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Performance

Community
daveebbelaar
performance

Make a macOS app fast by measuring hangs, stutter, CPU, memory, and energy, then moving work off the main thread and onto the GPU. Use when the app freezes, a shortcut feels slow, dragging stutters, the fan spins, memory grows, or the user asks to optimize or profile.

Overview

Publisherdaveebbelaar
Repositorybama
Skill nameperformance
Stars
952
Forks
136
Bundled files
3
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the 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.
    https://github.com/daveebbelaar/bama/tree/main/skills/code/performance
  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/daveebbelaar/bama.git /tmp/bama
mkdir -p .claude/skills
cp -r /tmp/bama/skills/code/performance .claude/skills/performance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 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 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 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.

Performance

Fast means two numbers: the first frame after a key press shows in under 100 ms, and nothing on the main thread blocks for more than 50 ms. Every change in this skill starts and ends with a measurement, so you know it helped. Symptom-by-symptom fixes are in recipes.md. For video, audio, camera, Metal, or large image pipelines, also read gpu-media.md.

The loop

text
reproduce -> measure (release build) -> find the line -> fix -> measure again -> commit with the numbers
  1. Reproduce. Write the exact steps, or add a probe command to the debug bridge (test-mac-app skill) that runs the slow action and logs the time of each step.

  2. Measure the release build. Debug Swift is 3 to 10 times slower and points at the wrong code.

  3. Find the line. Pick the tool for the symptom:

    SymptomTool
    App freezes, spinning pointersample <App> 5, then read the main thread stack
    Slow actionTime Profiler: xcrun xctrace record --template 'Time Profiler' --attach <App> --time-limit 10s
    Short freezes while typing or dragging--template 'Hangs'
    Stutter while moving or animating--template 'Animation Hitches'
    Memory growsfootprint <App>, leaks <App>, --template 'Allocations'
    Fan, battery--template 'Energy Log', look for timers and polling

    Read traces as text, not in the Instruments GUI: see "Measuring" in recipes.md. Delete every .trace after reading. A trace stores the app's full environment, and an app opened from an agent's shell inherits that shell's tokens. Never commit or share one.

  4. Fix with the matching recipe.

  5. Measure again with the same steps. Put before and after in the commit message: "Picker opens in 40 ms, was 600 ms".

The rules that fix most problems

  • Main thread does UI only. File, network, database, image decoding, Accessibility calls, and audio go elsewhere. A main-thread call that waits on another process (CoreAudio, AX) can freeze the app for minutes.
  • Show first, work after. Put the window or panel on screen in the same frame as the key press, then load. Never make the UI wait for the work.
  • Let the GPU composite. Large images go in a CALayer once. Pointer movement changes only small layers. Never redraw a full-screen picture per mouse event.
  • Decode at display size. ImageIO thumbnails, cached in NSCache.
  • Do not animate what must be fast. Search results and switchers update in place.
  • No polling without a reason. Timers get a tolerance and stop when nothing on screen needs them.

Apple silicon notes

  • Core Animation, Core Image (one shared CIContext), Vision, and AVFoundation already run on the GPU or the Neural Engine. Hand them the work instead of looping over pixels in Swift.
  • Write Metal (MTKView, compute shaders) only when a measurement shows Core Animation or Core Image is too slow. Most apps never need it.
  • Unified memory means a CGImage from ScreenCaptureKit passes to a layer without a copy. Keep it as a CGImage or IOSurface. Converting to NSImage and back costs copies.

Done when the slow action has a measured before and after, the after meets the two numbers at the top, and the commit message names both.

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 Performance AI skill do?

Make a macOS app fast by measuring hangs, stutter, CPU, memory, and energy, then moving work off the main thread and onto the GPU. Use when the app freezes, a shortcut feels slow, dragging stutters, the fan spins, memory grows, or the user asks to optimize or profile.

Why use Performance on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/daveebbelaar/bama/tree/main/skills/code/performance. 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 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 Performance?

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

Is the Performance AI skill free?

Yes. It is published on GitHub by daveebbelaar 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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