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Code Review

Checked
jwilger·vlatest·backend·CC0-1.0

Analyzes Python/Django backend code for style, potential bugs, and adherence to best practices using jwilger's established standards.

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 jwilger/agent-skills --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

jwilger

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 jwilger/agent-skills at e2f5e19add.

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

Commit
e2f5e19add
Manifest
skills/code-review/SKILL.md
Scanned
2 files, 403 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, style consistency, and potential logical errors. It acts as a peer reviewer within your development workflow, providing immediate feedback before code is merged or deployed.

When to use it

  • Before merging pull requests in a team environment to catch bugs early.
  • During solo development sessions to ensure code adheres to specific style guides.
  • When onboarding new developers to enforce consistent coding standards across the project.
  • To validate complex logic changes against existing architectural patterns.

Key capabilities

  • Automated analysis of code submissions for quality and correctness.
  • Detection of style inconsistencies and adherence to best practices.
  • Identification of potential logical errors or edge cases.
  • Context-aware feedback generation based on the specific codebase.

Example prompts

  • "Review this pull request and list any critical bugs or security vulnerabilities you find."
  • "Analyze the new API endpoint implementation for performance bottlenecks and suggest optimizations."
  • "Check if this function adheres to our team's naming conventions and error handling standards."

Tips & gotchas

Ensure the AI agent has access to the full context of the repository or relevant documentation to provide accurate reviews. While powerful, always verify critical security findings with a human expert before finalizing changes.