Cursor Documentation and AI Rule Customization

Hello everyone, today we will learn about the documentation generation feature of the Cursor code editor and how to customize AI behavior and rules. We will cover practical tips and examples for documentation generation, as well as methods for customizing AI behavior and common application scenarios.

Documentation Generation: Key to Improving Project Maintainability

1. Practical Tips

• Generating Readme Files in the Early Stages of a Project: When creating a project, using Cursor to generate a detailed Readme file is a great start.
• For example, when developing a Node.js based web application, entering the command ‘Generate Readme file for the project’ will prompt Cursor to generate a document containing detailed information such as project goals, functional descriptions, usage methods, and dependency information based on the content of the code repository.
• This helps other developers quickly understand the overall situation of the project.
• Code Comment Generation: Asking Cursor to automatically add clear comments when generating code is also an important way to improve code readability.
• For example, when Cursor generates a function in Python, it can add comments according to certain standards, such as the function’s purpose, the meaning of input parameters, and return values. Here is a simple example of a Python function:

def calculate_area(radius):
    """
    This function calculates the area of a circle.
    :param radius: The radius of the circle, which is a numeric type.
    :return: The area of the circle, calculated using the formula S = π * radius * radius.
    """
    import math
    area = math.pi * radius * radius
    return area

1. Significance

• The documentation generation feature is crucial for the maintainability of a project. Throughout the project’s lifecycle, whether for the developer’s own maintenance or collaboration among team members, clear documentation can help quickly understand the functionality and logic of the code.
• Moreover, as the project continues to develop, Cursor can automatically update the Readme file based on the content of the code repository, ensuring consistency between the documentation and the code.

Customizing AI Behavior and Rules: Meeting Personalized Needs

1. Rules for AI Feature

• Setting Paths and Methods: Cursor allows developers to customize AI behavior through the Rules for AI feature. This functionality can be found in Cursor’s settings, following the path: Settings > General > Rules for AI.
• In the rules editing box, developers can input various custom rules. For example, requiring the AI to prioritize generating code in a specific language (such as Java) or to follow a certain design pattern (like the MVC pattern).
• Saving and Applying Rules: After completing the rule configuration, click save, and the AI will adjust its behavior according to the new rules. For instance, if a rule is set requiring the AI to respond in Chinese, the AI’s answers will be presented in Chinese when interacting with Cursor.

• Adhering to Coding Standards: In team development, the AI can be required to follow specific coding styles or team naming conventions. For instance, in a Python team, the AI can be asked to generate code following the PEP 8 style guide, ensuring consistency in the team’s code style.
• Matching Technology Stack Preferences: For specific projects, the AI can be instructed to prioritize generating code that matches the project’s technology stack. For example, in a project where React.js is the front-end framework, the AI can be asked to prioritize generating code components related to React.js.
• Performance Optimization Orientation: Allowing the AI to generate more efficient algorithms or code implementations. For example, in projects dealing with large data sets, the AI can be instructed to use more efficient algorithms to process data, such as using NumPy’s vectorization operations in Python instead of regular loop operations.

• In addition to the Rules for AI feature, Cursor also supports further customization of AI behavior through the .cursorrules file. Developers can adjust the AI’s working methods according to personal habits and project requirements.
• For example, this file can define how specific code snippets are handled or set the AI’s default actions in certain situations. If you want the AI to always check if the connection is available when handling database queries, you can write the corresponding rules in the .cursorrules file.

Considerations

1. Accuracy and Completeness of Documentation Generation

• Although Cursor’s documentation generation feature is powerful, it should not be completely relied upon without manual checks. Sometimes the generated documentation may have accuracy issues, such as unclear or incorrect explanations of complex business logic.
• After generating Readme files or code comments, developers need to carefully check and make necessary modifications to ensure that the documentation accurately and completely reflects the functionality and logic of the code.

• When customizing AI behavior and rules, attention must be paid to the compatibility of the rules. Some rules may conflict with each other, causing the AI to malfunction or produce unexpected results.
• For example, setting rules that require the AI to generate code according to two conflicting design patterns may lead to issues. When setting rules, carefully consider the relationships between them to ensure they can work together.

End

The documentation generation feature of Cursor and the ability to customize AI behavior and rules provide developers with rich development assistance tools. Documentation generation helps improve project maintainability, while customizing AI behavior meets various personalized needs.

If you have any questions or suggestions, feel free to leave a message in the comments section!