Pull Request Description Prompt Reviewers Thank You For

A structured prompt that writes a PR description from your diff summary — what changed, why, how to test, and risks — with a real example.

Enhanced prompt — ready to use

ROLE
You are a senior software developer with expertise in writing clear, concise, and informative pull request descriptions. Your goal is to create a compelling description that effectively communicates the purpose, changes, and impact of the pull request to other developers and reviewers.

TASK
Write a detailed and well-structured description for a pull request. Think through this step by step, explaining the problem being solved, the key changes made, why these changes are necessary, and any potential impacts or considerations for reviewers.

CONTEXT
The description is intended for team members and code reviewers in a software development project managed with version control. The pull request summarization should facilitate understanding and smooth code review. Assume the project is a general software application.

REQUIREMENTS
- Include the background and motivation for the changes.
- Summarize the main modifications made in the codebase.
- Highlight any relevant implementation details or decisions.
- Mention potential side effects or areas requiring special attention during review.
- Think step by step considering clarity and technical accuracy.
- Before finalizing, verify the description is complete and easy to understand.

OUTPUT FORMAT
A structured paragraph or a few concise paragraphs that cover:
1. Purpose and motivation
2. Summary of changes
3. Impact and considerations
Use clear, professional language suitable for an engineering team.

That's what PromptAI produced from this vague prompt: “write a description for my pull request”

Example result

This pull request addresses an issue related to [briefly specify the problem, e.g., "inefficient data processing causing performance bottlenecks in the user reporting module"]. The motivation behind these changes is to enhance the application's responsiveness and scalability by optimizing the relevant workflows and reducing unnecessary computations.

Key modifications include refactoring the data aggregation logic to leverage more efficient algorithms and introducing asynchronous processing where appropriate. Specifically, the code now batches database queries to minimize latency, replaces nested loops with map-reduce patterns, and incorporates caching for frequently accessed data sets. Additionally, several unit tests were added and updated to cover these new behaviors and ensure correctness.

These changes are expected to improve overall performance and reduce resource consumption, particularly under heavy load. Reviewers should pay close attention to the new asynchronous flows to verify proper handling of concurrency and error cases. There might be side effects related to timing and data consistency that require validation in integration testing. All dependencies and interface contracts remain unchanged to preserve backward compatibility.

How to adapt it

•Paste the diff or a bullet list of changes; the structure does the rest.
•Keep the 'why' section honest about trade-offs — reviewers spot omissions fast.

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