10 Prompts for Claude Code: From Refactoring to Architecture

10 Prompts for Claude Code: From Refactoring to Architecture

Claude Code is an AI-powered coding assistant developed by Anthropic, designed to integrate directly into your development workflow. Unlike general-purpose chatbots, Claude Code operates within your terminal, understands your codebase, and can execute commands, read files, and suggest changes. As of 2026, it has become a staple tool for many software engineering teams, offering capabilities that range from simple code generation to complex architectural planning.

This article provides a curated collection of 10 practical prompts for Claude Code, organized by task category: code review, refactoring, and system architecture. Each prompt is designed to be copy-paste ready, with an explanation of its use case and a concrete example. Whether you are a seasoned developer or just starting with AI-assisted coding, these prompts will help you get the most out of Claude Code.

Why Use Structured Prompts for Claude Code?

Claude Code is powerful, but like any AI tool, the quality of its output depends heavily on the quality of your input. A vague prompt like "refactor this code" often yields generic suggestions. A structured prompt, on the other hand, provides context, constraints, and a clear goal. This leads to actionable, specific, and safe results.

Structured prompts also help you maintain control over the AI's behavior. By specifying what you want (e.g., "improve performance without changing the public API") and what you do not want (e.g., "do not add new dependencies"), you reduce the risk of unintended changes.

Code Review Prompts

Code review is one of the most common use cases for Claude Code. Instead of manually scanning every line, you can use these prompts to get a focused analysis.

1. Security Vulnerability Scan

Task: Identify potential security vulnerabilities in a given code snippet or file.

Prompt:

Perform a security audit on the following code. List any potential vulnerabilities, including SQL injection, cross-site scripting (XSS), insecure deserialization, hardcoded credentials, and improper error handling. For each issue, provide a brief explanation and a suggested fix.
[Paste your code here]

Example:

If you paste a Python Flask endpoint that concatenates user input directly into a SQL query, Claude Code will flag the SQL injection risk and suggest using parameterized queries or an ORM.

Why it works: The prompt explicitly lists common vulnerability types, guiding the AI to look for specific patterns. The request for "suggested fix" ensures the output is actionable.

2. Performance Bottleneck Detection

Task: Find performance issues like unnecessary loops, redundant database calls, or inefficient algorithms.

Prompt:

Review the following code for performance bottlenecks. Focus on:
- Time complexity (e.g., O(n²) loops)
- Redundant API or database calls
- Memory leaks or excessive memory allocation
- Unnecessary object creation
For each issue, suggest an optimized alternative.
[Paste your code here]

Example:

A developer submits a function that fetches user data in a loop, making N+1 database queries. Claude Code will detect this and suggest using a batch query or eager loading.

3. Code Style and Best Practices Compliance

Task: Ensure code follows a specific style guide (e.g., PEP 8 for Python, Airbnb style for JavaScript).

Prompt:

Review the following code against the [PEP 8 / Airbnb / Google Style Guide]. List all style violations, including:
- Naming conventions
- Indentation and spacing
- Line length
- Imports ordering
- Docstring presence and format
Provide the corrected lines.
[Paste your code here]

Example:

A Python file with mixed camelCase and snake_case will be flagged, and Claude Code will rename variables to match PEP 8.

Refactoring Prompts

Refactoring improves code structure without changing its external behavior. These prompts help you safely modernize or simplify your codebase.

4. Extract Method / Function

Task: Break a long, complex function into smaller, reusable functions.

Prompt:

Refactor the following function by extracting reusable logic into separate helper functions. The original function should become a composition of these helpers. Preserve all existing behavior and keep the public API unchanged. Use meaningful names for the new functions.
[Paste your code here]

Example:

A 200-line function that handles user registration, validation, and email sending can be split into validate_user_input(), create_user_record(), and send_welcome_email(). The main function then calls these in sequence.

5. Replace Conditional with Polymorphism

Task: Simplify complex if-else or switch statements using polymorphism or strategy pattern.

