surprisetalk/scrapsheets

AI Summary: Implement a header above the existing column stats in an Elm application to display overall sheet statistics such as file size (MB), number of rows, and load time. This requires adding new UI elements to display these statistics, and potentially fetching the necessary data from the application's backend or data model.

AI Summary: The task is to significantly improve the visual presentation and functionality of a 'stats row' in an Elm application, likely inspired by the example provided (rowboat.xyz). This involves modifying the Elm code (located in the `src` directory) to enhance the user interface of this specific row. The project uses a simple build process involving `elm make` and a `deno` based server for development.

AI Summary: Create a terminal-based user interface (TUI) for the existing Elm application. This involves replacing the current web-based frontend with a TUI, likely using a library like `elm-tui` or a similar alternative. The build process will need to be adapted to output a TUI application instead of a web application.

AI Summary: Add example usage scenarios to a shop application. This involves creating example data and potentially UI elements showcasing features like webforms, daily standups, device management, and integration with various services (Google Sheets, databases, Discord, etc.).

AI Summary: Implement aesthetically pleasing borders similar to those found on the Rows.com product page example. This involves updating the Elm codebase (located in the `src` directory) to incorporate the desired border styles. The provided build script uses `elm make` to compile the Elm code and `deno run` to serve the resulting JavaScript.

AI Summary: The task involves integrating a dataset of US case law (from the Common Pile's Caselaw Access Project) into an existing Elm application. This likely requires downloading the dataset, parsing its structure, and then incorporating it into the application's data model and user interface to allow searching and display of the legal cases.

AI Summary: Modify the Elm code to prevent database queries from executing on every keystroke. Queries should only be triggered when the user explicitly submits or saves their input.

AI Summary: Implement a "click to expand" feature for table cells containing more than 300 characters. This involves modifying the Elm code to truncate long text and add an interactive element to reveal the full content.

AI Summary: Implement keyboard shortcuts for all interactive elements in the Elm application. This involves adding keyboard shortcut functionality to buttons and other interactive elements, displaying these shortcuts on hover or as persistent UI elements.

AI Summary: Integrate a payment gateway (Stripe or similar) to enable users to make purchases within the Elm application. This involves setting up the payment gateway, handling payment processing within the Elm code, and ensuring secure transaction handling.

AI Summary: Implement user authentication features (signup/signin) on a library webpage. Replace the existing "library" breadcrumb with a login/signup button, displaying the username if the user is already logged in. Alternatively, integrate these features into the sidebar.

AI Summary: Improve the user interface for data type selection by replacing the current plaintext input with a dropdown menu. This will enhance discoverability and usability.

AI Summary: Integrate the Carbon ERP codex from the provided GitHub repository into an existing online shop. This involves downloading the codex, understanding its structure, and integrating it into the shop's existing infrastructure. The project uses Elm for frontend development and a Node.js based server for serving the static files.

AI Summary: The task is to improve the aesthetics of an Elm project. This involves modifying the project's codebase to address unspecified visual issues described as 'rapant ugly'. The current build process uses Elm, `cp`, and a Node.js server.

AI Summary: The task involves achieving parity with the Wolfram Knowledgebase. This requires accessing and potentially processing data from two specified Wolfram Cloud Data Repository URLs: one containing categorized data and another containing all data. The provided project uses Elm and a simple build/serve process; the task likely involves integrating the Wolfram data into this Elm application.

AI Summary: This task involves adding a wide variety of common datasets to a shop (likely a data shop or platform). The datasets cover diverse categories including economics, demographics, weather, sports, health, business, education, and geography. The work includes identifying reliable sources for these datasets and integrating them into the shop's system.