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Review Codebase

Checked
nesnilnehc·vlatest·backend·MIT

Analyzes codebase quality, identifies potential bugs, and suggests improvements based on best practices.

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-codebase -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.

Scanned
2 files, 202 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

The review-codebase skill analyzes a codebase and provides summaries of its structure, dependencies, and potential areas for improvement. It can identify common code smells, suggest refactoring opportunities, and generate documentation based on the existing code. This helps developers quickly understand unfamiliar projects or improve the quality of their own work.

When to use it

  • Onboarding new team members: Quickly familiarize them with a large or complex codebase.
  • Code review preparation: Generate an initial assessment before a manual code review begins.
  • Refactoring planning: Identify areas in the codebase ripe for refactoring and potential improvements.
  • Documentation generation: Automatically create basic documentation from existing code comments and structure.

Key capabilities

  • Codebase summarization
  • Dependency analysis
  • Identification of code smells
  • Refactoring suggestions
  • Documentation generation

Example prompts

  • "Summarize the architecture of this Python project."
  • "Identify potential performance bottlenecks in this JavaScript codebase."
  • "Generate documentation for the 'user authentication' module in this Go repository."

Tips & gotchas

The quality of the analysis depends heavily on code comments and consistent coding style. For best results, provide a well-structured and documented codebase.