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50 ChatGPT Prompts That Actually Work for Code Reviews (Copy-Paste Ready)

#chatgpt #codereview #productivity #ai

50 ChatGPT Prompts That Actually Work for Code Reviews (Copy-Paste Ready)

You're using ChatGPT to review code. But the output is... meh.

Vague prompts = vague answers. Specific prompts = specific, actionable feedback.

After using ChatGPT for hundreds of code reviews, I've reverse-engineered the prompts that actually work. Here's the framework ā€” and 10 copy-paste examples to get you started.

The Anatomy of a Good Code Review Prompt

Bad prompt:

"Review this code."

Good prompt:

"Review this Python function for security vulnerabilities. Focus on SQL injection, XSS, and authentication bypass risks. Flag every issue with severity (high/medium/low) and suggest a fix."

What makes it work:

  1. Language specified (Python)
  2. Review scope defined (security vulnerabilities)
  3. Focus areas listed (SQL injection, XSS, auth bypass)
  4. Output format requested (severity + fix)

10 Copy-Paste Code Review Prompts

1. Security Vulnerability Scan 

Review this [language] code for security vulnerabilities. 
Check for: SQL injection, XSS, authentication bypass, insecure deserialization, and hardcoded secrets.
For each issue: rate severity (critical/high/medium/low) and provide a fixed code snippet.

[paste your code here]
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2. Performance Bottleneck Detector 

Analyze this [language] code for performance issues.
Identify: O(nĀ²) or worse complexity, redundant database queries, memory leaks, blocking I/O.
Suggest optimizations with before/after performance estimates.

[paste your code here]
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3. Code Smell Identifier 

Review this [language] code for code smells and anti-patterns.
Flag: long functions (>50 lines), deep nesting (>3 levels), duplicate logic, magic numbers, God objects.
Suggest refactorings with examples.

[paste your code here]
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4. Best Practice Enforcer (Language-Specific) 

Review this [language] code against [language] best practices and idioms.
Check: naming conventions, error handling, type hints, docstrings, and community standards (PEP 8 for Python, PSR-12 for PHP, etc.).
Rewrite non-compliant sections.

[paste your code here]
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5. Test Coverage Analyzer 

Review this [language] code and identify untested edge cases.
List: boundary conditions, error paths, null/undefined inputs, race conditions, and failure scenarios.
Write unit test skeletons for the 5 most critical cases.

[paste your code here]
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6. API Design Validator 

Review this API endpoint design (REST/GraphQL).
Check: resource naming, HTTP methods, status codes, error responses, versioning, authentication.
Suggest improvements aligned with REST/GraphQL best practices.

[paste your API spec or code here]
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7. Database Query Optimizer 

Review this [SQL/ORM] query for performance and correctness.
Check: missing indexes, N+1 queries, unnecessary joins, lack of pagination, SQL injection risks.
Rewrite the query with optimizations and explain the impact.

[paste your query here]
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8. Accessibility & UX Review (Frontend) 

Review this [React/Vue/Angular] component for accessibility issues.
Check: semantic HTML, ARIA labels, keyboard navigation, color contrast, screen reader support.
Rewrite with WCAG 2.1 AA compliance.

[paste your component code here]
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9. Error Handling Audit 

Review this [language] code for error handling weaknesses.
Flag: uncaught exceptions, swallowed errors, missing logging, no retry logic, poor user feedback.
Add proper error handling with examples.

[paste your code here]
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10. Architecture & Design Review 

Review this [language] module/class for design issues.
Check: single responsibility violations, tight coupling, missing abstractions, unclear interfaces.
Suggest refactorings to improve testability and maintainability.

[paste your code here]
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How to Get Even Better Results

1. Provide context

Add this to any prompt:

"This is part of a [type of application] built with [tech stack]. The code handles [user action]."

2. Request specific output formats

  • Markdown table for issue lists
  • Code diffs for refactorings
  • Numbered severity ratings for prioritization

3. Chain prompts for deeper reviews

First prompt: "Identify the top 3 issues."
Second prompt: "For issue #1, write a refactored version with tests."

4. Use role-based prompts

"Act as a senior security engineer reviewing this code for a financial services application."

This primes the model for stricter, domain-specific analysis.

The Full Arsenal (50 Prompts)

These 10 are just the start. I've compiled 50 battle-tested prompts covering:

  • Code review (12 prompts)
  • Debugging (12 prompts)
  • System architecture (13 prompts)
  • Technical documentation (13 prompts)

All copy-paste ready. All designed for real dev workflows.

šŸ‘‰ Get the full Dev Prompt Arsenal here ā€” $27, instant download.

Final Thoughts

ChatGPT is only as good as your prompts. Vague input = vague output.

These prompts give you specificity ā€” the #1 factor in getting useful code reviews from AI.

Try the 10 above. If they save you time, the full 50-prompt pack will 10x your ChatGPT productivity.

What's your go-to ChatGPT prompt for code reviews? Drop it in the comments.

Resources

If you found this useful, I put together Dev Prompt Arsenal ā€“ 50 ChatGPT Prompts for Code Review, Debugging & Architecture ā€” a complete resource that goes much deeper on everything covered here. It's a one-time download that pays for itself the first time you use it.

Check it out: https://ariaworks3.gumroad.com/l/dev-prompt-arsenal

What's your biggest challenge with this topic? Drop it in the comments.

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