python-performance-optimization
Helps your agent optimize Python code performance. It identifies bottlenecks and improves application speed and memory usage.
What it does
This tool helps find and fix slow parts of your Python code. It analyzes how your program uses time and memory to make it faster and more efficient.
When to use it
- ✓Your Python program is taking too long to run.
- ✓You want your program to use less memory.
- ✓You need to speed up a specific part of your code.
Example of what to ask your AI
“How can I optimize my Python script that is very slow when processing data?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool uses techniques to measure the time and memory your Python code spends. Based on this data, it suggests ways to rewrite or adjust the code so it runs faster.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill python-performance-optimizationOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/python-performance-optimization/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Python Performance Optimization
Comprehensive guide to profiling, analyzing, and optimizing Python code for better performance, including CPU profiling, memory optimization, and implementation best practices.
Use this skill when
- Identifying performance bottlenecks in Python applications
- Reducing application latency and response times
- Optimizing CPU-intensive operations
- Reducing memory consumption and memory leaks
- Improving database query performance
- Optimizing I/O operations
- Speeding up data processing pipelines
- Implementing high-performance algorithms
- Profiling production applications
Do not use this skill when
- The task is unrelated to python performance optimization
- You need a different domain or tool outside this scope
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open
resources/implementation-playbook.md.
Resources
resources/implementation-playbook.mdfor detailed patterns and examples.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
FAQ
What is 'profiling'?
Profiling is like taking a snapshot of your program while it's running to see where it spends the most time and resources.
What are 'bottlenecks'?
Bottlenecks are the parts of your code that are causing slowness, like a narrow point in a pipe.
Do I need to be an expert programmer to use this?
No, this tool is designed to help even if you're not an experienced programmer. It focuses on making your code perform better.
Details
Original description by the author
Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.
Popularity
- GitHub stars
- 48k
- Ranking position
- #3936
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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