A pull request description speeds up code review when it tells a reviewer what changed, why it changed, and how it was tested — before they open a single diff — and AI can draft a strong one directly from your code changes and commit history if you prompt it with the actual diff rather than a vague summary request. A missing or thin description doesn’t just slow the review down; it pushes reviewers toward either rubber-stamping the change or reverse-engineering intent from the code itself, neither of which catches real problems.
What Sections Does a Good Pull Request Description Actually Need?
Five components consistently show up in strong PR templates: the What (a plain description of the change, not just a ticket link), the Why (the business or engineering goal it serves), the How (notable design decisions a reviewer wouldn’t infer from the diff alone), Testing (how it was validated and what wasn’t covered), and, when relevant, Screenshots for UI or infrastructure changes. The “why” section matters more than teams usually give it credit for — as one guide to writing great PR descriptions puts it, “the ‘why’ tells us what business or engineering goal this change achieves,” which is exactly the context a diff can’t provide on its own.
How Do You Prompt AI to Draft a Description From a Diff?
Feed the model the actual diff and commit messages, not just a topic:
“Here is a git diff and its commit messages: [paste diff/commits]. Write a pull request description with sections for What, Why, How, and Testing. In ‘Why,’ infer the likely motivation from the code changes and commit messages, but if it’s genuinely unclear, say so explicitly rather than guessing. In ‘How,’ call out any non-obvious design decisions, like a new dependency, a changed data structure, or an edge case being handled differently. Keep the whole description under 200 words.”
That instruction to flag genuine uncertainty instead of guessing matters — an AI-drafted “Why” that confidently states an incorrect motivation is worse than no “Why” section at all, since a reviewer is likely to trust it without checking.
How Do You Keep an AI-Drafted Description From Hiding Problems?
A well-written description should make a reviewer more critical, not less — the goal is for reviewers to “focus their critical attention where it matters most rather than deciphering specifications,” not to wave the change through. Two checks worth adding before you paste an AI-drafted description into a real PR:
- Confirm the “Testing” section reflects what you actually ran, not what the model assumed based on the code — never let AI invent a test you didn’t perform.
- If the diff touches more than a handful of unrelated concerns, treat that as a signal the change itself should be split into smaller PRs, not just described more thoroughly. A description that has to work hard to explain an oversized change is a symptom, not something to prompt your way around.
How Does This Fit Into a Broader AI-Assisted Dev Workflow?
A clear PR description is most valuable when the change itself is already well-scoped and tested. If the PR touches code nobody fully understands anymore, our prompts for refactoring legacy code without breaking it are a useful companion for making the underlying change safer before you write the description. And since the “Testing” section should reflect real coverage, prompts for generating realistic test data and fixtures can help make sure that section is describing something genuinely thorough rather than a single happy-path check.
Frequently Asked Questions
Should I let AI write the entire pull request description unedited?
No — treat it as a strong first draft. You wrote the code and ran the tests, so you’re the only one who can confirm the “Why” and “Testing” sections are actually accurate rather than a plausible-sounding guess based on the diff.
How long should a pull request description be?
Short and conversational, not exhaustive. If a description is getting long because the underlying change is genuinely complex, that’s usually a sign the change should be broken into smaller PRs rather than a sign the description needs to be more thorough.
Does a good PR description replace the need for inline code comments?
No, they serve different readers. A PR description gives a reviewer context at review time; inline comments explain non-obvious logic to anyone reading the code months later, long after the PR itself is buried in history.
For more on structuring the “What, Why, How, Testing” format, see HackerOne’s guide to writing great pull request descriptions.
Photo: programming code by Martin Vorel, licensed under CC BY-SA 4.0.
