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.cursorrules Cursor AI WordPress Draft MacOS prompt file

This project is called PressThat.
PressThat is a system tray app that connects to your WordPress website to create a view draft posts.

After first installing the app, you need to configure it with your website details. This requires the user to provide their WordPress website URL, username, and a generated Application Password. Users can generate an Application Password in their WordPress dashboard at the bottom of the "Users -> Profile" page. This password is unique and can be easily revoked at any time.

Here's a quick flow for how the new user experience (NUX) will work:

The user downloads, installs, and opens the app.
The app does an initial check to see if the user has previously configured the app. (For users who have previously configured the app, the app will skip the welcome screen and go straight to step 4.)
The welcome screen is shown asking for the website URL, username, and Application Password. This screen can also explain how the app works, and how to generate an Application Password.
The app tests the connection details and shows a message if the connection failed.
Upon successful connection an initial sync of (up to 20) drafts is performed. This stores the title, date, featured image, and excerpt for each draft.
A new menu bar (on MacOS, status bar on Windows, system tray on Linux) icon appears. The icon is a stylized "P" with a subscript number indicating the number of draft posts.
Clicking the icon show's the main app interface, which resemebles a cross between a deck of cards and a spreadsheet. The app uses a combination of cards and tables to display the draft posts, with the most recent posts appearing at the top of the deck.

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.cursorrules Cursor AI WordPress Draft MacOS prompt file

Shaun Andrews

0

NEW

Linux NVIDIA CUDA Python .cursorrules prompt file

1. **Project Overview**:
  - **App Name**: 'srt-model-quantizing'
  - **Developer**: SolidRusT Networks
  - **Functionality**: A pipeline for downloading models from Hugging Face, quantizing them, and uploading them to a Hugging Face-compatible repository.
  - **Design Philosophy**: Focused on simplicity—users should be able to clone the repository, install dependencies, and run the app using Python or Bash with minimal effort.
  - **Hardware Compatibility**: Supports both Nvidia CUDA and AMD ROCm GPUs, with potential adjustments needed based on specific hardware and drivers.
  - **Platform**: Intended to run on Linux servers only.

2. **Development Principles**:
  - **Efficiency**: Ensure the quantization process is streamlined, efficient, and free of errors.
  - **Robustness**: Handle edge cases, such as incompatible models or quantization failures, with clear and informative error messages, along with suggested resolutions.
  - **Documentation**: Keep all documentation up to date, including the README.md and any necessary instructions or examples.

3. **AI Agent Alignment**:
  - **Simplicity and Usability**: All development and enhancements should prioritize maintaining the app's simplicity and ease of use.
  - **Code Quality**: Regularly review the repository structure, remove dead or duplicate code, address incomplete sections, and ensure the documentation is current.
  - **Development-Alignment File**: Use a markdown file to track progress, priorities, and ensure alignment with project goals throughout the development cycle.

4. **Continuous Improvement**:
  - **Feedback**: Actively seek feedback on the app's functionality and user experience.
  - **Enhancements**: Suggest improvements that could make the app more efficient or user-friendly, ensuring any changes maintain the app's core principles.
  - **Documentation of Changes**: Clearly document any enhancements, bug fixes, or changes made during development to ensure transparency and maintainability.

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