SHA-256: e1e5531629166d5650d231943edbc9b3c4aa361a54bf32928c13279b8cad4358 This work presents the XREALISM® Rezostable Evaluation Core (ΣE), an architectural component designed to regulate action in artificial intelligence systems before execution occurs. The architecture explicitly separates: Perception (Πₙ) — perceptual signals and environmental inputs Proposed intention (Ψₙ) — internally generated action candidates Execution — permitted actions released after evaluation ΣE is not a decision-maker and does not generate intelligence, goals, or actions. Instead, it functions as a rezostable evaluative nucleus that determines whether a proposed intention is allowed to become executable, based on temporal coherence, contextual stability, and responsibility constraints. Evaluation is continuous with respect to perception, but discrete with respect to permission. Only evaluated and permitted intentions exit the system as authorized actions. The Rezostable Evaluation Core is embedded within the author’s Conscio-Perceptual Unit (CPUₙ) framework, where perception, intention, evaluation, and action remain structurally distinct without collapsing into a single decision-making entity. This approach enables architectural stability and accountability, making ΣE suitable for safety-critical and regulated AI deployments. License Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) XREALISM® — Some Rights Reserved