Cognitive modeling has evolved into a powerful tool for understanding and predicting user behavior. Higher-level modeling frameworks such as GOMS and its variants facilitate fast and easy model development but are sometimes limited in their ability to model detailed user behavior. Lower-level cognitive architectures such as EPIC, ACT-R, and Soar allow for greater precision and direct interaction with real-world systems but require significant modeling training and expertise. In this paper we present a modeling framework, ACT-Simple, that aims to combine the advantages of both approaches to cognitive modeling. ACT-Simple embodies a "compilation" approach in which a simple description language is compiled down to a core lower-level architecture (namely ACT-R). We present theoretical justification and empirical validation of the usefulness of the approach and framework.