Unity Clean Architecture Review logo

Unity Clean Architecture Review

Community
MinhLN1234
unity-clean-architecture-review

Review Unity C# code for Clean Architecture and SOLID compliance, with specific attention to the separation between MonoBehaviour/presentation, plain-C# domain logic, and Unity/infrastructure concerns. Use this whenever the user asks to review, audit, or sanity-check a script or system before merging it, asks "is this code clean?", flags tight coupling or untestable code, or wants a second opinion on how a new gameplay system should be structured. Also trigger proactively when a user pastes a new MonoBehaviour and asks for feedback, even if they don't say "architecture" or "SOLID" explicitly.

Overview

PublisherMinhLN1234
RepositoryClaude-Cowork-Game-Studio
Skill nameunity-clean-architecture-review
Stars
79
Forks
31
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by MinhLN1234 on GitHub. Read the source before you install it.

Installation

Install the Unity Clean Architecture Review 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/MinhLN1234/Claude-Cowork-Game-Studio/tree/master/unity-clean-architecture-review
  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/MinhLN1234/Claude-Cowork-Game-Studio.git /tmp/Claude-Cowork-Game-Studio
mkdir -p .claude/skills
cp -r /tmp/Claude-Cowork-Game-Studio/unity-clean-architecture-review .claude/skills/unity-clean-architecture-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Unity Clean Architecture Review 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 Unity Clean Architecture Review 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 Unity Clean Architecture Review 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.

Unity Clean Architecture Review

Many Unity projects deliberately separate game logic from Unity's engine plumbing (often in a dedicated Core/, Domain/, or named framework folder). The point of that separation: gameplay rules (health math, cooldown/reset logic, spawn timing) should be testable and reasoned-about without booting the Unity engine, and should not silently drift from the values documented in the design docs. A review against this skill is checking whether a piece of code preserves that separation, not just whether it "looks clean."

Before reviewing: look, don't assume

Read the actual code in the project first — how do existing systems separate domain logic from MonoBehaviour glue? Detect where this project keeps its engine-independent logic (it may be a Core/, Domain/, Gameplay/, or a named framework folder) and where its scene-facing scripts live. Conventions in a given codebase may not match textbook Clean Architecture layer names — infer the existing pattern from what's already there and review the new code against that, not against an abstract ideal. If the project has no such separation at all, say so and review against general SOLID principles instead.

What to check

Dependency direction. Domain/logic classes (health, cooldowns, scoring, spawn rules) should not reference UnityEngine types they don't need (no Update(), no GameObject, no Transform inside pure rule logic). If a class needs engine services, it should receive them through an interface or a thin wrapper, not call FindObjectOfType, GameObject.Find, or static engine state directly from inside logic that's supposed to be testable.

Single Responsibility. A MonoBehaviour that reads input, mutates health, plays VFX, and updates the camera in one method is doing too much. Flag where these should split — input/presentation vs. rule evaluation vs. side effects (audio, VFX, camera).

Testability. Can this class's core behavior be exercised in an EditMode test without a scene? If not, identify exactly what's blocking that (singleton access, coroutine-only logic, hidden Time.deltaTime calls) and suggest the smallest change that would unblock it — don't propose a full rewrite for a one-line fix.

Interface segregation / coupling. Does this script depend on a fat manager class when it only needs one or two methods from it? Tight coupling here is usually what causes rule values to drift between code and docs — when logic is scattered and tangled, it's harder to find every place a rule lives.

Consistency with design docs. If the code implements a numeric rule (health thresholds, cooldown/reset timing, transition type, spawn/wave activation), cross-check the value against the project's design docs (GDD, project bible, or whatever spec the project keeps). A clean-architecture violation and a doc-drift bug often show up in the same review — flag both. If the project keeps no such docs, skip this check and note that.

Output format

Structure findings as:

## Summary
[1-2 sentences: is this in good shape, needs minor cleanup, or needs restructuring?]

## Findings
- [File:line or method name] — [issue] — [why it matters] — [concrete suggested fix]

## Doc consistency
[Any numeric/rule values that should be cross-checked against design docs, or confirmation none were found / no docs exist]

Keep suggested fixes concrete and minimal — point at the smallest change that fixes the issue rather than redesigning the whole class, unless the user asks for a bigger refactor.

Frequently asked questions

What does the Unity Clean Architecture Review AI skill do?

Review Unity C# code for Clean Architecture and SOLID compliance, with specific attention to the separation between MonoBehaviour/presentation, plain-C# domain logic, and Unity/infrastructure concerns. Use this whenever the user asks to review, audit, or sanity-check a script or system before merging it, asks "is this code clean?", flags tight coupling or untestable code, or wants a second opinion on how a new gameplay system should be structured. Also trigger proactively when a user pastes a new MonoBehaviour and asks for feedback, even if they don't say "architecture" or "SOLID" explicitly.

Why use Unity Clean Architecture Review on TypingMind?

Because you install it once and use it with any model. Unity Clean Architecture Review 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 Unity Clean Architecture Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MinhLN1234/Claude-Cowork-Game-Studio/tree/master/unity-clean-architecture-review. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Unity Clean Architecture Review?

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 Unity Clean Architecture Review?

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

Is the Unity Clean Architecture Review AI skill free?

It is published on GitHub by MinhLN1234. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