SNIPE PDF - Minimalist And Secure PDFs
Free, Private and Secure PDF Reader and Writer
What it does
**SNIPE PDF** Minimalist, open-source reader and writer for Mac, Windows, and Linux. • **Performance:** ~35 MB memory footprint. Instant execution. • **Privacy:** 100% local. Zero cloud connectivity or telemetry. • **Access:** No accounts, subscriptions, or paywalls. • **Utility:** View, annotate, fill forms, and edit. Zero bloat. Zero dependencies.
SNIPE PDF is a fast, minimalist PDF reader and writer with no cloud, no accounts, and no distractions. Download for Mac, Windows, and Linux.
SNIPE PDF is a minimalist reader and writer. No cloud, no accounts, no subscriptions — just open, edit, and save. Launch and read instantly. No login required to view your data. Buy once, use forever. A native tool for your native workflow. We stripped away the bloat so you can focus on your documents. Opens documents instantly. No splash screens, no loading spinners, no waiting. View, annotate, fill forms, and make quick edits without leaving the app. Your files stay on your device. No uploads, no accounts, no tracking. Big-name PDF apps bundle browsers, cloud sync, AI assistants, and stores you never asked for. Then they eat your RAM and ask for a subscription to unlock basic features.…from snipe-your-pdfs.lovable.app
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Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io
- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com