Better Pull Requests
The Complete Guide

What Makes a Great Pull Request?

A great pull request isn't just about working code. It's about making your reviewer's job easier. When reviewers can quickly understand what changed and why, they approve faster and give better feedback.

Research from Google and Microsoft shows that PRs under 400 lines get reviewed 2x faster and have 50% fewer defects than larger PRs. But size is just one factor. Great PRs also have:

Anatomy of a PR That Gets Approved Fast

Fast-approved PRs share a common structure. Here's the anatomy of a PR that reviewers love:

Writing PR Descriptions That Reviewers Love

Your PR description is the first thing reviewers see. A good description answers questions before they're asked, while a bad description wastes everyone's time.

The Bad PR Description

What's wrong? No context, vague changes, no testing info. Reviewers have to read the entire diff to figure out what's happening.

The Good PR Description

Why it's better: Clear problem statement, specific changes, testing evidence, deployment notes. Reviewers know exactly what to expect.

Keeping PRs Small and Focused

The single most impactful change you can make is to keep PRs small. Data from Google, Microsoft, and Cisco shows that smaller PRs are reviewed faster, have fewer defects, and get better feedback.

The Numbers

How to Keep PRs Small

Code Examples: Good vs Bad PRs

Let's look at real code changes. These examples show common mistakes and how to fix them.

Example 1: Mixed Concerns

// PR: Add user profile feature
// 📁 src/auth/AuthService.ts
class AuthService {
-  login(username, password) {
+  async login(credentials: LoginCredentials) {
     // ... refactored auth logic
  }
+  async updateProfile(userId, profile) {
+    // ... new profile feature
+  }
}

// PR 1: Refactor AuthService to async/await
class AuthService {
-  login(username, password) {
+  async login(credentials: LoginCredentials) {
     // ... refactored auth logic
  }
}

// PR 2: Add user profile update feature
class AuthService {
  async login(credentials: LoginCredentials) {
    // ... existing code
  }
+  async updateProfile(userId, profile) {
+    // ... new profile feature
+  }
}

Example 2: Vague Commit Messages

abc1234 fix stuff
def5678 update code
ghi9012 oops
jkl3456 final changes

abc1234 feat: Add UserProfile model and database migration
def5678 feat: Implement updateProfile API endpoint
ghi9012 feat: Add profile update form to dashboard
jkl3456 test: Add unit tests for profile update flow

Example 3: Missing Context in Code

if (user.loginAttempts > 5) {
  user.locked = true;
  user.lockUntil = Date.now() + 1800000;
}

// Lock account after too many failed login attempts to prevent brute force
const MAX_LOGIN_ATTEMPTS = 5;
const ACCOUNT_LOCK_DURATION_MS = 30 * 60 * 1000; // 30 minutes

if (user.loginAttempts > MAX_LOGIN_ATTEMPTS) {
  user.locked = true;
  user.lockUntil = Date.now() + ACCOUNT_LOCK_DURATION_MS;
}

PR Templates and Checklists

Templates enforce consistency and reduce cognitive load. Here's a battle-tested PR template you can use with GitHub, GitLab, or Bitbucket.

PR Description Template

Pre-Submit Checklist

Use this checklist before clicking "Create Pull Request":

Automating PR Quality Checks

Great teams automate quality checks so reviewers can focus on logic and architecture. Here are the must-have automations for every PR:

# .github/workflows/pr-checks.yml
name: PR Checks
on: [pull_request]
jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - run: npm ci
      - run: npm test
      - run: npm run lint
      - run: npm run type-check
      - run: npm run build

Common PR Anti-Patterns

Avoid these mistakes that slow down reviews and frustrate your team:

How AI Can Improve Your PRs

AI code review tools can catch issues before human reviewers see your PR. But not all AI tools are created equal. Human-in-the-loop approval prevents AI mistakes from cluttering your pull requests.

What AI Can Catch

Git AutoReview: Human-in-the-Loop AI

Git AutoReview runs Claude, Gemini, and GPT on your PR, but you approve every suggestion before it posts to your pull request. This prevents the 29-45% of AI hallucinations from reaching reviewers.

Frequently Asked Questions