The Vanilla Framework is a CSS framework and design system built with Sass, providing reusable UI components, utilities, and patterns for building responsive and accessible web interfaces. It includes a documentation site (built with Flask) that showcases the components and provides usage guidelines. The framework is organized into modular Sass partials for base styles, utilities, and components, with optional JavaScript for interactive elements. The documentation site reads YAML configuration for navigation and feature status, and the framework itself is intended to be imported into web projects via Sass or standalone CSS builds.
NeoPass is a browser extension designed to assist students during online exams by bypassing restrictions (tab switching, pasting, screenshare) and providing AI-powered answer assistance. It employs a Manifest V3 architecture with a background service worker, content scripts injected into exam platforms, and a popup UI for configuration. Key features include automatic code typing, MCQ solving, a stealth-mode chatbot, and anti-detection measures to avoid identification by exam portals. The extension supports both a free mode (requiring user-configured API keys) and a Pro mode via a managed backend service.
The exifLooter is a command-line application written in Go that extracts EXIF metadata, particularly GPS coordinates, from image files. It relies on the external exiftool command-line utility to perform the actual metadata extraction and provides a user-friendly interface for analyzing single images, directories of images, or images downloaded from URLs via stdin. The tool also offers functionality to remove all metadata from images and to generate OpenStreetMap URLs from GPS coordinates found in images. The architecture is a standard CLI tool built using the Cobra library for command parsing and the fatih/color library for colored terminal output. The main entry point is in main.go, which delegates to the command defined in cmd/root.go. The core functionality involves invoking exiftool via os/exec, parsing its output to detect GPS-related tags, and presenting the results with color-coded warnings when geolocation data is detected. Additional features include downloading images from URLs (with validation of content type) for batch processing in a pipe mode. While the tool fulfills its intended purpose, the codebase exhibits some areas for improvement: the pipe mode's image validation step is inefficient (rescanning the entire directory for each download), the OpenStreetMap URL generation function incorrectly handles southern and western hemisphere coordinates, and there is a lack of automated tests. Despite these issues, the project is actively maintained with recent commits and uses dependency management via Go modules.
This repository is primarily a large collection of GPT prompt templates (markdown files) designed for use with AI chat platforms like FlowGPT or gptcall.net. Each prompt file defines a specific role or task for the AI, such as a resume editor, coding tutor, fitness planner, or creative writing assistant. The repository also includes an Android application (OpenClaw and Codex) referenced in the README, along with Node.js scripts (update.mjs, db.mjs) for managing the prompt data. The prompts are structured with placeholders for user input and often request specific output formats, enabling users to import them into chat interfaces to obtain specialized AI behavior without crafting prompts from scratch. While the prompt library is extensive, it contains significant duplication, minimal-effort entries, and some policy-risking content (e.g., jailbreaks, NSFW role-play), which affects overall quality and reuse potential.