Slack-native product assistant that, according to its author, scores product signals with Jev and waits for human review before shipping changes; the Jev integration is not independently inspectable, and public materials do not specify what data it sends to Jev.
This is an independent community listing. Check the source, license, data handling, and evaluation caveats before relying on a project. Inclusion is not an endorsement or security review.
Chrome extension that judges each LinkedIn post as it scrolls into view and stamps engagement bait or corporate marketing onto the post, leaving it readable, with the probability printed on the stamp; two Noul questions and a Choice category run per post, local keyword rules settle obvious cases before any API call, and verdicts are cached per post. Post text goes to TypeSafe through a local proxy that holds the key so the extension never receives it, and a proxy or model error leaves every post visible. Thresholds (is_slop 0.60, is_corporate 0.70) are fitted to the bundled 14-post labelled set, which is too small to characterise precision beyond that sample; English and text only, and the LinkedIn DOM selector will need updating when LinkedIn rebuilds its feed.
Apache-licensed, text-only classifier for 261 federal tax forms that sends PDF text to Jev; the author reports no wrong labels on two test corpora but 38 low-confidence pages, without committed page-level results.
Download share card
