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Context-aware systems often use rule-based reasoning engines for decision making without involving explicit interaction with the user. While rule-based systems excel in filtering out unsuitable solutions based on clear criteria, it is difficult to rank suitable solutions based on vague, qualitative criteria with a rule-based approach. Moreover, the description of such systems is typically ad-hoc without well-defined modeling tasks. CARGO (Context-Aware Reasoning using Goal-Orientation) aims to address these problems by combining rule-based and goal-based reasoning as well as scenario-based modeling to provide a more comprehensive way to define context-aware systems and to process contextual information. This demo presents CARGO, a modeling, simulation, and execution environment for context-aware systems built on existing tool support for the User Requirements Notation.