Python Quality Checker
CheckedAnalyzes 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
Run this in your project
terminal$ npx skills add matteocervelli/llms --skill python-quality-checker --full-depth -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto 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.
Automated safety checks
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.
- Commit
- 1e1f2089eb
- Scanned
- 1 file, 673 lines
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.