1. Write Clear, Specific Prompts
The quality of your output directly depends on the clarity of your input. Vague prompts lead to generic responses, while specific prompts yield precise, actionable code.
Examples:
- ❌ Bad: "Write a function to process data"
- ✅ Good: "Write a JavaScript function that validates email addresses using regex, handles edge cases like '+' in local part, and returns both validation status and error messages"
2. Provide Context and Examples
Claude Code performs better when you supply relevant context. Show examples of what you want, existing code structures, or related implementations.
- Share relevant code snippets or file structures
- Include examples of desired output format
- Mention project constraints (performance, compatibility, style guides)
- Reference existing patterns in your codebase
3. Use the Right Level of Detail
Balance is key—too much detail overwhelms Claude, too little creates ambiguity.
- For simple tasks: Brief, direct prompts work best
- For complex tasks: Break down into smaller sub-tasks
- For code review: Specify what aspects to focus on (performance, security, readability)
- For refactoring: Explain the goal, not just "make it better"
4. Leverage Plan Mode for Complex Tasks
Use /launch-plan before tackling complex problems. This gives you a structured approach before committing to changes:
- Get a detailed breakdown of the implementation strategy
- Review architectural decisions upfront
- Identify potential issues before starting
- Plan out the order of changes
5. Ask for Explanations and Documentation
Don't just ask for code—ask Claude Code to explain its reasoning:
- Request comments for complex logic
- Ask why certain approaches were chosen over alternatives
- Request documentation for new functions or modules
- Ask for potential gotchas or edge cases to watch for
6. Iterate and Refine
Great prompts aren't written once—they're refined through iteration:
- Start with a general prompt, then narrow based on results
- Ask follow-up questions to improve specific aspects
- Use feedback from generated code to refine your next prompt
- Save good prompt patterns for future reuse
7. Use Specific, Measurable Criteria
When asking for improvements, be specific about what "better" means:
- Performance: "Reduce execution time by at least 50%" or "Handle 100,000 items in under 1 second"
- Readability: "Follow Google Python style guide" or "Make variable names self-documenting"
- Security: "No SQL injection vulnerabilities" or "Sanitize all user inputs"
- Coverage: "Write tests that achieve 90% code coverage"
8. Leverage Agents for Research-Heavy Tasks
For tasks that require investigation or research, use agents with /launch-agent:
- Let agents explore your codebase independently
- Perfect for understanding existing implementations before making changes
- Great for complex refactoring across multiple files
- Ideal when you need investigation before implementation