donmarket

This project offers a missing piece of market intelligence: it reverse-engineers the fee schedules of Polymarket's various interfaces and trading bots by analyzing their on-chain executions. In the prediction market space, many platforms and bots claim to be 'free' but actually charge through spread markup or hidden fees. This toolkit uses what the author calls 'attributed executions' to infer the real cost applied by a specific builder or service. The methodology involves on-chain analytics, defined in the Python codebase, to map trade execution to known addresses and calculate the effective price paid versus the mid-market rate. This is a powerful research tool for any serious Polymarket participant looking to minimize costs or choose the best execution interface. The project is small in scope but high in value. The strategy is not a trading strategy but an information edge. This is a 'worth_cloning' for the unique data and analysis capabilities it provides. It enables a user to empirically measure the cost of their trading infrastructure. There are no malware indicators.