Quick Answer
A good PR description cuts review round-trips. This generates one from the diff in seconds, for $20/mo.
What you get
- Generate a structured PR description from the diff in under 30 seconds
- Give reviewers the what, why, and how-to-test up front so they start reviewing instead of reverse-engineering
- Reduce review round-trips caused by 'what does this even change?' back-and-forth
- Run the whole setup for $20/mo, or free if you already pay for a coding assistant
Step-by-Step Workflow
5 steps · 30 min to set up · runs per PR, seconds each ongoing
- 1
Define your PR description template
Decide the sections every PR should have: what changed, why (the problem or ticket), how to test it, and any risk or rollout notes. Commit it as a PULL_REQUEST_TEMPLATE so it is the default body, and so the AI has a fixed structure to fill rather than free-forming a different shape every time.
15 minOutput: A committed PR template with What / Why / How to test / Risk sectionsTip: Keep it to four sections. A template with ten fields gets half-filled and ignored; four sections a reviewer actually needs get filled every time.
- 2
Wire Claude Code to read the diff
Set up a small command or Claude Code prompt that runs against your branch's diff (via git diff or the gh CLI) and outputs the description in your template format. Because it reads the real diff, the description reflects what the code actually does, not what you remember doing across a week of commits.
Claude Code - the interface you'll work in for this step. Screenshot of the tool's own UI, not our results. 15 minOutput: A one-command flow that emits a filled-in PR description from the current diffTools: Claude CodeTip: Feed it the diff against the base branch, not the last commit. A PR is the whole branch; describing only the final commit misses most of the change.
- 3
Generate the description at PR-open time
When you open a PR, run the command, review the output, and paste it in (or push it straight to the PR body via gh). The review step matters: the AI describes what the diff does accurately, but only you know the why behind an ambiguous change, so you edit the 'why' where the diff alone cannot explain it.
under 30 sec per PROutput: Every PR opens with a complete, accurate descriptionTools: Claude CodeTip: The AI nails 'what changed' and guesses at 'why'. Always sanity-check the why; that is the sentence the reviewer most needs to be true.
- 4
Add a native summary layer if you want zero setup
For contributors who will not run a local command, turn on GitHub Copilot's native PR summary or CodeRabbit's automatic walkthrough so every PR gets a machine summary even when the author writes nothing. This is the safety net that keeps the standard from depending on individual discipline.
GitHub Copilot - the interface you'll work in for this step. Screenshot of the tool's own UI, not our results. 15 minOutput: A generated summary on every PR regardless of whether the author ran the commandTools: GitHub Copilot, CodeRabbitTip: Do not run both Copilot summaries and CodeRabbit walkthroughs on the same PR; two auto-summaries is noise. Pick one automatic layer.
- 5
Make a real description the merge norm
Add 'PR has a description with what/why/how-to-test' to your review checklist so an empty PR gets sent back. With generation down to seconds, there is no excuse for a blank body, and the norm costs the author nothing. This is what converts a nice-to-have into a consistent reviewer experience.
ongoingOutput: A team norm where every PR carries a complete description before reviewTip: Enforce the norm, not the tool. Some people will paste from Copilot, some from Claude Code; what matters is the reviewer never gets a blank PR.
Most PR descriptions are either empty or a copy of the branch name, and the cost lands on the reviewer, who has to reverse-engineer intent from the diff before they can even start reviewing. That reverse-engineering is where review time goes and where round-trips come from. The fix is cheap: an AI reads the diff and writes a real description (what changed, why, and how to test it) in seconds, formatted to your team's template. It is one of the highest-return, lowest-effort AI workflows in engineering, and the required version costs $20/mo or nothing on top of a coding assistant you already pay for.
The description is for the reviewer, not the author
Authors skip PR descriptions because they already know what the change does. But the description is not for the author, it is for the reviewer, who is walking in cold. A reviewer handed a blank PR spends the first several minutes reconstructing intent from the diff, and that reconstruction is exactly where they miss things and where they ask questions the author could have answered up front. A generated description that states the what, the why, and the how-to-test converts that dead reconstruction time into actual review, and it removes the most common round-trip ('what is this change trying to do?') before it happens.
Stack cost breakdown
Public list prices as of July 2026. Optional tools are marked in the notes.
| Tool | Plan | Monthly cost | Notes |
|---|---|---|---|
| Claude Code | Claude Pro | $20/mo | Required. Reads the diff via the gh CLI and writes the description against your template. |
| GitHub Copilot | Pro | $10/mo | Optional. Native in-GitHub PR summary button, no local command needed. |
| CodeRabbit | Pro | $24/mo | Optional. Auto-posts a walkthrough and summary comment on every PR alongside review. |
| Total | $20 - $54/mo($20 required, $54 with optional tools) | ||
Email me this stack as a checklist
Every tool, the plan to pick, and the monthly cost - in your inbox.
