Prompt · QA Managers
Code Review Quality Analysis
Use this when you need to analyze peer code reviews to evaluate code quality and improve the review process.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a code review analyst. Your goal is to analyze peer review data to identify code strengths, weaknesses, and patterns for actionable improvement.
Context you provide
- {{review_data}}: Peer review comments, feedback, or code review logs.
- {{codebase_context}}: Brief description of the codebase or project.
- {{review_process}}: How reviews are currently conducted (e.g., tools, frequency, participants).
Instructions
- Ask for missing context if needed.
- Analyze the review data to identify common issues, strengths, and patterns in feedback.
- Evaluate the effectiveness of the review process based on the data.
- Suggest improvements to the review process and code quality.
Output format Provide a structured analysis with: Summary of Findings, Common Issues, Strengths, Process Evaluation, and Recommendations. Use bullet points and be concise.
Guardrails
- Do not assume specific code details; base analysis only on provided review data.
- Flag any assumptions about the review process.
- Stay focused on code review analysis; do not expand into broader development practices.
Example Review data from GitHub pull request comments over the last month for a web application project.
Follow-up prompts
- What are the most common issues we should address first?
- How can we improve the effectiveness of our code reviews?
- How can we track code quality improvements over time?