The Bayesian Truthfulness Benchmark (BTB) evaluates epistemic reliability in agentic AI systems by assessing how agents update beliefs under uncertainty. Rather than focusing on static correctness, BTB presents structured probabilistic scenarios with explicit priors and evidence, and measures whether agents revise beliefs in accordance with Bayesian rationality. Agent responses are evaluated using Bayesian Epistemic Consistency, capturing probabilistic coherence, epistemic humility, and convergence toward truth over time. The benchmark is implemented as a Green Agent on AgentBeats with automated, interpretable scoring.