Review Game

Organization

PlayableIntelligence

review-game

Review an existing game codebase for architecture, performance, and best practices. Use when the user says "review my game", "code review", "check my game architecture", "is my game well structured", or "audit my game code". Do NOT use for making changes — this is read-only analysis. Use improve-game to implement fixes.

Overview

Publisher	PlayableIntelligence
Repository	`game-creator`
Skill name	`review-game`
Stars	331
Forks	41
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by PlayableIntelligence on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/PlayableIntelligence/game-creator.git /tmp/game-creator
mkdir -p .claude/skills
cp -r /tmp/game-creator/skills/review-game .claude/skills/review-game

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Review Game 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 Review Game 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 Review Game 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.

Performance Notes

Take your time to do this thoroughly
Quality is more important than speed
Do not skip validation steps

Review Game

Analyze an existing game codebase and provide a structured review. This is the final step in the pipeline — it checks everything is wired up correctly and gives you a quality score.

Instructions

Analyze the game at $ARGUMENTS (or the current directory if no path given).

Step 1: Identify the game

Detect the engine (Three.js, Phaser, or other)
Read package.json for dependencies and scripts
Read the main entry point and index.html
Identify the game concept/genre

Step 2: Architecture Review

Check for these required patterns and report compliance:

EventBus: Is there a centralized event system? Are modules decoupled?
GameState: Is there a centralized state singleton?
Constants: Are config values centralized or scattered as magic numbers?
Orchestrator: Is there a main Game class that initializes everything?
Directory Structure: Is code organized into core/systems/gameplay/ui/level layers?
Event Constants: Are events defined as named constants or raw strings?

Step 3: Performance Review

Check for common issues:

Delta time capping: Is getDelta() capped to prevent death spirals?
Object pooling: Are temp objects reused in hot loops?
Resource disposal: Are Three.js geometries/materials/textures disposed?
Event cleanup: Are event listeners cleaned up on scene transitions?
Asset loading: Are assets preloaded with progress feedback?

Step 4: Code Quality

No circular dependencies: Modules flow one direction
Single responsibility: Each module has one clear job
Error handling: Event handlers wrapped in try/catch
Consistent naming: Events use domain:action, files use PascalCase

Step 5: Monetization Readiness

Points system: Is there a scoring/points mechanism?
Session tracking: Can game sessions be identified?
Anti-cheat potential: Is score validation server-side or at least structured for it?
Play.fun integration: Any existing SDK integration?

Output Format

Provide a structured report with:

Game Overview - What the game is, tech stack, game loop
Architecture Score (out of 6 checks)
Performance Score (out of 5 checks)
Code Quality Score (out of 4 checks)
Monetization Readiness (out of 4 checks)
Top Recommendations - Prioritized list of improvements with plain-English explanations
What's Working Well - Positive findings

Example Usage


/review-game examples/flappy-bird

Result: Architecture 6/6, Performance 4/5, Code Quality 4/4, Monetization 2/4 → Top recommendations: add Play.fun SDK, add object pooling for pipes, add delta time capping. Positive findings: clean EventBus usage, proper GameState reset, well-organized directory structure.

Next Step

Tell the user:

Your game has been through the full pipeline! Here's what you have:

Scaffolded architecture (/viral-game)

Visual polish (/design-game)

Music and sound effects (/add-audio)

Automated tests (/qa-game)

Architecture review (/review-game)

(Reflects the /viral-game one-shot pipeline. If you're working through /make-game, the equivalent state is "post-scaffold-phase + first development milestone shipped".)

What's next?

Add new gameplay features with /game-creator:add-feature [description]

Deploy to the web — run npm run build && ~/.agents/skills/here-now/scripts/publish.sh dist/ for instant hosting, or use GitHub Pages, Vercel, Netlify, itch.io

Keep iterating! Run /design-game, /add-audio, or /review-game again anytime after making changes.

Frequently asked questions

What does the Review Game AI skill do?

Why use Review Game on TypingMind?

Because you install it once and use it with any model. Review Game 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 Review Game in TypingMind?

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

Which AI models can use Review Game?

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 Review Game?

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

Is the Review Game AI skill free?

Yes. It is published on GitHub by PlayableIntelligence under the MIT license. 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Performance Notes

Review Game

Instructions

Step 1: Identify the game

Step 2: Architecture Review

Step 3: Performance Review

Step 4: Code Quality

Step 5: Monetization Readiness

Output Format

Example Usage

Next Step

Frequently asked questions

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