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Review Python

Checked
nesnilnehc·vlatest·backend·MIT

Helps with code review, Python 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 nesnilnehc/ai-cortex --skill review-python -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

nesnilnehc

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 nesnilnehc/ai-cortex at 3d3325ab58.

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

Commit
3d3325ab58
Manifest
skills/review-python/SKILL.md
Scanned
2 files, 208 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 allows an AI agent to review and provide feedback on Python code. It can identify potential errors, suggest improvements in style or efficiency, and explain complex code snippets in simpler terms. The skill is designed for both novice and experienced programmers seeking assistance with their Python projects.

When to use it

  • Code Review: Have the AI agent analyze a block of Python code you've written before submitting it for formal review.
  • Debugging Assistance: Paste error messages or problematic code snippets to get suggestions on how to fix them.
  • Learning and Understanding: Ask the agent to explain unfamiliar Python code or concepts.
  • Style Improvement: Request feedback on code style and adherence to PEP 8 guidelines.

Key capabilities

  • Code analysis for errors
  • Suggestion of improvements in efficiency
  • Explanation of complex code snippets
  • PEP 8 compliance checks

Example prompts

  • "Review this Python function and suggest any improvements: [paste code]"
  • "Explain what this Python code does: [paste code]"
  • "Check this Python script for PEP 8 style violations: [paste code]"

Tips & gotchas

The quality of the review depends heavily on the clarity and completeness of the provided code. Ensure that any necessary imports or dependencies are included when submitting code for analysis.