Treat Your PRs Like APIs: The Prompt That Makes It Happen

Ship safer and faster by automating your PR descriptions—when it matters

Author: Hou C.
August 05, 2025

Writing good code is one thing. Explaining it clearly is what gets it shipped.

But here's the reality: most PR delays aren't caused by poor descriptions. They're caused by reviewer availability, large diffs, or architectural debates. That said, for complex or risky changes, a well-structured PR description can be the difference between a confident approval and a week of back-and-forth.

Core Insight: Scale Your PR Docs With Complexity

Not every PR needs a novel. A dependency bump doesn't require a deployment strategy. But a payment integration touching multiple services? That needs context.

The key is knowing when to invest in documentation—and using AI to make that investment efficient when you do.

When PR Descriptions Actually Matter

Use detailed descriptions for:

• Breaking changes to shared APIs or libraries

• Security-sensitive modifications (auth, payments, PII)

• Database migrations or schema changes

• Cross-service architectural changes

• First implementation of a new pattern

Skip the ceremony for:

• Dependency updates with clear changelogs

• Simple bug fixes with linked tickets

• Formatting or refactoring changes

• Documentation updates

• Changes under 50 lines with obvious intent

The Graduated Approach

Level 1: The Quick Template (80% of PRs)

For straightforward changes, keep it simple:

**What:** Fixed user avatar upload failing for files over 5MB
**How tested:** Added unit test for large files, manually tested with 10MB image
**Note:** Increased Lambda timeout from 30s to 60s

Time investment: 30 seconds. Value: Sufficient.

Level 2: The Standard Template (15% of PRs)

For meaningful features or moderate complexity:

## What Changed
- Added Stripe webhook handling for subscription updates
- New background job processes payment_intent.succeeded events

## Testing
- Unit tests for webhook signature validation
- Integration test with Stripe test fixtures
- Manually triggered test webhooks in staging

## Deployment Notes
- Add STRIPE_WEBHOOK_SECRET env var before deploy
- Run migrations first (adds webhook_events table)

Time investment: 2 minutes. Value: Helps reviewers focus.

Level 3: The Full Template (5% of PRs)

For complex, risky, or architectural changes, AI can help generate comprehensive documentation:

You are a senior engineer writing a PR description for a complex change.
Focus only on information that helps reviewers understand risks and make decisions.

**Our context:** [Your stack, team size, deployment style]

**The change:** [Paste key parts of your diff or summary]

Generate a PR description with these sections (skip any that aren't relevant):

## Changes
- What functionality changed and why

## Review Focus  
- Specific files/areas that need careful review
- Trade-offs or decisions that need validation

## Risk Assessment
- What could break in production
- Which users/flows are affected

## Testing Strategy
- How this was validated
- What edge cases were considered

## Deployment Requirements
- Prerequisites (migrations, env vars, feature flags)
- Rollback plan if needed

Keep it under 200 words. Be specific, not comprehensive.

You're absolutely right to call that out. Let me replace that section with something more honest and useful:

Common Patterns: Where Detailed Descriptions Add Value

Pattern 1: Hidden Dependencies

Change type: Modifying shared utilities, libraries, or base classes
Why descriptions matter: Reviewers can't see all consumers in the diff
Key information to include: "This is used by X, Y, and Z services"
Without it: Breaking changes slip through to production

Pattern 2: Non-Obvious Side Effects

Change type: Event handlers, webhooks, background jobs
Why descriptions matter: Async effects aren't visible in code
Key information to include: "This triggers email to users" or "This will reprocess 10K queued jobs"
Without it: Unexpected customer impact or system load

Pattern 3: Performance Implications

Change type: Database queries, API calls in loops, cache changes
Why descriptions matter: Performance impact isn't obvious from logic changes
Key information to include: Query execution time, expected traffic, cache hit rates
Without it: Reviews miss O(n²) problems or cache stampedes

Pattern 4: Security Boundaries

Change type: Auth changes, data access, API endpoints
Why descriptions matter: Security implications need explicit callout
Key information to include: Who can access what, rate limits, authentication flow
Without it: Authorization bypasses or data exposure risks

Pattern 5: Partial Implementations

Change type: Feature flags, phased rollouts, MVP versions
Why descriptions matter: Reviewers need to know what's intentionally missing
Key information to include: "This only handles happy path, error handling in next PR"
Without it: Reviewers waste time commenting on known limitations

The Human Element AI Can't Capture

Even the best AI can't explain:

• Why you chose approach A over B (unless you tell it)

• Business context from private Slack threads

• Which pieces you're unsure about and want input on

• The customer complaint that triggered this change

Always add a human note about decisions and doubts:

## Context
Customer X reported timeouts. Chose caching over DB optimization 
because we're migrating databases next quarter anyway. 
Not sure if 5-minute TTL is right—thoughts?

Practical Implementation

Week 1: Manual Testing

1. Pick your next complex PR (>200 lines or touching >3 files)

2. Use the Level 2 template manually

3. Ask reviewers: "Did the description help?"

4. If no: don't waste time on descriptions for similar PRs

Week 2-4: Find Your Pattern

• Track which PRs actually benefited from detailed descriptions

• Note common questions from reviewers

• Build your own template based on what YOUR team needs

Month 2+: Selective Automation

• Use AI only for Level 3 PRs (complex/risky)

• Save successful descriptions as templates

• DON'T automate until you know what adds value

IMO, splitting large PRs into smaller ones has more impact than perfecting descriptions.

Tool Recommendations (When You're Ready)

Start simple: Text file with templates, copy-paste as needed
For Level 3 PRs: Claude 3.5 Sonnet or GPT-4 for nuanced analysis
Automation warning: Only automate after you've manually validated value for 20+ PRs
Anti-pattern: Building GitHub Actions before proving the approach works

The Reality Check

This approach helps maybe 20% of your PRs. For the other 80%:

• Keep PRs small and focused

• Link to the ticket with full context

• Use clear commit messages

• Add screenshots for UI changes

• Let the code speak for itself

The goal isn't perfect documentation—it's removing friction where friction actually exists.

Ready for Higher Leverage?

Better PR descriptions help at the margins. For transformative impact, focus on:

1. Reducing PR size (biggest lever)

2. Improving test coverage (catches issues before review)

3. Establishing clear code ownership (faster reviewer assignment)

This upgrade comes from Stage 5: Finalize of Prompt-to-Production → Read the full 6-stage system