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Unity Performance

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Besty0728
unity-performance

Advise on Unity performance red flags

Overview

PublisherBesty0728
RepositoryUnity-Skills
Skill nameunity-performance
Stars
1.8K
Forks
164
Bundled files
Instructions only
LicenseMIT
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 Besty0728 on GitHub. Read the source before you install it.

Installation

Install the Unity Performance 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.
  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.

Use it in TypingMind

Enable Unity Performance 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 Performance 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 Performance 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.

Before calling any skill in this module: if you are about to call a skill with parameters guessed from its name or description, STOP — read this file (or fetch its schema via GET /skills/recommend?includeSchema=true) first. If you already have the parameter definitions from recommend/schema, you may proceed straight to dryRun.

Triggers

  • Reviewing performance
  • Diagnosing frame drops
  • Reducing allocations
  • Planning pooling/optimization
  • 做性能审查、诊断掉帧或卡顿、减少内存分配、规划对象池/优化

Unity Performance Red Flags

Use this skill for a high-signal review of likely Unity performance issues. Focus on red flags, not speculative micro-optimizations.

Check For

  • Too many unrelated Update / LateUpdate / FixedUpdate loops
  • Repeated Find, GetComponent, Camera.main, or tag lookups in hot paths
  • Frequent Instantiate / Destroy suitable for pooling
  • Avoidable per-frame allocations:
    • LINQ
    • string formatting
    • closures
    • boxing
  • Reflection in runtime hot paths
  • Expensive editor-only helpers leaking into runtime code
  • Physics, animation, or UI updates happening at the wrong cadence

Hidden Costs: Possibility ≠ Actuality

Three counter-intuitive traps where what seems "free" is actually expensive. Each cost is paid for possibility of work, not for work actually performed — which is why profilers rarely catch them directly.

Write permission costs, even without writing

A component whose Update can mutate transform.position pays the cost whether the branch runs or not: dirty-flag and serialization systems treat write permission as a reason to poll every frame. Similarly, a [SerializeField] field that is never modified at runtime still sits on the serialization path. The fix is to remove the permission, not tighten the branch — split the rarely-needed writer into its own component and AddComponent only when needed. Source: NetcodeSamples/HelloNetcode/2_Intermediate/07_Optimization/Optimization.md — "a system with the possibility of writing to a component, regardless of whether it writes to it or not, will always have to be serialized".

Sequential seeds produce correlated random streams

Seeding N RNG instances with baseSeed + i gives N similar streams — patrol paths line up, spawn jitter clumps, loot rolls cluster. Hash the index before seeding:

csharp
// Wrong — N correlated streams
for (int i = 0; i < N; i++) rngs[i] = new System.Random(baseSeed + i);

// Correct — hash decorrelates adjacent seeds
for (int i = 0; i < N; i++)
    rngs[i] = new System.Random((int)((uint)baseSeed * 2654435761u ^ (uint)i));

Unity.Mathematics.Random.CreateFromIndex(i) applies this internally and is preferred when the math package is available. Source: Dots101/Entities101/Assets/HelloCube/3. Prefabs/SpawnSystem.cs:37-39 and its comment.

Logging fires in release builds by default

Debug.Log is not stripped in Player builds; only methods marked [Conditional("UNITY_EDITOR")] (such as Debug.DrawLine) have their arguments elided at the call site. That means a log line with interpolation or helper calls runs every frame in shipped games:

csharp
// Wrong — GetPlayerInfo() and string interpolation execute in release
Debug.Log($"Player {GetPlayerInfo()} at {Time.time}");

// Better — guard the whole expression
if (Debug.isDebugBuild) Debug.Log($"Player {GetPlayerInfo()} at {Time.time}");

The same principle as the "possibility write" rule above — the runtime pays for the possibility of work, not only for the work.

Output Format

  • Confirmed red flags
  • Likely red flags
  • Changes worth doing now
  • Changes not worth doing now
  • Expected gain category: clarity / frame time / GC / scalability

Guardrails

Mode: Documentation only — no REST skills to gate; load freely under any operating mode (Approval / Auto / Bypass).

  • Do not recommend large refactors without a meaningful hotspot.
  • Do not replace simple code with unreadable “optimized” code unless the hot path is real.

Frequently asked questions

What does the Unity Performance AI skill do?

Advise on Unity performance red flags

Why use Unity Performance on TypingMind?

Because you install it once and use it with any model. Unity Performance 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 Performance in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Besty0728/Unity-Skills/tree/main/SkillsForUnity/unity-skills~/skills/performance. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Unity Performance?

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 Performance?

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

Is the Unity Performance AI skill free?

Yes. It is published on GitHub by Besty0728 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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