Evaluating GP schema in context is considered to be a complex, and, at times impossible, task. The tightly linked nodes of a GP tree is the main reason behind its complexity. This paper presents a new approach to evaluate GP schema in context. It is simple in its implementation with a potential to address well-known GP problems, such as identification of significant schema, dead code (introns) and module acquisition to name a few. It is based on the principle that the contribution of a schema can be evaluated by neutralizing the effect of the schema in the tree containing it (container-tree) and then checking its effect on the container-tree’s fitness. Its usefulness is empirically demonstrated along with its limitation. Categories and Subject Descriptors I.2 [Artificial Intelligence]: Problem Solving, Control Methods, and Search—Genetic Programming General Terms Algorithms, Theory Keywords Tree Semantics, Module Acquisition, Schema Theory