Original Summary

Hey r/SideProject , long-time lurker. My LinkedIn feed filled up with engagement bait, "I turned down a 7-figure offer at 24" stories, and furthermore-flavored wisdom (yes, "furthermore"; Graphite's research clocked "furthermore the" at 43x the human rate, and my feed agrees). So I built Slop Mop: a free, open-source Chrome extension for desktop LinkedIn that reads posts before you see them and either folds suspected slop into a strip or highlights it. You set the threshold. Formally: Slop Mop helps desktop LinkedIn users identify and reduce AI slop and other low-value writing while keeping the reader in control. The part I'm proudest of: it's not an AI detector, it's a bad-writing detector. Each post gets eleven questions from Jev (a decision-probability model from Typesafe AI): nine writing signs associated with slop, plus two counter-signals asking whether it sounds like a person and whether it's actually useful to readers. A useful post survives the mop no matter how it was written. Nothing gets deleted, muted, or reported. The filter is local, it shows its work, and you can override any call. It's also a small experiment in economics. Jev's inference is cheap enough to judge every post as you scroll, continuously, for free. No account, no API key, MIT licensed. It's live on the Chrome Web Store as of today: one-click install, no sideloading. Honest question for the room: where do you think a writing judge like this gets posts wrong? I want the embarrassing examples. https://slopmop.lol   submitted by   /u/tom_reddit [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/24 01:23:10