To enhance the effectiveness of the AI coding assistant and ensure a smooth user experience throughout the software development process, we can integrate the suggested improvements and additional prompts into the existing framework. Below is the refined list of prompts, incorporating clarity, progress tracking, user feedback, and other enhancements: ### General Prompts for AI Coding Assistant 1. Project Initialization: - "Create a new software project named [Project Name] in the designated folder [Folder Path]. Set up the initial file structure with folders for [list of folders, e.g., src, tests, assets]." 2. Code Generation: - "Generate a [specific programming language] function that [describe the function's purpose, e.g., calculates the sum of two numbers]. Ensure the code follows best practices and includes comments for clarity." 3. File Creation: - "Create a new file named [File Name] in the [Folder Name] folder. This file should contain [brief description of the content, e.g., a class definition, a module, etc.]." 4. Real-Time Code Review: - "As you generate code for [specific feature or functionality], please explain each step and the reasoning behind your choices. Highlight any potential issues or improvements." 5. User Interface Development: - "Design a simple user interface for [describe the application, e.g., a to-do list app] using [specific framework or library, e.g., React, Vue]. Provide the code for the main components and explain how they interact." 6. Integration with Open-Source Services: - "Integrate the project with [specific open-source service, e.g., GitHub]. Use the following credentials: [insert credentials]. Ensure that the integration allows for [describe functionality, e.g., version control, issue tracking]." 7. Testing and Debugging: - "Generate unit tests for the [specific function or module] to ensure its correctness. Include edge cases and explain the testing strategy used." 8. Live Preview Feedback: - "As you develop the software, provide a live preview of the UI in the Software Preview tab. Allow me to interact with the preview and give feedback on any changes needed." 9. Documentation Generation: - "Create documentation for the project, including an overview, installation instructions, and usage examples. Ensure it is clear and easy to follow." 10. Final Review and Deployment: - "Before finalizing the project, conduct a review of the codebase for any potential improvements or optimizations. Once reviewed, provide instructions for deploying the software to [specific platform, e.g., Heroku, AWS]." ### Suggested Improvements 1. Clarification Prompts: - "Could you please clarify what you mean by [specific term or request]? This will help me generate the most accurate code." 2. Progress Tracking: - "Provide a summary of the current project status, including completed features and any outstanding tasks." 3. Version Control Prompts: - "Create a new branch in the GitHub repository for the current feature development. Name the branch [Branch Name] and ensure all changes are committed." 4. Code Refactoring: - "Review the existing code for [specific module or function] and suggest any refactoring opportunities to improve readability and maintainability." 5. User Feedback Integration: - "After generating the code for [specific feature], please let me know if there are any changes or improvements you would like to see." ### Additional Prompts 1. Dependency Management: - "Identify and install any necessary dependencies for the project using [specific package manager, e.g., npm, pip]. Provide a brief explanation of each dependency's purpose." 2. Environment Setup: - "Set up the development environment for the project, including any required configurations for [specific IDE or tools]. Provide instructions for other users to replicate the setup." 3. Code Style Guidelines: - "Adhere to [specific coding style guide, e.g., PEP 8 for Python] when generating code. Please explain how the code complies with these guidelines." 4. Performance Optimization: - "Analyze the performance of the current implementation of [specific feature] and suggest optimizations to improve efficiency." 5. Deployment Automation: - "Create a deployment script that automates the process of deploying the application to [specific platform]. Include instructions for running the script." 6. User Authentication: - "Implement user authentication for the application using [specific method, e.g., OAuth, JWT]. Provide the necessary code and explain how it works." ### Conclusion By incorporating these enhancements and additional prompts, the AI coding assistant can provide a more interactive, user-friendly experience. This structure encourages clarification, tracks progress, integrates user feedback, and emphasizes best practices, ultimately guiding users effectively through the software development process.