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Code Review Playbook

Community
yonatangross
code-review-playbook

Structured review processes, conventional comments, language-specific checklists, and feedback templates. Use when reviewing PRs, conducting code review, or standardizing review practice.

Overview

Publisheryonatangross
Repositoryorchestkit
Skill namecode-review-playbook
Stars
298
Forks
35
Bundled files
16
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 16 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by yonatangross on GitHub. Read the source before you install it.

Installation

Install the Code Review Playbook AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/yonatangross/orchestkit/tree/main/plugins/ork/skills/code-review-playbook
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yonatangross/orchestkit.git /tmp/orchestkit
mkdir -p .claude/skills
cp -r /tmp/orchestkit/plugins/ork/skills/code-review-playbook .claude/skills/code-review-playbook
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Review Playbook in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Code Review Playbook on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Code Review Playbook is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Code Review Playbook

This skill provides a comprehensive framework for effective code reviews that improve code quality, share knowledge, and foster collaboration. Whether you're a reviewer giving feedback or an author preparing code for review, this playbook ensures reviews are thorough, consistent, and constructive.

Overview

  • Reviewing pull requests or merge requests
  • Preparing code for review (self-review)
  • Establishing code review standards for teams
  • Training new developers on review best practices
  • Resolving disagreements about code quality
  • Improving review processes and efficiency

Upstream coverage (do not restate)

This skill is a thin wrapper. General review craft is documented first-party elsewhere; only OrchestKit's own decisions live here. Load Read("references/ork-delta.md") for the house rules that survived the retired files.

TopicGo here instead
Review philosophy, speed, tone, PR sizinghttps://google.github.io/eng-practices/review/
Conventional comment labels and decorationsreferences/conventional-comments.md, https://conventionalcomments.org/
OWASP Top 10 review checksrules/security-baseline.md, https://owasp.org/Top10/
Generic language and framework review checklistsrules/typescript-quality.md, rules/python-quality.md, rules/linting-biome-rules.md
Review report shape and multi-agent full-PR reviework:review-pr
Applying findings to the working tree/code-review --fix, /simplify (see below)
Security-only pass over the current branch/security-review
GitHub review mechanics (approve, request changes, inline comments)https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/reviewing-changes-in-pull-requests

Conventional Comments

issue [blocking]: Missing error handling for API call
If the API returns a 500 error, this will crash. Add try/catch.

security [blocking]: API endpoint is not authenticated
The /api/admin/users endpoint is missing auth middleware.

Load Read("references/conventional-comments.md") for the full format, labels (praise, nitpick, suggestion, issue, question, security, bug, breaking), decorations ([blocking], [non-blocking], [if-minor]), and examples.


Review Process

1. Before Reviewing

Check Context:

  • Read the PR/MR description
  • Understand the purpose and scope
  • Review linked tickets or issues
  • Check CI/CD pipeline status

Verify Automated Checks:

  • Tests are passing
  • Linting has no errors
  • Type checking passes
  • Code coverage meets targets
  • No merge conflicts

Set Aside Time:

  • Small PR (< 200 lines): 15-30 minutes
  • Medium PR (200-500 lines): 30-60 minutes
  • Large PR (> 500 lines): 1-2 hours (or ask to split)

2. During Review

Follow a Pattern:

  1. High-Level Review (5-10 minutes)

    • Read PR description and understand intent
    • Skim all changed files to get overview
    • Verify approach makes sense architecturally
    • Check that changes align with stated purpose
  2. Detailed Review (20-45 minutes)

    • Line-by-line code review
    • Check logic, edge cases, error handling
    • Verify tests cover new code
    • Look for security vulnerabilities
    • Ensure code follows team conventions
  3. Testing Considerations (5-10 minutes)

    • Are tests comprehensive?
    • Do tests test the right things?
    • Are edge cases covered?
    • Is test data realistic?
  4. Documentation Check (5 minutes)

    • Are complex sections commented?
    • Is public API documented?
    • Are breaking changes noted?
    • Is README updated if needed?

