Most agent evals measure one of three things: knowledge, task completion, or tool use. Some newer benchmarks measure social intelligence or deception in bounded settings. CrucibleBench exists to measure a different failure surface: whether an agent can remain coherent, adaptive, and trustworthy when relationships persist, feedback accumulates, and actions change the future state of the world.
CrucibleBench is an independent applied research effort focused on behavioral evaluation for AI agents operating in persistent social environments.
The work draws on experience in AI test & evaluation, adversarial scenario design, simulation design, and product deployment. We publish benchmark methods, results, and limitations openly, and use the same framework for private evaluations with teams shipping agentic systems.
Research collaboration, enterprise evaluation, or questions about the work.
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