Automate AI Prompts with Claude Code Custom Commands

Learn how Claude Code custom commands eliminate prompt repetition and standardize AI workflows. Complete tutorial with examples, $ARGUMENTS usage, and team implementation strategies.

Every Claude Code user knows this frustration: writing the same detailed prompts over and over. "Perform a code review following our team standards..." "Generate tests using Jest and React Testing Library..." "Analyze this architecture for DDD compliance..." The repetition kills productivity and creates inconsistent results across your team.

Claude Code's custom commands solve this by letting you save your best prompts as reusable commands. Think of them as prompt templates that you can call instantly, ensuring consistency and saving massive amounts of time.

Setting Up Your First Command

Custom commands live in your project structure. Here's the simple setup:

Find (or create) the .claude folder in your project root
Create a commands directory inside it
Add markdown files for your commands

The filename becomes your command name. Create code_review.md and you get the /code_review command.

Here's a sample of a code review command:

Perform a comprehensive code review focusing on:

# Technical Quality
- Architecture patterns and best practices
- Performance and security considerations
- Error handling and edge cases
- Code readability and maintainability

# Team Standards
- Naming conventions and style guide compliance
- Documentation completeness
- Test coverage adequacy

# Output Format
Provide findings in order of priority:
1. Critical issues (bugs, security, breaking changes)
2. Performance concerns
3. Improvements for maintainability
4. Style and convention fixes

Include specific suggestions with reasoning for each recommendation.

After creating commands, restart Claude Code to register them.

Making Commands Dynamic with Arguments

The real power comes from $ARGUMENTS - this placeholder gets replaced with whatever you type after the command. This transforms static templates into flexible tools.

Create a new_endpoint.md command:

# API Endpoint Generator for: $ARGUMENTS

Create a complete REST API endpoint following our project standards:

## Implementation Requirements
- Express.js with TypeScript
- Input validation using Joi schemas
- Proper error handling with standardized responses
- OpenAPI documentation comments
- Unit tests with Supertest

## Code Structure
- Route handler in `/routes` directory
- Business logic in `/services` layer
- Data models in `/models` with proper typing
- Middleware for authentication if needed

## Quality Standards
- Include request/response TypeScript interfaces
- Add comprehensive error scenarios
- Implement proper HTTP status codes
- Follow RESTful naming conventions

Generate the complete endpoint with all supporting code.

Now /new_endpoint user registration creates a signup API, while /new_endpoint product search builds a search endpoint with filters.

Working Around File Reference Limitations

Custom commands can't use @ file references. The solution is to design commands that ask for context first, then proceed with the task.

Instead of trying to reference files directly, create interactive commands:

Your goal is to create comprehensive API documentation.

# First Step: Gather Information
Ask me to provide the specific API endpoints or code files you need to document. I'll share the relevant files after you request them.

# Documentation Requirements
Once you have the code:
- OpenAPI 3.0 format
- Complete endpoint descriptions
- Request/response examples
- Error handling documentation
- Authentication requirements

Don't start documenting until you have all necessary code and context.

This approach ensures you get all the context needed while working within command limitations.

Team Standardization Benefits

The biggest advantage is team consistency. Create commands for your common workflows:

DDD Architecture Review (/ddd_review):

# Domain-Driven Design Validation

Analyze the provided code for DDD compliance: $ARGUMENTS

Check for:
- Proper bounded contexts
- Aggregate design patterns
- Domain vs application services
- Repository pattern implementation
- Value object immutability

Provide a compliance score (1-10) with specific improvement recommendations.

Technical Specification (/create_spec):

# Technical Specification Generator

Your objective is to produce a complete technical specification.

## Information Gathering Phase
First, ask me detailed questions about the specification requirements. I'll provide the necessary information for you to understand the scope and context.

Then, ask any additional clarifying questions needed before starting the specification.

Do not begin writing until everything is clear.

## Specification Rules
- Never write real code, only pseudo-code when necessary
- Use Mermaid diagrams to enhance understanding
- Keep explanations concise and clear
- Include a complete implementation roadmap at the end

## Final Deliverable
Save the completed specification as a Markdown file.

If you get stuck or need guidance, ask me questions to stay on track.

These commands ensure every team member applies identical standards, eliminating subjective interpretations and maintaining quality consistency.

Why This Matters

Custom commands transform Claude Code from a chat interface into a standardized development toolkit. Your team builds a library of proven prompts that:

Eliminate repetitive prompt writing
Ensure consistent quality standards
Scale expertise across team members
Create reusable organizational knowledge

The most successful teams treat commands as infrastructure investments. Start with your most frequently repeated prompts, then expand your command library over time.

Custom commands represent the evolution from ad-hoc AI conversations to systematic development automation. They turn prompt engineering into a team asset that improves with every project.

To go further: