In Plain Sight: CurioBench-1K, a Benchmark for Whether Agents Utilize Environmental Resource Leads

Curiosity, the disposition of an agent to notice, inspect, and act on useful resources it was not instructed to use, is essential for operating in unfamiliar environments and for identifying dangerous or specification-violating behavior, yet existing agentic benchmarks score only whether the task was completed. We introduce CurioBench-1K, a benchmark of 1,000 deterministic, judge-free tasks that plant discoverable resource leads in synthetic workspaces, with planted measurement tasks paired against identical-prompt controls so that deliberate inspection is measured separately from task-solving capability, in both benign and adversarial scenarios. Evaluating six models across two instruments, we find meaningfully distributed results: even the strongest agents exhibit a 58-point gap between discovering a planted solution and touching it, and deliberate opening of a visible solution stays at or below 10.3% on the replication split (23.6% at most on the second instrument). The failure localizes to the moment of choosing what to inspect: agents enumerate the workspace, see the planted file's name, and choose not to open it. Capable models already notice more than they say. When asked what they noticed, their median reporting of planted findings increases from 10% to 79%, although one-sentence instructions change what they use only marginally. A small model had nothing to unlock, since no prompt moved it from zero while training on demonstrations did, and reward-based training on the benchmark's own scorer added little. Default evaluations therefore measure an agent's default behavior, not its underlying capability. CurioBench-1K is designed to distinguish the two.