Tinydot vs GituU

tinydot turns a folder into a website. A blog, a wiki, docs for a project, a portfolio, a page for anything: drop files into the folder and they're live at yourname.tinydot.com, or at a domain you already own. HOW IT WORKS • Create a site and a real folder appears in Finder (Files on iPhone and iPad) • Drag files in and they're live. Edit one and the site updates. Move it and the site follows • No builder, no deploy step, nothing to publish WHAT BECOMES A PAGE • Markdown becomes pages. Images, video and audio play inline • Code renders with syntax highlighting, PDFs get a viewer, CSVs become tables • Everything else becomes a clean download • Pick a theme, or add your own CSS on top of it WRITE LIKE A WIKI • Link pages with [[wikilinks]] and each page shows what links back • Tag with #hashtags. Mark a file draft and it stays hidden until you're ready • It's plain Markdown, so a notes folder or an Obsidian vault publishes as it is YOUR ADDRESS • Every site gets yourname.tinydot.com the moment you create it • Bring your own domain and point it at your site with one DNS record • HTTPS is issued automatically and renews itself YOUR FILES • The site is a folder on your Mac, iPhone and iPad. It syncs like iCloud Drive, in Finder and in Files • Leave any time and take the whole site with you: there is nothing to export INCLUDED • RSS, sitemap, search and social previews • Keep a site private with sign-in, or invite people to edit • tinydot is free • Terms of Use (EULA): https://www.apple.com/legal/internet-services/itunes/dev/stdeula/

In an era of rapid AI development, transparency and authenticity in coding are more important than ever. GituU is a powerful developer tool designed to detect AI-generated code patterns within any GitHub repository using state-of-the-art on-device Machine Learning. Whether you are a recruiter verifying a candidate's project, a student learning code structure, or a developer auditing your own work, GituU provides deep insights into the origin of code patterns with just a few taps. Key Features: Dual Search Modes: Search for repositories directly via keywords or paste a specific GitHub URL for a deep-dive analysis. Comprehensive ML Analysis: Our model scans code files, commit history, and directory structures to determine the likelihood of AI generation. Detailed Score Breakdown: Get a transparent look at how the AI Score is calculated, including individual ratings for code patterns, commit styles, and project structure. Visual Pattern Recognition: Use our intuitive "Human vs. AI" slider and radial progress indicators to understand repository authenticity at a glance. On-Device Privacy: Analysis is powered by high-performance on-device ML models, ensuring your data remains private and the detection is lightning-fast. Beautiful, Minimalist UI: Designed with a clean, modern interface that makes navigating complex repository data easy and accessible.