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Performance Profiling

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vudovn
performance-profiling

Performance profiling principles. Measurement, analysis, and optimization techniques.

Overview

Publishervudovn
Repositoryag-kit
Skill nameperformance-profiling
Stars
8.2K
Forks
1.5K
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Performance Profiling 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/vudovn/ag-kit/tree/main/.agents/skills/performance-profiling
  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/vudovn/ag-kit.git /tmp/ag-kit
mkdir -p .claude/skills
cp -r /tmp/ag-kit/.agents/skills/performance-profiling .claude/skills/performance-profiling
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Performance Profiling 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 Profiling 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 Profiling 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 Profiling

Measure, analyze, optimize - in that order.

🔧 Runtime Scripts

Execute these for automated profiling:

ScriptPurposeUsage
scripts/lighthouse_audit.pyLighthouse performance auditpython scripts/lighthouse_audit.py https://example.com

1. Core Web Vitals

Targets

MetricGoodPoorMeasures
LCP< 2.5s> 4.0sLoading
INP< 200ms> 500msInteractivity
CLS< 0.1> 0.25Stability

When to Measure

StageTool
DevelopmentLocal Lighthouse
CI/CDLighthouse CI
ProductionRUM (Real User Monitoring)

2. Profiling Workflow

The 4-Step Process

1. BASELINE → Measure current state
2. IDENTIFY → Find the bottleneck
3. FIX → Make targeted change
4. VALIDATE → Confirm improvement

Profiling Tool Selection

ProblemTool
Page loadLighthouse
Bundle sizeBundle analyzer
RuntimeDevTools Performance
MemoryDevTools Memory
NetworkDevTools Network

3. Bundle Analysis

What to Look For

IssueIndicator
Large dependenciesTop of bundle
Duplicate codeMultiple chunks
Unused codeLow coverage
Missing splitsSingle large chunk

Optimization Actions

FindingAction
Big libraryImport specific modules
Duplicate depsDedupe, update versions
Route in mainCode split
Unused exportsTree shake

4. Runtime Profiling

Performance Tab Analysis

PatternMeaning
Long tasks (>50ms)UI blocking
Many small tasksPossible batching opportunity
Layout/paintRendering bottleneck
ScriptJavaScript execution

Memory Tab Analysis

PatternMeaning
Growing heapPossible leak
Large retainedCheck references
Detached DOMNot cleaned up

5. Common Bottlenecks

By Symptom

SymptomLikely Cause
Slow initial loadLarge JS, render blocking
Slow interactionsHeavy event handlers
Jank during scrollLayout thrashing
Growing memoryLeaks, retained refs

6. Quick Win Priorities

PriorityActionImpact
1Enable compressionHigh
2Lazy load imagesHigh
3Code split routesHigh
4Cache static assetsMedium
5Optimize imagesMedium

7. Anti-Patterns

❌ Don't✅ Do
Guess at problemsProfile first
Micro-optimizeFix biggest issue
Optimize earlyOptimize when needed
Ignore real usersUse RUM data

Remember: The fastest code is code that doesn't run. Remove before optimizing.

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 Profiling AI skill do?

Performance profiling principles. Measurement, analysis, and optimization techniques.

Why use Performance Profiling on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vudovn/ag-kit/tree/main/.agents/skills/performance-profiling. 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 Profiling?

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 Profiling?

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

Is the Performance Profiling AI skill free?

Yes. It is published on GitHub by vudovn 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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