Metacognitive monitoring is the ability to accurately judge how likely your own answer is to be correct. This simulator makes that judgment measurable: before each trial you set a confidence rating, then answer, and the reliability diagram bins every stated confidence against the fraction of trials in that bin that actually turned out correct. A perfectly calibrated forecaster's bins sit on the diagonal; systematic overconfidence pulls them below it, systematic underconfidence pushes them above it. The batch simulator can generate dozens of trials under a chosen bias so the three calibration archetypes — overconfident, underconfident, well-calibrated — are visible immediately, and the running Brier score gives a single number for how good your (or the simulated) confidence judgments are.