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Python Performance Optimization

Checked
acaprino·vlatest·backend·MIT

Helps with Python, performance optimization, optimization as part of developing backend services and APIs workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add acaprino/daodan --skill python-performance-optimization -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

acaprino

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned acaprino/alfio-claude-plugins at 10363691a2.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
10363691a2
Manifest
exports/pi/plugins/python-development/skills/python-performance-optimization/SKILL.md
Scanned
6 files, 987 lines
Copies in repo
3 — all of them scanned
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill optimizes Python code for improved performance. It analyzes existing Python scripts and suggests changes to reduce execution time and resource consumption, focusing on areas like algorithm efficiency and memory usage. The tool aims to provide practical recommendations that developers can implement directly into their projects.

When to use it

  • Slow Scripts: When a Python script takes an unexpectedly long time to run.
  • Resource Intensive Tasks: For scripts that consume excessive CPU or memory resources.
  • Performance Bottlenecks: To identify and address specific areas within code causing performance slowdowns.
  • Code Refactoring: During code refactoring efforts, to ensure performance improvements are maintained.

Key capabilities

  • Python code analysis
  • Performance bottleneck identification
  • Algorithm efficiency suggestions
  • Memory usage optimization recommendations

Example prompts

  • "Analyze this Python script and suggest ways to improve its speed: [script content]"
  • "I have a slow data processing script. Can you identify the performance bottlenecks?"
  • "Optimize this function for memory usage: [function code]"

Tips & gotchas

The skill's effectiveness depends on the complexity of the Python code provided; very large or highly optimized projects may yield less impactful suggestions. Ensure the provided code is complete and representative of the problem area being addressed.