Real usage
What people actually run
No usage reports yet - be the first to share what you run. Tell us your real stack, your actual monthly cost, and any tools you swapped.
The generation prompt and what it produces
One prompt against the branch diff produces a description in your template. Here is the prompt and a sample of its output.
Claude Code PR description prompt
Read the diff between this branch and the base branch (run: git diff origin/main...HEAD). Write a pull request description in exactly these sections: What changed (bullet points of the concrete changes), Why (the problem this solves; if you cannot infer it from the diff, write 'AUTHOR: fill in the why'), How to test (specific steps a reviewer can run), and Risk (anything touching auth, payments, migrations, or public APIs). Be concrete and terse. Do not praise the change or editorialize.
Note: The 'AUTHOR: fill in the why' fallback is deliberate. It stops the model from inventing a rationale and forces the one thing only the author knows to be filled in by a human.
Sample generated description
What changed: - Add rate limiting to POST /api/invite (10/min per user) - Return 429 with a Retry-After header when exceeded - Add integration test covering the limit and the reset window Why: Invite endpoint was being abused to send bulk spam; ticket ENG-482. How to test: Hit POST /api/invite 11 times in a minute with the same token; the 11th returns 429. Wait 60s and confirm it succeeds again. Risk: Touches a public API. Limit is per-user, so a shared service account could be throttled; confirm no internal job calls this endpoint in a tight loop.
Note: This is the shape a reviewer can act on immediately: they know what to look at, why it exists, exactly how to verify it, and where the sharp edge is.
Adjust for Your Situation
If you want zero author effort
Skip the local Claude Code command and rely on GitHub Copilot's native PR summary or CodeRabbit's auto walkthrough. You lose the ability to shape the 'why' up front, but every PR still gets a machine summary with no discipline required. Cost drops to $10/mo (Copilot) or folds into review (CodeRabbit).
If you already run CodeRabbit for review
Use its automatic PR walkthrough as your summary layer and skip a separate description tool entirely. The review bot already reads the diff; let its walkthrough be the description and keep a template for the author to add the why and test steps.
If you want it fully automated in CI
Move generation into a git hook or a GitHub Action that calls the model on PR open and posts the description via the API. No human trigger. Keep a required 'why' field the author must fill, since CI cannot infer intent the diff does not contain.
Swap options
Drop-in substitutions if a tool does not fit your budget or stack. These trade cost or effort for the recommended setup.
| Swap out | Use instead | When |
|---|---|---|
| Claude Code | GitHub Copilot PR summary | You want the description generated inside GitHub with one click and no local setup |
| Claude Code | CodeRabbit walkthrough | You already run CodeRabbit for review and want the summary as part of that |
| GitHub Copilot | Cursor or Windsurf | You would rather generate the description from your IDE than the GitHub UI |
| Generate the description | A git hook or CI step calling the model | You want it fully automated with zero human trigger |
Common Pitfalls
- Trusting the AI's 'why'. The diff shows what changed, not why; the model guesses the rationale and can guess wrong. Always review and correct the why before opening the PR.
- Generating from the last commit instead of the full branch diff. A PR is the whole change; describing one commit misses most of it and misleads the reviewer.
- Stacking two auto-summarizers. Copilot plus CodeRabbit on the same PR produces two competing summaries and trains people to ignore both. Pick one automatic layer.
- Letting the description replace review context in code. A great description does not excuse cryptic code; it complements it. Do not use generated prose to paper over a confusing diff.
- Making it a tool mandate instead of an outcome norm. Enforce 'every PR has a real description', not 'everyone must use tool X'. The reviewer cares about the description, not how it got there.
Frequently Asked Questions
What does this cost?
Can the AI really infer why I made a change?
Do I even need a tool, or can GitHub do this natively?
Will reviewers actually read a generated description?
Is it safe to send my diff to an AI to summarize?
How much review time does this actually save?
How we built this workflow
ToolJunction's editorial team tests each workflow with real accounts and real budgets before publishing. Cost figures reflect public pricing pages as of July 2026. Reply rates, time estimates, and outcome metrics come from our own runs or vetted operator interviews. We update this page when a tool's pricing changes or a step stops working.
Last updated July 7, 2026; prices verified at publication.