30 Claude Prompts for Better Code Reviews

Code review is one of the highest-leverage activities in software development, and one of the most time-consuming. Whether you are checking your own work before a pull request, reviewing a junior colleague or enforcing standards across a growing codebase, it is slow and easy to do inconsistently. The right Claude prompts for code review give you focused, senior-level feedback in minutes.

Below are 30 prompts in five groups: general reviews, bug detection, security, performance and code quality, and tests and team process. They are written for Claude but work in any AI chatbot.

The best review prompts set a role, a focus area and an output format. On top of that:

• State the language and framework: ‘Python 3.11 with FastAPI’ or ‘TypeScript with React’ gets you idiomatic advice
• Share known trade-offs: tell Claude what you are deliberately not fixing so it focuses on what you need to discover
• Ask for rewrites, not just flags: add ‘and rewrite the problematic section with the fix applied’ to any prompt
• Verify and protect: run the tests on every suggested fix, never paste secrets, and follow your company’s rules on sharing code with AI tools

For careful, structured reviews of complex code, Claude Sonnet 5 is a strong default.

Six prompts for broad reviews with no single focus area. Gemini 3 Pro can hold long files or several modules at once when a change spans many places.

1. Senior engineer review

Act as a senior software engineer reviewing this [language/framework] code. Give feedback on correctness and logic, performance, readability and naming, error handling and edge cases, and security. Rate each issue Critical, High, Medium or Low and give a specific fix. Code: [paste your code]

2. Quick pre-merge scan

Review this code and list only the three most important issues to fix before it goes to production. Skip minor style points unless they seriously hurt readability. Code: [paste your code]

3. Contextual review

I am building [project, e.g. a REST API for a financial app]. This function is responsible for [what it does]. Review it with that context and flag anything that could cause problems in production, especially around [concern, e.g. concurrency or data integrity]. Code: [paste your code]

4. Pull request diff review

Here is the git diff for a pull request. Review only the added and changed lines and flag bugs, regressions or risks the change could introduce. Do not comment on unchanged code. Diff: [paste your diff]

5. Explain before reviewing

Before reviewing, explain in plain language what this code does, its inputs and outputs, and any assumptions it makes. Then list anything that looks surprising or inconsistent with that purpose. Code: [paste your code]

6. Team standards check

Here are our team’s coding standards: [paste]. Review this code against them only, list each deviation with the rule it breaks and suggest the compliant version. Code: [paste your code]

Prompt 5 is worth running on unfamiliar code — if Claude’s explanation does not match what the code is meant to do, you have found the first issue. For fast quick scans on small changes, Claude Haiku 4.5 keeps up with a busy review queue.

Six prompts for when finding bugs matters more than style. DeepSeek V4 Pro is useful for step-by-step reasoning through tricky logic.

7. Logic error hunt

Identify any logic errors, off-by-one errors, incorrect conditionals or edge cases in this code. For each, explain the input that would trigger the bug and the incorrect behaviour it would cause. Code: [paste your code]

8. Null and edge case analysis

Focus only on how this code handles null values, empty inputs, unexpected types and boundary conditions. List every scenario where it could fail and suggest a defensive fix for each. Code: [paste your code]

9. Concurrency and race conditions

This code runs [concurrently / in async handlers / across multiple workers]. Review it for race conditions, shared state issues, deadlocks and missing locks or transactions, and describe the sequence of events that would cause each problem. Code: [paste your code]

10. Error handling review

Review how this code handles errors: swallowed exceptions, overly broad catches, missing retries or timeouts, unclear error messages and failures that leave data in a bad state. Suggest a better pattern for each. Code: [paste your code]

11. Regression risk check

Here is the old version and the new version of this function: [paste both]. What behaviour has changed, which callers could break and which tests should I run or add to be confident nothing regressed?

12. Stack trace debugger

Here is an error and stack trace: [paste] and the relevant code: [paste]. Explain what is failing and why, list the most likely root causes in order and suggest how to confirm each before changing anything.

Always reproduce a suspected bug with a failing test before fixing it. For bugs that resist every fix, our ChatGPT prompts for problem solving help you step back and question your assumptions.

Six prompts that direct attention to the most common security risks, especially useful if you are not a security specialist. Claude Sonnet 4.6 is a dependable second reviewer for sensitive code.

