≻=PlayingFild uses on device machine learning to classify tabs by content, not URL. The same website can be productive or distracting based on the page. Classification happens entirely on your device. Raw page content, HTML and personal text don't leave your browser. Earn break time by focusing and spend it when you need it. Tabs reorder themselves based on what you actually use, and unused tabs close. Includes per window rules, focus timer modes, recap cards, and productivity analytics.
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Thanks Omri, and thanks for the questions on Product Hunt too. You've hit the exact thing that's been bugging me.
Slightly embarrassing honest answer: the correction flow partly exists already. There's a prompt that asks "was this site productive?" so you can override wrong guesses and train your own local model. It works in my dev build, but a packaging bug meant the file never made it into the store build, so store users have never seen it.
I found the fix a while back but held off pushing mid-launch because I didn't want to break a build people were actively installing. I've been running the fixed version myself for a while now and it's stable, so it's going out now. Chrome review takes a few days.
The full "why did this get flagged" log is the next layer. The diagnostics exist internally from when I was debugging the classifier, they show which signals fired for a page. Surfacing that to users is what I'm building next, and your review moved it up the list.