Code Review Checklist Prompts for Developers

Code review checklist prompts help developers structure their review process and catch issues before code goes into production. A clear code review checklist ensures you examine every critical area from security to performance without missing important details.

SeriesWire offers an AI prompt generator and a prompt library to help developers work faster and think through complex tasks. The prompts below are templates that you can customize by replacing the bracketed placeholders with your own project details, programming language, constraints, or team standards.

Pull Request Review Prompts

These prompts help you review pull requests with consistent standards across your team.

Review this pull request for [programming language] and check for [list specific concerns such as security vulnerabilities, performance issues, or code duplication]. Provide feedback on code quality, maintainability, and adherence to [coding standards or style guide]. Format your response as a structured checklist.

Analyze this PR for [project name] and evaluate whether it meets the following criteria: [list acceptance criteria]. Identify any breaking changes, edge cases not handled, or potential conflicts with existing functionality. Suggest improvements where needed.

Act as a senior developer reviewing a pull request for [specific feature or module]. Check the code against these priorities: [list priorities such as readability, test coverage, error handling]. Point out any violations of [team conventions or design patterns] and suggest specific fixes.

Review this code change for [language and framework] with focus on [specific aspect such as API design, database queries, or frontend performance]. Highlight any code smells, anti-patterns, or areas that could cause technical debt. Recommend refactoring strategies if necessary.

Security Review Prompts

Security checks prevent vulnerabilities from reaching production environments.

Perform a security review of this code for [application type] written in [programming language]. Check for common vulnerabilities including [list specific threats such as SQL injection, XSS, CSRF]. Identify any insecure dependencies or configuration issues.

Analyze this code for security risks related to [specific concern such as authentication, data encryption, or input validation]. Review how user data is handled and whether it follows [security standard or compliance requirement]. List any potential attack vectors.

Review this API implementation for [service or feature] and identify security weaknesses in [areas such as authorization, rate limiting, or sensitive data exposure]. Check whether error messages leak information and whether logging captures security events properly.

Examine this code for [specific module] and verify that it implements security best practices for [context such as payment processing, file uploads, or user authentication]. Flag any hardcoded credentials, weak encryption, or improper access controls.

Code Quality and Structure Prompts

These prompts focus on maintainability and clean code principles.

Evaluate the code quality of this [language] implementation for [feature or component]. Assess naming conventions, function length, complexity, and modularity. Identify areas where the code violates [principles such as SOLID, DRY, or KISS] and suggest refactoring.

Review this codebase for [project or module] and analyze its structure and organization. Check whether classes and functions have single responsibilities, whether abstractions are appropriate, and whether the code follows [architectural pattern]. Point out any tight coupling or design issues.

Analyze this code for readability and maintainability in [programming language]. Identify functions that are too complex, variables with unclear names, or logic that needs comments for clarity. Suggest ways to simplify and improve code documentation.

Review this implementation of [feature or algorithm] and assess whether it follows [coding standard or style guide]. Check for consistent formatting, appropriate use of language features, and adherence to [team conventions]. Highlight any deviations that should be fixed.

Performance and Optimization Prompts

Performance reviews catch bottlenecks before they affect users.

Analyze this code for [application type] and identify performance bottlenecks in [specific areas such as database queries, API calls, or loops]. Suggest optimizations for [target metric such as response time, memory usage, or throughput]. Consider the impact on [scale or load conditions].

Review this implementation for [feature or service] and evaluate its efficiency. Check for unnecessary computations, redundant database calls, or inefficient algorithms. Recommend improvements using [specific techniques such as caching, indexing, or batch processing].

Examine this code for [programming language and framework] and assess whether it handles large datasets efficiently. Identify any memory leaks, N+1 query problems, or blocking operations. Suggest alternative approaches that scale better at [expected load].

Analyze the performance characteristics of this [component or module] under [specific conditions]. Check whether resources are released properly, whether connections are pooled, and whether the code implements [optimization technique]. Estimate performance impact on [target environment].

Testing and Coverage Prompts

Testing reviews ensure code changes include proper test coverage.

Review the test coverage for this code change in [project or module]. Identify missing test cases for [scenarios such as edge cases, error conditions, or integration points]. Suggest additional tests that would increase confidence in [specific functionality].

Analyze the test suite for this [feature or component] and evaluate whether tests are meaningful and maintainable. Check for brittle tests, poor assertions, or missing mocks. Recommend improvements to test structure and [testing strategy such as unit, integration, or e2e].

Examine this code and its tests for [programming language]. Verify that tests cover happy paths, error handling, and boundary conditions for [specific functionality]. Identify any untested code paths and suggest test scenarios that would catch [type of bugs].

Review this test implementation for [feature or module] and assess whether it follows [testing best practices or framework conventions]. Check for test independence, proper setup and teardown, and clear test names. Point out any tests that are too slow or fragile.

Error Handling and Logging Prompts

Proper error handling makes code resilient and easier to debug.

Review error handling in this code for [application or service]. Check whether exceptions are caught at appropriate levels, whether error messages are clear, and whether the code fails gracefully. Verify that errors are logged with [required information such as context, stack traces, or user IDs].

Analyze this implementation for [feature or module] and evaluate how it handles failure scenarios. Identify any unhandled exceptions, missing validation, or improper error propagation. Suggest improvements for [specific context such as user experience or system stability].

Examine the logging strategy in this code for [project or component]. Check whether log levels are appropriate, whether sensitive data is redacted, and whether logs provide enough context for debugging. Recommend changes to make logs more useful for [monitoring or troubleshooting].

