A feed is a stream of posts you did not choose. A feed filter reads each one and decides whether to show it, hide it, blur it or label it. The rule is often fuzzy, such as engagement bait, sponsored, or low value, which is hard to write as code. A decision model takes the rule in plain words and returns a typed answer with a confidence value for each post. The examples in this hub run on Jev and other decision models, and Laya appears in some. Most are browser extensions. Examples include Your Signal by Fabio Angela, which scores posts on your X feed and applies your own rules locally, trungdq88/youtube-sponsor-detection, and ragelink/firehose-judge for the Bluesky firehose. Before you copy one, check what post text leaves your browser, whose API key it uses, whether the filtering is reversible, and how it treats posts it is unsure about. Because filters run on every post, small mistakes show up often, so look at how each one lets you undo them.
12 entries
Showing 12 of 12
A Chrome extension and small web app that find sponsor reads in a YouTube video's transcript using Jev, then skip or flag them; needs a TypeSafe key and, for some modes, a Deepgram key.
Tony Dinh (@tdinh_me)Opentrungdq88/youtube-sponsor-detection on github.com95 starsTranscript mode under 1 cent/hrListen mode ~$0.46/hr
An open source, bring-your-own-key browser extension that scores posts already on your X feed with Jev, then applies your own rules locally. Reversible, with no telemetry.
Chromium extension that flags AI-slop writing style on X, LinkedIn and Reddit using a local Laya-MLX helper for detection.
Code-Wizard-WilsonOpenSlop Finder on github.com
Judges the live Bluesky firehose post by post with Jev on Cloudflare Durable Objects, routing low-confidence calls to a human review lane.
A Chrome extension that sends LinkedIn feed post text to Jev with a rubric of narrow yes/no and rating questions, then blurs posts it scores as low value, with one-click reveal.
A free tool where Jev reads 3 days of posts from a chosen niche, asks 8 questions per post to filter out bait and hidden ads, and weighs like/reply/repost ratios, running in about 2 seconds for $0.007.
Rob Hallam (@robj3d3)OpenA feed filter that scores posts by niche with Jev (X) on x.com176k viewsPer run ~2s, $0.007Questions/post 8
A simulation of the X ranking algorithm built with Jev, using real ranking weights to simulate a post's virality against a global feed of other users.
A browser extension that hides or collapses X posts by a natural-language rule, using Jev to judge each post fast enough that the filtering is not noticeable while scrolling.
Marcel Pociot 🧪 (@marcelpociot)85k viewsOpenA browser extension that filters X posts with Jev (X) on x.com
A video demo of Jev tagging X posts in real time as breaking, a golden nugget, or slop.
A video demo uses Jev to filter out low-quality reply comments on X that the platform's own filters miss, built in about 5 minutes with Astra and an API key.
Ian Nuttall (@iannuttall)OpenFiltering unwanted X replies (X) on x.com18k viewsBuild time ~5 min
A Chrome extension that labels every X post on the timeline as clean, engagement bait, promo, secondhand or filler, at $0.03 per 1,000 posts; open source.
Classifies a LinkedIn post into one of eleven species, such as humblebrag or fake epiphany, using Jev. Posts are processed once and discarded, with nothing stored.
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Clear a filter to widen the search, or send us the thing you were looking for.
A feed filter hooks into the page, collects the visible post text, and sends each post to the decision model with a rubric. sushrutb17/linkedin-noslop-extension sends LinkedIn posts with narrow yes or no and rating questions, then blurs the ones scored as low value. LinkedIn Zoo by Brendan O'Leary uses a choice among eleven species instead, which makes it a label, not a filter.
Choice labels, noul flags and score ranks. Showing a score keeps the final call with the reader. Slop Finder by Code-Wizard-Wilson uses a local Laya helper for detection. Others call a hosted API with your own key, so check where the text goes. Choose the primitive by the action: a flag for hide or blur, a label for sorting, a score for ranking. Run the first week in a mode that only marks posts.
The limit is the rule itself. Words like slop or bait mean different things to different people, and a filter can hide a post you wanted. Entries that keep the action reversible, like Your Signal, or send unsure calls to a human review lane, like ragelink/firehose-judge, handle that better than ones that delete. Ask who maintains the rubric, since it decides what gets hidden.
Yes. Several browser extensions here use Jev to hide, collapse or label posts by a rule you write in plain words. Check whether each one sends post text to a hosted API and whether it uses your own key.
Entries such as Slop Finder, Jev Detector and the LinkedIn noslop extension try. The idea of slop is fuzzy, so expect disagreement with your own taste, and prefer tools that show the score instead of deleting.
Not for the judging step. The entries here use a decision model to return a typed answer for each post. Some pair it with an LLM elsewhere, for example to write a summary.
