
WriteGap
Finds what to write, fixes what's ranking, publishes it
What it does
WriteGap finds competitor keyword gaps and unclaimed keywords, fixes your existing pages that are almost ranking, and writes SEO-ready drafts, publishing them straight to WordPress or Shopify. Managed or bring your own API keys.
WriteGap finds the keywords your competitors rank for that you don't, plus the ones nobody's claimed yet — in 46 languages and 241 local markets — then writes the article draft for you.
Then WriteGap writes the article for each one, in 46 languages across 241 local markets. You read it, publish, and watch your position move. Dashboards show you what's possible. WriteGap tells you what to do next — then does it. Paste your URL. WriteGap figures out who you compete with and what you sell. About 2 minutes, once. Every week, a brief lands with your best gaps: competitor keywords, plus unclaimed ones nobody owns yet. WriteGap writes the H1, sections, and schema in your website's own tone, then publishes straight to WordPress or Shopify. Paste any URL. WriteGap audits SEO, conversion, and UX, then hands you copy ready to paste back in. Connect Google Search Console and WriteGap…from writegap.com
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More growth this month
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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 · 16d ago · simedw.com