AI Trading Bot Gets a Logic Auditor to Flag Incoherent Buy/Sell Decisions

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A developer running an LLM-powered forex trading bot on funded prop accounts added a reasoning auditor called shadow.py to evaluate whether the bot's trade thesis actually matches its directional calls. The bot uses a vision model to analyze candlestick charts hourly and trades EURUSD, GBPUSD, and USDJPY via MetaTrader 5, with hard risk limits including a 2% daily loss cap and a four-loss killswitch. Despite these guardrails, an initial $10,000 account was wiped out on September 9 after breaching maximum drawdown, prompting a deeper look at decision quality. The auditor uses TypeSafe's JEV model to run binary pass/fail checks on each recorded trade decision, flagging cases where the model's reasoning contradicts the direction it chose. Unlike open-ended AI commentary, the binary verdict format allows the developer to track incoherence rates over thousands of trades and correlate them with actual trading outcomes.

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