ChatGPT Prompts for Code Review: Faster, Better Feedback
ChatGPT prompts for code review. Security, performance, readability, and architecture review frameworks for any programming language.
The Prompt
Act as a senior software engineer with 10+ years of experience conducting code reviews at Google, Stripe, or equivalent.
Review the following code:
[PASTE CODE HERE]
Language/framework: {language and framework}
Context: {what this code does and where it fits in the codebase}
Review focus: {security / performance / readability / architecture / all}
Team experience level: {junior / mid / senior — affects depth of explanation}
Review output (structured):
1. Summary verdict: APPROVE / REQUEST CHANGES / BLOCK with one-sentence reason
2. Critical issues (block merge — security vulnerabilities, data loss risk, breaking changes):
- Line reference + issue description + required fix
3. Important issues (request changes — performance problems, error handling gaps):
- Line reference + issue + suggested improvement
4. Minor suggestions (non-blocking — readability, naming, style):
- Line reference + suggestion
5. What's done well (at least 2 specific callouts — good code review is bidirectional)
6. Test coverage assessment: what scenarios are missing from the current test suite
Constraints:
- Critical issues must include the specific risk, not just what to change
- All references must include line numbers or function names
- Suggestions must include the improved code snippet, not just the description
- Never be condescending — frame everything as "consider X" or "this could X" for minors
Variables to fill in
-
{code}The code to review — paste directly into the prompt -
{context}What this code does and where it lives in the codebase -
{review focus}Security, performance, readability, architecture, or all -
{team experience}Junior, mid, or senior — affects explanation depth
How to use this prompt
- Paste the exact code block you want reviewed into the prompt
- Specify review focus — 'security only' produces more thorough security analysis than 'all'
- Use the structured output format as your PR review template
- Run security-focused reviews on any code handling authentication or user data
Code review is a teaching tool, not just a quality gate
The best code reviews improve the reviewer as much as the code being reviewed. Structuring feedback into Critical / Important / Minor creates a signal hierarchy — a developer knows immediately whether they need to fix something before merge or whether it’s a style preference. This prompt enforces that hierarchy.
The ‘what’s done well’ section is not optional
Code reviewers who only surface problems create a culture of defensiveness. Developers who receive only critical feedback start to dread reviews and write safer, less innovative code. Two genuine, specific callouts of what worked well take 30 seconds and significantly change the tone of the entire review.
AI code review catches pattern-level issues humans miss
Human reviewers miss security issues because they’re context-switching across many files. AI code review with a focused prompt — ‘security only, look for injection vulnerabilities, unsafe deserialization, and hardcoded credentials’ — can do a complete scan in seconds. Use this as a first pass before human review, not as a replacement for it.
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