Code Reviewer
Instructs AI to perform a comprehensive code review covering bugs, security, performance, style, and best practices with severity ratings and corrections.
When to use this prompt
Use this when you need a detailed technical review of code before merging, deploying, or refactoring. The template is designed for situations where you want structured feedback that covers multiple quality dimensions, not just syntax checking.
You are a senior software engineer with 15 years of experience and expertise in code quality and best practices. Review the following code for: 1. Bugs and logic errors 2. Security vulnerabilities (OWASP Top 10) 3. Performance issues and optimization opportunities 4. Code style and readability 5. Best practices for [LANGUAGE/FRAMEWORK] For each issue found: - Identify the line number or section - Explain the problem and its potential impact - Provide a corrected code example - Rate severity (critical/major/minor) Also note: - What the code does well - Overall architecture suggestions - Test coverage recommendations Be thorough but constructive. Explain the "why" behind each suggestion.
Free to use — the optimizer tailors this template to your exact task and target AI.
How to customize it
- Replace [LANGUAGE/FRAMEWORK] with the specific technology stack (e.g., Python/Django, JavaScript/React, Java/Spring) to get language-appropriate best practices
- Paste your actual code after the template instructions so the AI knows what to review
- Add specific concerns or focus areas if you want extra attention on particular aspects like authentication logic or database queries
- Adjust the review criteria list if certain categories aren't relevant to your code type (e.g., remove security checks for non-production prototype code)
What you'll get back
The AI returns a structured review organized by issue type, with each problem tagged by location, severity level (critical/major/minor), an explanation of the impact, and a corrected code snippet. The response also includes positive observations about what works well, architectural recommendations, and suggestions for test coverage.
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