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Code Review

Checked
jwynia·vlatest·backend

Automates Python/Django code reviews, identifying potential bugs, style issues, and security vulnerabilities for improved backend quality.

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 jwynia/agent-skills --skill code-review --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

jwynia

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 jwynia/agent-skills at e02ec7e226.

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

Commit
e02ec7e226
Manifest
skills/tech/development/quality/code-review/SKILL.md
Scanned
1 file, 230 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 enables AI agents to perform automated code reviews, analyzing source code for bugs, security vulnerabilities, and adherence to coding standards. It provides immediate feedback on pull requests or standalone files to improve software quality before deployment.

When to use it

  • Before merging a pull request in a collaborative development environment.
  • When integrating new libraries or dependencies into an existing backend service.
  • To enforce consistent style guides and architectural patterns across a codebase.
  • During the initial review of critical security patches or sensitive data handling logic.

Key capabilities

  • Automated analysis of code for potential errors and vulnerabilities.
  • Evaluation against defined coding standards and best practices.
  • Identification of security flaws within backend logic.
  • Generation of actionable feedback reports for developers.

Example prompts

  • "Review this pull request and list any security vulnerabilities you find in the authentication module."
  • "Analyze the provided Python script for compliance with our internal style guide and suggest refactoring improvements."
  • "Perform a code review on this new API endpoint implementation to check for potential race conditions or memory leaks."

Tips & gotchas

Ensure the AI agent has access to the full context of the codebase, including related files and configuration, to provide accurate security assessments. This skill is most effective when used as part of a broader CI/CD pipeline rather than as a standalone final check.