In both cognitive science and computer science, goals are treated as cognitive states that can flexibly combine with world knowledge to organize and specify purposeful behavior. In other words, goals are compositional representations whose content is tightly linked to rational action. Highlighting goals as representations and their content reveals a parallel with other areas of cognitive science—especially the syntax‑semantics interface in linguistics and logic—and raises foundational questions about the expressivity, design principles, and efficiency of different goal representations.\ \ Traditionally, goals are taken as fixed constraints that restrict desirable behaviors. Yet we can also impose constraints on the goal representations themselves, such as whether a particular goal language is expressive enough to capture behaviors of interest, or whether different representations encode the same behavior. Researchers have begun to systematically characterize the properties of various goal representations, treating them as points within a broader design space.\ \ Distinguishing the form (syntax) from the meaning (semantics) of goals clarifies the implicit assumptions we make about goals, informs the study of interactions between higher‑level cognition and motivation, and isolates axes of variation across different conceptions of goals.\ \ Review: The paper reframes goals as compositional cognitive artifacts, borrowing the syntax‑semantics framework from linguistics to provide a fresh lens for assessing goal language expressivity and constraints, thereby bridging cognitive and computational perspectives on goal modeling.