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Code Review

Checked
alinaqi·vlatest·backend·MIT

Automates Python/Node.js backend code reviews, identifying bugs, style issues, and suggesting performance improvements.

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 alinaqi/maggy --skill code-review -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

alinaqi

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 alinaqi/maggy at 72a456e6cc.

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

Commit
72a456e6cc
Manifest
skills/code-review/SKILL.md
Scanned
2 files, 1,193 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 submitted code for quality, adherence to best practices, and potential security vulnerabilities. It provides immediate feedback to developers by highlighting issues and suggesting improvements directly within the development workflow.

When to use it

  • Before merging a pull request to ensure all changes meet project standards.
  • During initial code implementation to catch logical errors or style inconsistencies early.
  • When onboarding new team members to enforce consistent coding conventions across the codebase.
  • For security audits to identify common vulnerabilities like SQL injection or hardcoded credentials.

Key capabilities

  • Automated analysis of code quality and maintainability.
  • Detection of security flaws and vulnerability patterns.
  • Enforcement of specific coding style guides and best practices.
  • Generation of actionable feedback and refactoring suggestions.

Example prompts

  • "Review this Python function for performance bottlenecks and security issues."
  • "Analyze the provided JavaScript code snippet against our team's ESLint rules and suggest fixes."
  • "Perform a pre-merge review on this commit to check for logic errors and missing error handling."

Tips & gotchas

Ensure your AI agent has access to the full context of the project's existing style guide or configuration files (e.g., .eslintrc, pyproject.toml) for accurate reviews. While the skill identifies many issues, complex architectural decisions may still require human oversight.