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Requesting Code Review

Listed
sickn33·vlatest·backend·MIT

Automates code review requests from pull requests, flagging potential issues based on sickn33's established coding 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 sickn33/agentic-awesome-skills --skill requesting-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

sickn33

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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 sickn33/antigravity-awesome-skills at 5a4cdd9df8.

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

Commit
5a4cdd9df8
Manifest
skills/requesting-code-review/SKILL.md
Scanned
0 files
Copies in repo
3 — all of them scanned
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 an AI agent to request code reviews from developers or peers, ensuring that code is evaluated for quality, correctness, and adherence to best practices. It can generate review requests with context, such as the purpose of the code, specific areas of concern, or desired feedback types.

When to use it

  • Before merging a pull request in a collaborative development environment.
  • When seeking input on complex logic or edge cases in a codebase.
  • To ensure compliance with team coding standards or style guides.
  • When preparing for a code review meeting and need structured feedback from peers.

Key capabilities

  • Generate clear, concise code review requests.
  • Include relevant context such as code snippets or repository links.
  • Specify the type of feedback desired (e.g., performance, readability).
  • Format messages to be used in issue trackers or communication platforms.

Example prompts

  • "Request a code review for the auth module in the main branch. Focus on security and error handling."
  • "Generate a message asking for feedback on my new feature implementation in the feature/user-profile branch."
  • "Write a code review request that includes the pull request link, highlights of changes, and asks for testing suggestions."

Tips & gotchas

  • Ensure the AI agent has access to repository details or context about the code being reviewed.
  • Avoid overly vague requests; specify what kind of feedback is needed for better results.