13. General security audit

Act as a security-focused reviewer. Check this code for common vulnerabilities such as injection, XSS, insecure direct object references, weak input validation, hardcoded credentials and error messages that expose sensitive data. For each, explain the risk, the potential impact and how to fix it. Code: [paste your code]

14. Authentication and authorisation review

Review this authentication and authorisation logic. Check whether tokens are properly validated, whether sessions are managed securely, whether privilege escalation is possible and whether access checks can be bypassed by changing inputs or headers. Code: [paste your code]

15. Input validation review

List every place this code accepts external input — request bodies, query parameters, files, headers or environment variables — and check how each is validated and sanitised. Suggest a validation approach for anything missing. Code: [paste your code]

16. Secrets and configuration check

Review this code and configuration for secrets handling: hardcoded keys, credentials in logs, insecure defaults and settings that differ dangerously between environments. Suggest how to move each secret to a safer place. Code (with real secrets removed): [paste]

17. Dependency risk review

Here is my dependency file: [paste]. Point out packages that look outdated, unmaintained or unnecessary, and suggest what to check. Remind me to confirm vulnerabilities with a proper dependency scanner, since your information may be out of date.

18. API data exposure check

Review this API endpoint and its response: [paste]. Flag any field that exposes more data than the client needs, missing rate limiting, weak pagination limits and responses that differ in ways that could leak information.

An AI security review is a helpful first pass, not a replacement for a proper security audit, penetration test or automated scanning. For code that handles payments or personal data, involve a security specialist.

Six prompts for faster, cleaner and more maintainable code. GPT-5.6 Sol is a useful second opinion on complexity analysis and refactoring plans.

19. Performance and complexity analysis

Analyse this code for performance. Give the time and space complexity of each function or loop, and flag O(n²) or worse operations, repeated work that could be cached, database calls inside loops and large allocations. Suggest a more efficient alternative for each. Code: [paste your code]

20. Database query review

Review these queries and ORM calls for [database, e.g. PostgreSQL 15]. Look for missing indexes, full table scans, inefficient joins, N+1 patterns, missing pagination and UPDATE or DELETE statements without a WHERE clause. Explain the impact and suggest a rewrite. Code: [paste your code]

21. Naming and readability review

Review this code only for readability and naming. Flag unclear, misleading or inconsistent names, suggest better ones and briefly explain why. Do not comment on logic or performance. Code: [paste your code]

22. Refactoring suggestions

Identify refactoring opportunities that would improve maintainability without changing behaviour: repeated code, overly long functions, deep nesting, magic numbers and SOLID violations. Show a short before and after for each. Code: [paste your code]

23. Dead code and duplication finder

Find unused functions, unreachable branches, commented-out code and near-duplicate logic in these files: [paste]. Tell me what is safe to remove and what needs checking for callers elsewhere first.

24. Comments and documentation review

Review the comments and docstrings in this code. Flag comments that are outdated, obvious or misleading, and write clear docstrings for public functions describing purpose, parameters, return values and errors. Code: [paste your code]

Measure before and after any performance change — complexity analysis tells you where to look, profiling tells you whether it mattered. If your queries feed reports or dashboards, our ChatGPT prompts for data analysis cover SQL writing and checking in more depth.

Six prompts for tests, pull request descriptions and review comments that help your team rather than slow it down.

25. Test coverage gaps

Identify the most important missing test cases for this code. For each, describe the scenario, why it matters and a short example test in [framework, e.g. Jest, pytest]. Focus on edge cases, error paths and untested branches. Code: [paste your code]

26. Test suite review

Review these tests: [paste]. Flag tests that do not actually assert anything meaningful, depend on each other, rely on timing or mock too much, and suggest how to make them more reliable.

27. Pull request description writer

Write a pull request description for this diff: [paste]. Include what changed and why, how it was tested, risks or migration steps and what reviewers should focus on.

28. Kind and clear review comments

Here are my draft review comments for a colleague’s pull request: [paste]. Rewrite them to be specific, respectful and actionable, separating must-fix issues from suggestions and questions.

29. Review checklist builder

Create a code review checklist for our [language/framework] team covering correctness, security, performance, tests, readability and documentation, short enough to use on every pull request.

30. Language-specific review

This is [language and version, e.g. Python 3.11 or TypeScript 5 in Next.js]. Review this code for patterns specific to it — for example mutable default arguments and missing type hints in Python, or implicit any types, unhandled promises and hook dependency issues in TypeScript. Code: [paste your code]

Prompt 28 is worth using on every comment you are unsure about — how feedback lands affects whether it gets acted on. A quick pass with the AI grammar checker keeps PR descriptions clear for reviewers reading in a second language.

For critical code — authentication, payments, data migrations or public APIs — run the same review prompt through several AI models and compare. Each tends to catch slightly different classes of issues, and Chat Smith lets you do this side by side in one app while saving your favourite prompts as templates.

AI review makes human review faster, not unnecessary. For prompting technique beyond code, see the main ChatGPT prompts guide.