Create comprehensive code review checklists tailored to your tech stack, team standards, and common issues.
Copy & paste the prompt below into your preferred LLM. Unless a specific AI model is mentioned, you can use whichever you prefer.
You are a engineering manager who has built high-performing code review cultures. Create a review checklist for my team. My team: - Tech stack: [LANGUAGES, FRAMEWORKS, TOOLS] - Team size: [NUMBER OF DEVELOPERS] - Code review tool: [GITHUB PRs / GITLAB MRs / BITBUCKET / GERRIT / OTHER] - Common issues: [BUGS, STYLE INCONSISTENCY, PERFORMANCE, SECURITY, etc.] - Team experience: [JUNIOR-HEAVY / MIXED / SENIOR] - Review bottleneck: [REVIEWS TAKE TOO LONG / NOT THOROUGH ENOUGH / INCONSISTENT QUALITY] Build: 1. **Review Checklist** organized by priority: - **Must Check (blockers):** Security vulnerabilities, data handling, error handling, breaking changes, test coverage - **Should Check (quality):** Code clarity, naming, DRY violations, edge cases, logging, documentation - **Nice to Check (polish):** Performance optimization, code style, refactoring opportunities 2. **Stack-Specific Items:** Checklist items unique to your technology (React hooks rules, SQL injection prevention, API rate limiting, etc.) 3. **Review Comment Templates:** How to give feedback that's constructive, not critical. Examples of good vs. bad review comments 4. **Review Process:** - PR description template - How to size PRs (under 400 lines ideal) - Who reviews what (ownership model) - SLA for review turnaround - How to handle disagreements 5. **Automated Checks:** What should be automated (linting, formatting, type checking, tests) vs. what needs human eyes 6. **Onboarding Guide:** How to teach new team members your review standards 7. **Review Metrics:** What to track (review time, comments per PR, revision count) and healthy ranges Code review is a team skill, not an individual one. Make it efficient, kind, and educational.
The effectiveness of "Code Review Checklist Builder" comes from its well-structured structure. By incorporating output formatting and few-shot examples and tone calibration, it channels the AI's capabilities toward producing exactly what you need. What you get back is production-quality code that handles edge cases and follows your stack conventions - production-ready rather than a rough draft that needs heavy reworking.
These coding tips will help you get stronger results when using "Code Review Checklist Builder" and similar prompts in this category.
"Code Review Checklist Builder" is particularly useful in these situations. If any of these scenarios sound familiar, this prompt will save you significant time.
When you use "Code Review Checklist Builder" with ChatGPT, Claude, or Gemini, here is what to expect in the AI output.
Adapt "Code Review Checklist Builder" to your specific situation by modifying these key areas. The more context you add, the better the results.