KeepKnown
The filter builder your Gmail and Outlook should have
What it does
KeepKnown is an advanced filter builder for Gmail and Outlook. Combine relationship, history, header, attachment, subject, and mailbox signals with nested logic; preview rules on real mail; activate in Shadow, Review Only, or Enforce where supported; and trace every match in a decision log. New filters save paused, reusable templates speed up common workflows, and core filtering does not read email bodies.
Build advanced Gmail and Outlook filters with richer conditions, safe previews, staged activation, and a decision log for every match.
Create richer rules, test them on real mail, and see why every message moved. Works with Gmail and Outlook. KeepKnown gives filters a builder, a test bench, and a decision log. Combine sender, contact, domain, subject, header, history, and mailbox signals with nested all, any, and exception logic. Filter by contacts, approved domains, people you replied to, VIPs, and your own sender groups. Keep, move, label, prioritize, hold for review, or add matching mail to a digest. Start with a useful rule, see exactly what it does, then make it yours. Contacts, approved domains, and prior replies stay in your inbox. A previous rescue triggers a sender or domain approval suggestion. KeepKnown helps…from keepknown.com
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AstraPixels▲267A pixel-art solar system at its real current positions.
Growth · 29d ago · astrapixels.com

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