Acting Through Others: Evaluating Agent Competence and Safety in Socially Distributed Environments

What can an agent accomplish when the knowledge it needs and the authority to act belong to others? In such settings, progress requires discovering whom to ask, what others can provide, and how to get actions carried out. We introduce Incognita, a framework that transforms existing benchmark tasks into matched environments with centralized or socially distributed knowledge and action authority, while retaining task objectives and success criteria. In distributed conditions, agents interact with role-isolated participants whose capabilities are initially undisclosed. Using tasks adapted from AgentDojo and τ-bench, we investigate the dual demands of acting through others: acquiring information needed for progress while resisting information that would redirect that progress. In exploratory security tests, the effects of distributed access varied across models and attack families. Lower exposure to malicious information did not necessarily translate into fewer successful attacks. Task completion was also lower under distributed access in our competence study. Most failed distributed runs in that study stalled before obtaining the information needed to act. These complementary findings motivate a relational view of agent evaluation. Incognita makes the dependencies underlying action experimentally tractable, allowing us to examine how competence and vulnerability take shape through an agent’s relations with others.