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Game Architect

Community
Yuki001
game-architect

READ this skill when designing or planning any game system architecture — including combat, skills, AI, UI, multiplayer, narrative, or scene systems. Contains paradigm selection guides (DDD / Data-Driven / Prototype), system-specific design references, and mixing strategies. Works as a domain knowledge plugin alongside workflow skills (OpenSpec, SpecKit) or plan mode of an agent.

Overview

PublisherYuki001
Repositorygame-dev-skills
Skill namegame-architect
Stars
104
Forks
13
Bundled files
36
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 36 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Yuki001 on GitHub. Read the source before you install it.

Installation

Install the Game Architect AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Yuki001/game-dev-skills/tree/main/skills/game-architect
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Yuki001/game-dev-skills.git /tmp/game-dev-skills
mkdir -p .claude/skills
cp -r /tmp/game-dev-skills/skills/game-architect .claude/skills/game-architect
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Game Architect in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Game Architect on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Game Architect is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Game Architect Skill

Game architecture domain knowledge reference. Provides paradigm selection, system design references for game project architecture.

[!NOTE] This skill contains domain knowledge only, not a workflow. Pair it with a workflow skill (e.g., OpenSpec, SpecKit) or an agent's plan mode for structured design flow.

Usage Modes

With Workflow Skill (Recommended)

When used with a workflow skill (e.g., OpenSpec, SpecKit) or in the plan mode of an agent, this skill serves as a domain knowledge plugin:

  • During requirements/spec phases: Consult the Paradigm Selection Guide and System-Specific References to inform architectural decisions
  • During design/planning phases: Use the Reference Lookup Guide below to read relevant references/ documents

Knowledge Mode (Query)

When user requests to query knowledge for game architecture, this skill provides a reference lookup guide to relevant references/ documents based on the task.


Reference Lookup Guide

When designing game architecture, read the relevant references/ documents based on the task:

Architecture References

WhenRead
Always (high-level structure)references/macro-design.md
Always (core principles)references/principles.md
Requirement analysisreferences/requirements-analysis.md
Choosing DDD paradigmreferences/domain-driven-design.md
Choosing Data-Driven paradigmreferences/data-driven-design.md
Choosing Prototype paradigmreferences/prototype-design.md
Evolution & extensibility reviewreferences/evolution.md
Changing requirements in an existing implementationreferences/requirement-change-strategy.md
Performance optimization neededreferences/performance-optimization.md
Multiplayer support neededreferences/multiplayer-overview.md
  • For physical architecture design, see the Physical Architecture References table below.
  • For system-specific design, see the System-Specific References table below.
  • For multiplayer system design, see the Multiplayer References table below.

Note : Only read the multiplayer references when multiplayer is needed.

Physical Architecture References

WhenRead
Project structure & file organizationreferences/project-structure.md
Data formats, processing, custom formats, bundles, metadatareferences/data-files.md
Gameplay content editor applications and authoring pipelinesreferences/content-editor.md
Asset conventions & pipelinereferences/asset-conventions.md
Distribution, packaging, hot update, CDN, deploymentreferences/distribution.md

System-Specific References

System CategoryReference
Foundation & Core (Logs, Timers, Modules, Events, Resources, Audio, Input)references/system-foundation.md
Time & Logic Flow (Update Loops, Async, FSM, Command Queues, Controllers)references/system-time.md
Combat & Scene (Scene Graphs, Spatial Partitioning, ECS/EC, Loading)references/system-scene.md
UI & Modules (Modules Management, MVC/MVP/MVVM, UI Management, Data Binding, Reactive)references/system-ui.md
Skill System (Attribute, Skill, Buff)references/system-skill.md
Action Combat System (HitBox, Damage, Melee, Projectiles)references/system-action-combat.md
Camera, Character & Controller 3C (PlayerController, Physics, Camera, Actor States)references/system-3c.md
Effect & Feedback System (Screen Shake, VFX, Hit-Stop, Haptics, SFX, Floating Text, UI Feedback, Orchestration)references/system-effect-feedback.md
Narrative System (Dialogue, Cutscenes, Story Flow)references/system-narrative.md
Game AI System (Movement, Pathfinding, Decision Making, Tactical)references/system-game-ai.md
Mod & DLC System (Plugin Architecture, Config Database, Scripting, Hooks, Extensibility)references/system-mod.md
Procedural Content Generation (PCG) (World/Level Generation, Roguelike, Noise, Simulation)references/system-pcg.md
Algorithm & Data Structures (Pathfinding, Search, Physics, Generic Solver)references/algorithm.md
Puzzle Game System (Match-3, Jigsaw, Water Sort, Blocks, Physics Puzzles, Board Games, Content & Presentation Boundaries)references/system-puzzle.md

