Skip to content
TrustedSkillsbeta
Back to all skills

Python Quality Checker

Checked
matteocervelli·vlatest·backend·MIT

Analyzes Python code for style, errors, and potential improvements using established quality standards like PEP 8.

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 matteocervelli/llms --skill python-quality-checker --full-depth -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

matteocervelli

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 matteocervelli/llms at 1e1f2089eb.

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

Scanned
1 file, 673 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 feedback on its quality, identifying potential issues and suggesting improvements. It leverages static analysis tools to check for style violations (PEP 8), common errors, and adherence to best practices. The goal is to help developers write cleaner, more maintainable, and robust Python code.

When to use it

  • Code Review: Automatically assess the quality of a pull request before merging into a main branch.
  • Automated Linting: Integrate into a CI/CD pipeline to enforce coding standards across a project.
  • Learning & Improvement: New developers can use it to understand and correct common Python code style issues.
  • Refactoring: Identify areas in existing code that could benefit from improvements based on quality checks.

Key capabilities

  • PEP 8 compliance checking
  • Error detection
  • Code style suggestions
  • Static analysis

Example prompts

  • "Check the quality of this Python code: [paste code here]"
  • "Analyze this file for PEP 8 violations: /path/to/my_script.py"
  • "Can you find any potential errors in this function? [paste function definition]"

Tips & gotchas

The skill requires a Python environment to be available and configured correctly. Ensure the necessary dependencies are installed before using it, as specific linters or analysis tools might need to be present.