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Python Performance Optimization

Checked
spjoshis·vlatest·backend

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 spjoshis/claude-code-plugins --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

spjoshis

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 spjoshis/claude-code-plugins at ddcf16ef7b.

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

Commit
ddcf16ef7b
Manifest
plugins/python-development/skills/python-performance-optimization/SKILL.md
Scanned
1 file, 819 lines
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 analyzes Python code and provides recommendations for performance optimization. It identifies bottlenecks, suggests algorithmic improvements, and offers strategies to reduce execution time and resource consumption. The agent can also suggest appropriate data structures and libraries to enhance efficiency.

When to use it

  • You have a slow-running Python script that needs to be sped up.
  • You are experiencing performance issues in a web application or API built with Python.
  • You want to profile your code to understand where the most time is being spent.
  • You're using inefficient data structures and algorithms that impact overall speed.

Key capabilities

  • Code analysis for performance bottlenecks
  • Algorithmic optimization suggestions
  • Data structure recommendations
  • Library selection guidance

Example prompts

  • "Analyze this Python code for performance issues: [code snippet]"
  • "How can I optimize the runtime of this function? [function definition]"
  • "Suggest a more efficient data structure to store and process this dataset."

Tips & gotchas

The skill's effectiveness depends on providing clear, concise code snippets. Complex or obfuscated code may yield less accurate optimization suggestions.