Multiplayer References

FocusReferenceUse When
Multiplayer overviewreferences/multiplayer-overview.mdDecide client/server responsibility, authority split, and gameplay sync style
Multiplayer protocol and connectionreferences/multiplayer-protocol.mdDesign messages, serialization, Req/Resp/Notify, heartbeat, reconnect
Multiplayer server architecturereferences/multiplayer-server-architecture.mdDesign ownership boundaries, process roles, deployment, persistence, recovery
Common server components and servicesreferences/multiplayer-implementation-common.mdBuild shared infrastructure such as auth, gateway, connector, db, cache, discovery, queue, observability
Room server build playbookreferences/multiplayer-implementation-room.mdBuild a concrete small-to-medium room-based realtime server with join flow, room ownership, settlement, reconnect
Encounter server build playbookreferences/multiplayer-implementation-encounter.mdBuild a concrete turn-based or combat-workflow server with checkpointing, idempotent actions, settlement
Persistent world server build playbookreferences/multiplayer-implementation-world.mdBuild a concrete AOI world server with region ownership, transfer, location registry, reconnect
Deterministic sync, lockstep, and rollbackreferences/multiplayer-deterministic-sync.mdDesign deterministic input-sync architectures, frame pipelines, rollback, replay, and desync handling

Paradigm Selection Guide

ParadigmKeyPointApplicability ScopeExamplesReference
Domain-Driven Design (DDD)OOP & Entity FirstHigh Rule Complexity. Rich Domain Concepts. Many Distinct Entities.Core Combat Logic, Physics Interactions, Damage/Buff Rules, Complex AI Decision.references/domain-driven-design.md
Data-Driven DesignData Layer FirstHigh Content Complexity. Flow Orchestration. Simple Data Management.Content: Quests, Level Design.Flow: Tutorial Flow, Skill Execution, Narrative.Mgmt: Inventory, Shop, Mail, Leaderboard.references/data-driven-design.md
Use-Case Driven PrototypeUse-Case Implementation FirstRapid ValidationGame Jam, Core Mechanic Testing.references/prototype-design.md

Here, Data-Driven Design means a data-structure-first programming paradigm, not specifically configuration-driven gameplay. See references/data-driven-design.md for the full terminology boundary.

Mixing Paradigms

Most projects mix paradigms:

  1. Macro Consistency: All modules follow the same Module Management Framework.
  2. Domain for Core Entities & Rules: Use DDD for systems with high rule complexity, rich domain concepts, and many distinct entities (e.g., Combat Actors, Damage Formulas, AI Decision).
  3. Data for Content, Flow & State: Use Data-Driven for expandable content (Quests, Level Design), flow orchestration (Tutorial, Skill Execution, Narrative), and simple data management (Inventory, Shop).
  4. Hybrid Paradigms:
    • 4.1 Entities as Data: Domain Entities naturally hold both data (fields) and behavior (methods). Design entities to be serialization-friendly (use IDs, keep state as plain fields) so they serve both roles without a separate data layer.
    • 4.2 Flow + Domain: Use data-driven flow to orchestrate the sequence/pipeline, domain logic to handle rules at each step. E.g., Skill System: flow drives cast→channel→apply, domain handles damage calc and buff interactions.
    • 4.3 Separate Data/Domain Layers: Only when edit-time and runtime representations truly diverge. Use a Bake/Compile step to bridge them. E.g., visual node-graph editors, compiled assets.
  5. Paradigm Interchangeability: Many systems can be validly implemented with either paradigm. E.g., Actor inheritance hierarchy (Domain) ↔ ECS components + systems (Data-Driven); Buff objects with encapsulated rules (Domain) ↔ Tag + Effect data entries resolved by a generic pipeline (Data-Driven). See Selection Criteria table above for trade-off signals.
  6. Integration: Application Layer bridges different paradigms.

Selection Criteria

When both DDD and Data-Driven fit, use these signals:

SignalFavor DDDFavor Data-Driven
Entity interactionsComplex multi-entity rules (attacker × defender × buffs × environment)Mostly CRUD + display, few cross-entity rules
Behavior sourceVaries by entity type, hard to express as pure dataDriven by config tables, designer-authored content
Change frequencyRules change with game balance iterationsContent/flow changes far more often than logic
Performance profileAcceptable overhead for rich object graphsNeeds batch processing, cache-friendly layouts
NetworkingStateful objects acceptableFlat state snapshots preferred (sync, rollback)
Team workflowProgrammers own the logicDesigners need to iterate without code changes

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Game Architect AI skill do?

READ this skill when designing or planning any game system architecture — including combat, skills, AI, UI, multiplayer, narrative, or scene systems. Contains paradigm selection guides (DDD / Data-Driven / Prototype), system-specific design references, and mixing strategies. Works as a domain knowledge plugin alongside workflow skills (OpenSpec, SpecKit) or plan mode of an agent.

Why use Game Architect on TypingMind?

Because you install it once and use it with any model. Game Architect is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Game Architect in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Yuki001/game-dev-skills/tree/main/skills/game-architect. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Game Architect?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Game Architect?

As many as you like. As long as a model supports skills, you can use Game Architect with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Game Architect AI skill free?

It is published on GitHub by Yuki001. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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