How do humans learn, through social interaction, whom to depend on in different situations? We compared the extent to which inferred trait attributes-as opposed to learned reward associations previously examined as part of feedback-based learning-could adaptively inform cross-context social decision-making. In four experiments, participants completed a novel task in which they chose to "hire" other players to solve math and verbal questions for money. These players varied in their trait-level competence across these contexts and, independently, in the monetary rewards they offered to participants across contexts. Results revealed that participants chose partners primarily based on context-specific traits, as opposed to either global trait impressions or material rewards. When making choices in novel contexts-including determining who to choose for social and emotional support-participants generalized trait knowledge from past contexts that required similar traits. Reward-based learning, by contrast, demonstrated significantly weaker contextsensitivity and generalization. These findings suggest that people form context-dependent trait impressions from interactive feedback and use this knowledge to make flexible social decisions. These results support a novel theoretical account of how interaction-based social learning can support context-specific impression formation and adaptive decision-making.