Skip to content
TrustedSkillsbeta
Back to all skills

Code Review Playbook

Checked
yonatangross·vlatest·backend·MIT

Automates backend code reviews using Yonatan Gross's playbook, ensuring consistency and catching common errors efficiently.

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 yonatangross/orchestkit --skill code-review-playbook -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

yonatangross

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 yonatangross/orchestkit at 7784b90c05.

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

Commit
7784b90c05
Manifest
src/skills/code-review-playbook/SKILL.md
Scanned
2 files, 458 lines
Copies in repo
2 — 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

The code-review-playbook skill provides a structured framework for AI agents to conduct comprehensive code reviews, focusing on security vulnerabilities, architectural consistency, and adherence to best practices. It transforms raw code submissions into actionable feedback by systematically analyzing logic flow, dependency management, and maintainability standards.

When to use it

  • Before merging pull requests in backend repositories to catch critical bugs early.
  • When integrating new team members who need guidance on project-specific coding conventions.
  • During refactoring efforts to ensure legacy code remains secure and performant.
  • To validate that third-party library implementations follow the project's security policies.

Key capabilities

  • Automated detection of common security vulnerabilities and anti-patterns.
  • Analysis of architectural alignment with established backend design principles.
  • Generation of prioritized feedback lists distinguishing between critical, major, and minor issues.
  • Context-aware suggestions for improving code readability and testability.

Example prompts

  • "Review this Python service implementation against our security playbook and list any potential injection risks."
  • "Act as a senior backend engineer and critique the database migration script for performance bottlenecks."
  • "Generate a checklist of improvements for this API controller based on standard code review guidelines."

Tips & gotchas

Ensure you provide the full context of the project's architecture or specific style guide, as the skill relies on these details to offer precise recommendations. While effective at identifying standard issues, it may require human oversight for complex architectural decisions involving business logic nuances.