docs/usage/prompting/prompting-best-practices.mdx

---
title: Prompting Best Practices
description: When working with OpenHands AI software developer, providing clear and effective prompts is key to getting accurate and useful responses. This guide outlines best practices for crafting effective prompts.
---

## Characteristics of Good Prompts

Good prompts are:

- **Concrete**: Clearly describe what functionality should be added or what error needs fixing.
- **Location-specific**: Specify the locations in the codebase that should be modified, if known.
- **Appropriately scoped**: Focus on a single feature, typically not exceeding 100 lines of code.

## Examples

### Good Prompt Examples

- Add a function `calculate_average` in `utils/math_operations.py` that takes a list of numbers as input and returns their average.
- Fix the TypeError in `frontend/src/components/UserProfile.tsx` occurring on line 42. The error suggests we're trying to access a property of undefined.
- Implement input validation for the email field in the registration form. Update `frontend/src/components/RegistrationForm.tsx` to check if the email is in a valid format before submission.

### Bad Prompt Examples

- Make the code better. (Too vague, not concrete)
- Rewrite the entire backend to use a different framework. (Not appropriately scoped)
- There's a bug somewhere in the user authentication. Can you find and fix it? (Lacks specificity and location information)

## Tips for Effective Prompting

- Be as specific as possible about the desired outcome or the problem to be solved.
- Provide context, including relevant file paths and line numbers if available.
- Break large tasks into smaller, manageable prompts.
- Include relevant error messages or logs.
- Specify the programming language or framework, if not obvious.

The more precise and informative your prompt, the better OpenHands can assist you.

See [Getting Started with OpenHands](../getting-started) for more examples of helpful prompts.