Write a post, a listing, a product or a headline, and 10,000 computed AI residents read it. The 600 it should matter to see it first, and it reaches the next 1,500 only if more readers were glad than annoyed, so a weak text dies for half a cent and a good one reaches everyone in 14 seconds. You get who stopped, liked, reposted or blocked, by interest, job, age, city and budget; the questions buyers would ask a listing first; and a demand curve over a product's price ladder. No sign-in.
I pasted in a cold outreach subject line I'd actually sent and it flagged the exact thing a real reader would roll their eyes at - too much throat-clearing before the actual ask. Having a pool of simulated readers react before I publish anything is a genuinely useful gut-check step that's normally missing until you get real (and much slower) feedback.
What needs improvement
It would help to see a breakdown of which persona segments reacted negatively and why, not just an aggregate glad-vs-annoyed number - right now I can't tell if a low score means the hook is weak or just that it doesn't land with one specific audience.
Wordtune polishes the sentence itself but doesn't tell you how a reader will actually react to it. Jevtown is closer to a reader-reaction test than a grammar/style pass, which is the piece I was actually missing.
This is in now. When a check finishes, the town is asked why. The people who scrolled past or got annoyed each pick a reason, such as "not for them", "the opening does not hook", "hard to believe" or "off-putting tone". The page then splits the answers into those about the text and those about who was reading it, so you can tell a weak hook from the wrong audience. The Got annoyed tab names the group most often annoyed, and the people who liked it say what stopped them.
This is in now. When a check finishes, the town is asked why. The people who scrolled past or got annoyed each pick a reason, such as "not for them", "the opening does not hook", "hard to believe" or "off-putting tone". The page then splits the answers into those about the text and those about who was reading it, so you can tell a weak hook from the wrong audience. The Got annoyed tab names the group most often annoyed, and the people who liked it say what stopped them.