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Receiving Code Review

Checked
guanyang·vlatest·backend·MIT

Guanyang's code review agent automatically checks pull requests for style, errors, and potential bugs based on 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 guanyang/open-agent-hub --skill receiving-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

guanyang

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 guanyang/antigravity-skills at 0d6f1e7d3f.

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

Commit
0d6f1e7d3f
Manifest
skills/receiving-code-review/SKILL.md
Scanned
1 file, 182 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 accept incoming code reviews, allowing them to process feedback and integrate suggestions directly into their development workflow. It streamlines the collaboration loop between human reviewers and automated agents by handling review ingestion systematically.

When to use it

  • You need an agent to automatically analyze pull requests or merged code changes submitted by team members.
  • Your workflow requires immediate integration of peer review comments into the codebase without manual intervention.
  • You are building a continuous integration pipeline where feedback loops must be closed instantly after a review is posted.
  • You want to ensure no critical security or logic flaws identified in reviews are overlooked during automated deployments.

Key capabilities

  • Ingests structured and unstructured code review comments from various platforms.
  • Parses reviewer suggestions to identify specific lines of code requiring modification.
  • Triggers subsequent actions such as refactoring, testing, or re-committing based on review content.

Example prompts

  • "Review the latest pull request for the authentication module and apply all 'must-fix' security comments."
  • "Accept the code review feedback regarding memory leaks in the data processing function and update the implementation."
  • "Process the batch of code reviews from yesterday's sprint and generate a summary of changes made based on reviewer input."

Tips & gotchas

Ensure your AI agent has read permissions for the repository where reviews occur to successfully ingest feedback. This skill is most effective when combined with automated testing suites to validate that review suggestions do not break existing functionality before applying them.