I built a read-only Chrome extension for Kalshi with a YES / NO Scanner Lab. Would love feedback from other builders.
Hey everyone,
I’ve been experimenting with AI-assisted development and built a read-only Chrome extension for Kalshi prediction market observation.
I’m not posting this as a trading tool or investment advice.
What I’m more interested in sharing is the build process, because this became a much harder AI-assisted development project than I expected.
The project is called EightyPlus for Kalshi.
It does not place orders.
It does not automate trading.
It does not control the user’s account.
The extension is focused on read-only prediction market observation.
The hardest part was building the Scanner Lab.
At first, I thought it would be a simple scanner UI.
But Kalshi is different from a normal crypto exchange or stock market platform.
It is based on event contracts and YES / NO markets.
So the more I built it, the more the Scanner Lab became a logic system for event-based markets.
I needed users to be able to combine conditions like:
YES bid
YES ask
YES last price
NO-side interpretation
spread
liquidity
volume
open interest
market status
event category
contract timing
market movement
probability-like pricing
Then those conditions had to work with:
AND
OR
NOT
parentheses
condition stacks
repeated scans
saved recipes
The difficult part was not only building the UI.
The difficult part was redefining scanner logic for YES / NO markets.
In stocks or crypto, scanner conditions usually feel more familiar:
price
volume
candles
technical indicators
momentum
trend
volatility
But prediction markets are different.
A normal market scanner does not directly fit event contracts.
For Kalshi, the scanner has to think more in terms of event context, YES / NO pricing, market movement, liquidity, and whether the contract itself is worth observing.
That changed the way I had to organize the product logic.
This was one of the parts where AI was useful, but not magical.
The AI helped generate code, refactor components, and explore different UI structures.
But I still had to define the product logic, decide the constraints, test the behavior, and keep correcting the direction.
The bigger workflow I’m testing is:
- Use the Chrome extension to observe Kalshi markets.
- Build YES / NO Scanner Lab conditions.
- Save result cards.
- Send those cards into an AI chat workflow.
- Use AI for research, context, and analysis. Not prediction.
I’m currently testing the core implementation before preparing for Chrome Web Store submission.
But while building it, I keep asking myself:
Is this something people would actually find useful?
That’s the part I’m not fully sure about yet.
Technically, it works.
But I’m still trying to understand whether the idea, positioning, and workflow make sense from a user’s point of view.
Would love to hear your thoughts.