performance-profiling-plugins

performance profiling plugins

7,385 stars

Best use case

performance-profiling-plugins is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

performance profiling plugins

Teams using performance-profiling-plugins should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/performance-profiling-plugins/SKILL.md --create-dirs "https://raw.githubusercontent.com/kreuzberg-dev/kreuzberg/main/.ai-rulez/domains/plugin-system/skills/performance-profiling-plugins/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/performance-profiling-plugins/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How performance-profiling-plugins Compares

Feature / Agent	performance-profiling-plugins	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

performance profiling plugins

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

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SKILL.md Source

Profile plugin performance

1. Measure plugin registration time
2. Measure selection overhead
3. Measure plugin execution time
4. Profile GIL usage (for Python plugins):
   - GIL hold time
   - Frequency of acquisition
   - Release efficiency
5. Profile memory usage:
   - Plugin memory footprint
   - Data structure sizes
   - Cache sizes
6. Identify bottlenecks
7. Implement optimizations
8. Verify improvements

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