Backtest audit in one command. QuantPad's new /review checks your research for the defects that most often invalidate a backtest: lookahead, bad fills, missing costs, and parameters tuned on the answer. We ran it on a real study: 15 years of E-mini S&P 500 futures (ES, 2011 to 2025), 3,726 trades from a 15-minute opening-range rule. What it did, in order. It started from the trade log and printed the tripwires: entry times, trades per session, hit rate against profit factor. It checked the raw feed: 371,556 of 8,015,276 minute rows fail a strict OHLC check, and none of them touch the bars this strategy traded. It reran the engine on the cached bars and rebuilt all 3,726 trades, every one identical. Then it priced three trades by hand, -$16.50, -$379.00 and +$1,808.50, and all three match the log. The report: 38 checks, each with its evidence. One flag, a single zero-duration trade at 15:59 that moves the result by $16.50. The strategy still loses money after costs (net -$1,816.50 at $16.50 a round turn), and now that loss is verified instead of assumed. All figures are in-sample for a fixed, untuned rule. Why QuantPad: the audit reruns your trades against the same minute data your backtest used, and that data is included with your subscription. A chatbot can read your code. It cannot rerun it against 15 years of futures data. Type /review on your own research. #QuantPad #backtesting #quanttrading #algotrading #futurestrading - @quantpad