Agents Need Event Time: Freshness-Aware Reasoning over Delayed Tool Results

Tool-using agents often treat the latest message as the latest state. Under asynchronous execution, this ordering is wrong: a result delivered last can describe a snapshot taken before the world changed. We introduce event-time reasoning, a runtime protocol that attaches snapshot versions and scope watermarks to tool results so agents can validate evidence against decision-time state. EventTimeBench makes this failure measurable with evolving SQLite, workflow-event, and Python-AST backends, while Watermark combines exact version invalidation with calibration-free query influence and optional service cost. Across 97,200 controlled tasks and 747,600 paired outcomes, a preregistered five-seed confirmation raises exact accuracy from 87.0% with version-only ranking to 90.1% with Watermark-I, a +3.09-point gain $[2.53,3.62]$ that also exceeds a direct answer-flip predictor; the gain remains +4.15 points $[3.68,4.61]$ under two unseen transition regimes. Natural code exposes a complementary requirement: when sources jointly determine an answer, selective refresh can create an incoherent state, so the cut must remain atomic. Frozen query-family allocation reaches 96.45% across 265 commits from ten unseen repositories; a frozen gate matches that accuracy at 96.50% while refreshing 48.7% fewer sources than full refresh. Executable OpenCode sessions across two model families demonstrate integration. Event time makes freshness an explicit, efficient reasoning primitive for agents operating over evolving state.