Prompt:

Refactor the following code to replace conditional logic with polymorphism or the strategy pattern. Create appropriate classes or interfaces. The external interface of the module should not change.
[Paste your code here]

Example:

A function that calculates shipping cost based on a string "ground", "air", or "sea" can be refactored into a ShippingStrategy interface with concrete implementations for each shipping type.

6. Remove Duplicate Code

Task: Eliminate code duplication across multiple files or functions.

Prompt:

Identify and remove duplicate code in the following project files. Extract the duplicated logic into a shared utility function or module. List all files that were changed and explain the refactoring.
[Paste your project structure or multiple files]

Example:

If validation logic for email addresses appears in three different controllers, Claude Code will suggest a validate_email() function in a shared utils.py file.

Architecture Prompts

Architecture-level prompts help you design new systems or evaluate existing ones. These are particularly useful during planning phases or major rewrites.

7. System Design Evaluation

Task: Evaluate a proposed system architecture for scalability, reliability, and maintainability.

Prompt:

Evaluate the following system architecture description. Identify potential bottlenecks, single points of failure, and scalability limitations. Suggest improvements using established patterns (e.g., CQRS, event sourcing, microservices, or load balancing). Provide a revised architecture diagram in text form.
[Paste your architecture description or diagram]

Example:

A monolith with a single database for both reads and writes can be flagged for read scalability issues. Claude Code might suggest adding a read replica or migrating to CQRS.

8. API Design Review

Task: Review a REST or GraphQL API design for consistency, completeness, and best practices.

Prompt:

Review the following API specification. Check for:
- Consistent naming conventions (e.g., plural nouns for REST endpoints)
- Proper HTTP method usage (GET for reads, POST for creates, etc.)
- Appropriate status codes
- Pagination and filtering support
- Error response structure
List any violations and suggest corrections.
[Paste your OpenAPI / Swagger spec or endpoint list]

Example:

An endpoint like /getUser?id=123 will be flagged as non-RESTful, with a suggestion to use /users/123.

9. Database Schema Normalization

Task: Evaluate a database schema for normalization and performance.

Prompt:

Analyze the following database schema. Identify:
- Redundant columns
- Missing indexes
- Violations of normalization (2NF, 3NF)
- Potential join performance issues
Suggest a revised schema with explanations.
[Paste your CREATE TABLE statements]

Example:

A table with user_name and user_email repeated in an orders table will be flagged for denormalization. Claude Code will suggest splitting into separate users and orders tables.

10. Microservices Decomposition

Task: Break a monolithic application into microservices.

Prompt:

Given the following monolith application description, propose a microservices decomposition. For each proposed service, define:
- Responsibility and bounded context
- API endpoints
- Data ownership (which database each service owns)
- Inter-service communication pattern (sync via HTTP/gRPC or async via message queue)
- Potential challenges and mitigation strategies
[Paste your monolith description]

Example:

An e-commerce monolith can be decomposed into Product Service, Order Service, Payment Service, and Notification Service. Claude Code will outline how they communicate, e.g., Order Service emits an event when an order is placed, which Payment Service consumes.

Best Practices for Using Claude Code Prompts

To get the most out of these prompts, follow these guidelines:

1. Provide context. Always include the relevant code or description. The more specific you are, the better the output.
2. Set constraints. Mention what you do not want to change (e.g., "do not change the public API") to avoid unwanted modifications.
3. Iterate. The first output may not be perfect. Use follow-up prompts like "Simplify this further" or "Add error handling."
4. Review manually. Never blindly accept AI suggestions. Always review changes, especially for security-critical code.
5. Use version control. Before applying any refactoring, commit your current state so you can revert if needed.

Conclusion

Claude Code is a versatile tool that can significantly boost your productivity across code review, refactoring, and architecture design. The key is to use structured prompts that provide clear goals and constraints. The 10 prompts in this article are a starting point — adapt them to your specific projects and coding standards.

Remember that AI is a collaborator, not a replacement for human judgment. Use these prompts to accelerate your work, but always apply your expertise to validate the output. With practice, you will develop a prompt library that saves you hours of manual work every week.

Start by trying one prompt today. Pick a piece of code you have been meaning to review or refactor, and see what Claude Code suggests. You might be surprised at how much time you can save.