Computer-based information systems connected to high-speed communication networks provide increasingly rapid access to a wide variety of data resources. However, this connectivity to data resources burdens decision-makers the need to access and analyze a large volume of data to support their decision making processes. Without effective decisional guidance, access to data resources provides only a minor benefit to decision-makers. Intelligent agents are expected to act like human-assistants in support of complex decision processes by anticipating the information requirements of the decision-makers or by autonomously performing a specific set of tasks. In this article, we provide a methodology for assessment of buddy-agents in a multi-agent information system environment in support of complex decision problems. Our findings from an empirical assessment of the methodology that was used to support common stocks selection among investors support the viability of the proposed methodology.