Review this code for [programming language] and verify that it implements proper error handling for [specific operations such as database access, API calls, or file operations]. Check for resource cleanup in error paths and whether retry logic is appropriate for [failure type].

Documentation Review Prompts

Documentation helps teams understand and maintain code over time.

Review the documentation for this code change in [project or repository]. Check whether inline comments explain complex logic, whether function signatures have clear descriptions, and whether [documentation standard] is followed. Identify any missing or outdated documentation.

Analyze the API documentation for this [service or module]. Verify that endpoints are documented with request and response examples, error codes, and usage notes. Check whether breaking changes are clearly marked and whether [API documentation tool] is updated properly.

Examine this codebase for [project name] and assess the quality of its documentation. Check whether READMEs are current, whether setup instructions work, and whether architecture decisions are recorded. Suggest improvements to help [target audience such as new developers or external contributors].

Review this implementation and verify that it includes appropriate documentation for [specific aspect such as configuration, deployment, or troubleshooting]. Check whether code comments match actual behavior and whether examples are provided for [complex functionality].

Architecture and Design Pattern Prompts

Architecture reviews prevent design problems that are expensive to fix later.

Review the architectural decisions in this code for [system or feature]. Evaluate whether the design follows [pattern or principle] and whether it fits with the overall system architecture. Identify any decisions that could cause problems with [concern such as scalability, maintainability, or testability].

Analyze this implementation of [feature or component] and assess whether it uses appropriate design patterns for [problem or context]. Check whether abstractions are at the right level and whether dependencies are managed properly. Suggest alternative designs if current approach has issues with [specific concern].

Examine this code for [project or module] and evaluate its integration with existing systems. Check whether interfaces are clean, whether coupling is minimized, and whether the design supports [requirement such as extensibility or reusability]. Point out any architectural violations.

Review this system design for [application or service] and analyze how it handles [cross-cutting concern such as configuration, logging, or authentication]. Verify that the approach is consistent with [architectural standard or pattern] and identify any areas where design could be improved.

Database and Data Access Prompts

Database review prompts catch common data access problems.

Review database queries in this code for [application or feature]. Check for SQL injection vulnerabilities, missing indexes, or inefficient joins. Analyze query performance for [expected data volume] and suggest optimizations for [specific bottleneck].

Analyze the data access layer for this [module or service]. Verify that transactions are handled correctly, that connections are managed properly, and that [ORM or database library] is used according to best practices. Identify any potential race conditions or deadlocks.

Examine this database schema change for [project name]. Check whether migrations are reversible, whether indexes are appropriate, and whether the change maintains data integrity. Assess the impact on [existing queries or application performance].

Review this code's interaction with [database type] and verify that it implements proper error handling, connection pooling, and query timeouts. Check whether data validation happens at appropriate layers and whether [data access pattern] is applied correctly.

Code Review Process and Standards Prompts

These prompts help establish consistent review practices across teams.

Create a code review checklist for [team or project] that focuses on [priorities such as security, performance, or maintainability]. Include specific checkpoints for [technology stack or framework] and tailor the checklist to [team size or experience level].

Define code review standards for [programming language or framework] that align with [organizational goals or quality targets]. Specify what reviewers should check for, how feedback should be delivered, and what criteria must be met before approval.

Develop a peer review process for [type of changes such as new features, bug fixes, or refactoring]. Include guidelines on review turnaround time, number of reviewers required, and how to handle disagreements. Make the process work for [team structure or workflow].

Generate a training checklist for new developers joining [team or project]. Cover what to look for during code reviews, common issues in [codebase or technology], and how to provide constructive feedback. Include examples of [good and bad patterns] specific to your context.

Using AI for Code Review Checklist Creation

AI tools can help create custom code review checklists tailored to your project needs. When you provide context about your technology stack, team standards, and quality goals, AI can generate comprehensive checklists that cover all critical areas.

The best code review processes according to Mozilla’s frontend code review guidelines balance thoroughness with efficiency. Teams that use structured checklists catch more bugs while keeping reviews focused and productive.

Different projects need different review approaches. A startup building an MVP might prioritize speed and core functionality, while enterprise teams might enforce strict security and compliance checks. Your code review checklist should reflect your actual priorities and constraints rather than generic best practices.

Common mistakes in code reviews include focusing too much on style issues while missing logic problems, reviewing too much code at once, or not giving feedback that helps developers improve. Checklists keep reviews focused on what matters most for code quality.

The prompts in this library work best when you customize them with specific details about your codebase, coding standards, and team workflow. Replace general placeholders with exact framework names, security requirements, or performance targets relevant to your project.

How to Use These Code Review Checklist Prompts

These prompts are templates that you should adapt for your specific situation. Replace all bracketed placeholders with actual details from your project. For example, change [programming language] to Python or JavaScript, and change [security concerns] to specific threats relevant to your application.

Start with a basic prompt and add more constraints as needed. If the AI response is too general, include more context about your codebase, team standards, or quality requirements. If the response is too detailed, simplify the prompt or focus on one specific aspect of the review.

Test prompts with different levels of detail to find what works for your AI tool and use case. Some tools respond better to structured requests with numbered criteria, while others work well with conversational descriptions of what you need.

Combine multiple prompts when reviewing complex changes. Use one prompt for security analysis, another for performance review, and a third for testing coverage. This approach gives you comprehensive feedback without overwhelming a single prompt with too many concerns.

Save and refine prompts that work well for recurring review scenarios. Build a personal library of prompts customized for your most common code review situations, such as API changes, database migrations, or frontend components.