3. After Reviewing

Provide Clear Decision:

  • ✅ Approve: Code is ready to merge
  • 💬 Comment: Feedback provided, no action required
  • 🔄 Request Changes: Issues must be addressed before merge

Respond to Author:

  • Answer questions promptly
  • Re-review after changes made
  • Approve when issues resolved
  • Thank author for addressing feedback

Review Checklists

General Code Quality

  • Readability: Code is easy to understand
  • Naming: Variables and functions have clear, descriptive names
  • Comments: Complex logic is explained
  • Formatting: Code follows team style guide
  • DRY: No unnecessary duplication
  • SOLID Principles: Code follows SOLID where applicable
  • Function Size: Functions are focused and < 50 lines
  • Cyclomatic Complexity: Functions have complexity < 10

Security

  • Authentication: Protected endpoints require auth
  • Authorization: Users can only access their own data
  • Input Sanitization: SQL injection, XSS prevented
  • Secrets Management: No hardcoded credentials or API keys
  • Encryption: Sensitive data encrypted at rest and in transit
  • Rate Limiting: Endpoints protected from abuse

Quick Start Guide

For Reviewers:

  1. Read PR description and understand intent
  2. Check that automated checks pass
  3. Do high-level review (architecture, approach)
  4. Do detailed review (logic, edge cases, tests)
  5. Use conventional comments for clear communication
  6. Provide decision: Approve, Comment, or Request Changes

For Authors:

  1. Write clear PR description
  2. Perform self-review before requesting review
  3. Ensure all automated checks pass
  4. Keep PR focused and reasonably sized (< 400 lines)
  5. Respond to feedback promptly and respectfully
  6. Make requested changes or explain reasoning

CC Built-in Review Commands (2.1.152+)

This playbook is the manual framework; Claude Code ships built-in commands that automate parts of it:

  • /code-review — reviews the current diff for correctness bugs and reuse/simplification/efficiency cleanups.
  • /code-review --fix (CC 2.1.152+) — runs the review then applies the findings to your working tree (a bug-hunting review covering correctness plus reuse/simplification/efficiency).
  • /code-review --comment — posts findings as inline PR comments.
  • /simplify — CC 2.1.154 changed this: it now runs a cleanup-only review (reuse, simplification, efficiency, altitude) and applies the fixes — it no longer invokes the full /code-review --fix bug-hunt. Reach for /simplify for tidy-ups, /code-review --fix for bug-finding-plus-fix.

Use the built-ins for fast diff-scoped passes; use ork:review-pr for the multi-agent, full-PR review (security + testing + architecture).


Skill Version: 2.0.0 Last Updated: 2026-01-08 Maintained by: OrchestKit

Related Skills

  • ork:architecture-patterns - Enforce testing and architectural best practices during code review
  • ork:security-patterns - Auth, input validation, and OWASP patterns to complement manual review
  • ork:testing-unit - Unit testing patterns to verify during review

Rules

Each category has individual rule files in rules/ loaded on-demand:

CategoryRuleImpactKey Pattern
TypeScript Qualityrules/typescript-quality.mdHIGHNo any, Zod validation, exhaustive switches, React 19
Python Qualityrules/python-quality.mdHIGHPydantic v2, ruff, mypy strict, async timeouts
Security Baselinerules/security-baseline.mdCRITICALNo secrets, auth on endpoints, input validation
Lintingrules/linting-biome-setup.mdHIGHBiome setup, ESLint migration, gradual adoption
Lintingrules/linting-biome-rules.mdHIGHBiome config, type-aware rules, CI integration

Total: 5 rules across 4 categories

Available Scripts

  • scripts/review-pr.md - Dynamic PR review with auto-fetched GitHub data

    • Auto-fetches: PR title, author, state, changed files, diff stats, comments count
    • Usage: review-pr [PR-number]
    • Requires: GitHub CLI (gh)
    • Uses $ARGUMENTS and !command for live PR data
  • assets/pr-template.md - PR description template

There is deliberately no review-report template here; ork:review-pr owns that output shape. See references/ork-delta.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Code Review Playbook AI skill do?

Structured review processes, conventional comments, language-specific checklists, and feedback templates. Use when reviewing PRs, conducting code review, or standardizing review practice.

Why use Code Review Playbook on TypingMind?

Because you install it once and use it with any model. Code Review Playbook is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Code Review Playbook in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yonatangross/orchestkit/tree/main/plugins/ork/skills/code-review-playbook. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Code Review Playbook?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Code Review Playbook?

As many as you like. As long as a model supports skills, you can use Code Review Playbook with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Code Review Playbook AI skill free?

Yes. It is published on GitHub by yonatangross under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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