) | game-development/pc-games |
| VR/AR headsets | game-development/vr-ar |
Dimension Selection
| If the game is... | Use Sub-Skill |
|---|---|
| 2D (sprites, tilemaps) | game-development/2d-games |
| 3D (meshes, shaders) | game-development/3d-games |
Specialty Areas
| If you need... | Use Sub-Skill |
|---|---|
| GDD, balancing, player psychology | game-development/game-design |
| Multiplayer, networking | game-development/multiplayer |
| Visual style, asset pipeline, animation | game-development/game-art |
| Sound design, music, adaptive audio | game-development/game-audio |
Core Principles (All Platforms)
1. The Game Loop
Every game, regardless of platform, follows this pattern:
INPUT → Read player actions
UPDATE → Process game logic (fixed timestep)
RENDER → Draw the frame (interpolated)
Fixed Timestep Rule:
- Physics/logic: Fixed rate (e.g., 50Hz)
- Rendering: As fast as possible
- Interpolate between states for smooth visuals
2. Pattern Selection Matrix
| Pattern | Use When | Example |
|---|---|---|
| State Machine | 3-5 discrete states | Player: Idle→Walk→Jump |
| Object Pooling | Frequent spawn/destroy | Bullets, particles |
| Observer/Events | Cross-system communication | Health→UI updates |
| ECS | Thousands of similar entities | RTS units, particles |
| Command | Undo, replay, networking | Input recording |
| Behavior Tree | Complex AI decisions | Enemy AI |
Decision Rule: Start with State Machine. Add ECS only when performance demands.
3. Input Abstraction
Abstract input into ACTIONS, not raw keys:
"jump" → Space, Gamepad A, Touch tap
"move" → WASD, Left stick, Virtual joystick
Why: Enables multi-platform, rebindable controls.
4. Performance Budget (60 FPS = 16.67ms)
| System | Budget |
|---|---|
| Input | 1ms |
| Physics | 3ms |
| AI | 2ms |
| Game Logic | 4ms |
| Rendering | 5ms |
| Buffer | 1.67ms |
Optimization Priority:
- Algorithm (O(n²) → O(n log n))
- Batching (reduce draw calls)
- Pooling (avoid GC spikes)
- LOD (detail by distance)
- Culling (skip invisible)
5. AI Selection by Complexity
| AI Type | Complexity | Use When |
|---|---|---|
| FSM | Simple | 3-5 states, predictable behavior |
| Behavior Tree | Medium | Modular, designer-friendly |
| GOAP | High | Emergent, planning-based |
| Utility AI | High | Scoring-based decisions |
6. Collision Strategy
| Type | Best For |
|---|---|
| AABB | Rectangles, fast checks |
| Circle | Round objects, cheap |
| Spatial Hash | Many similar-sized objects |
| Quadtree | Large worlds, varying sizes |
Anti-Patterns (Universal)
| Don't | Do |
|---|---|
| Update everything every frame | Use events, dirty flags |
| Create objects in hot loops | Object pooling |
| Cache nothing | Cache references |
| Optimize without profiling | Profile first |
| Mix input with logic | Abstract input layer |
Routing Examples
Example 1: "I want to make a browser-based 2D platformer"
→ Start with game-development/web-games for framework selection
→ Then game-development/2d-games for sprite/tilemap patterns
→ Reference game-development/game-design for level design
Example 2: "Mobile puzzle game for iOS and Android"
→ Start with game-development/mobile-games for touch input and stores
→ Use game-development/game-design for puzzle balancing
Example 3: "Multiplayer VR shooter"
→ game-development/vr-ar for comfort and immersion
→ game-development/3d-games for rendering
→ game-development/multiplayer for networking
Remember: Great games come from iteration, not perfection. Prototype fast, then polish.
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
davila7/claude-code-templates
verl-rl-training
Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.
davila7/claude-code-templates
openrlhf-training
High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.
davila7/claude-code-templates
gguf-quantization
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
davila7/claude-code-templates
Claude Code Guide
Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.
davila7/claude-code-templates
qdrant-vector-search
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
davila7/claude-code-templates
behavioral-modes
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
Didn't find tool you were looking for?