Temporal properties specify how systems must evolve over time, requiring events to occur, conditions to persist, or responses to follow triggers within given intervals. Their verification is essential in safety-critical and reactive domains where behavior is expressed as sequences of timed events, such as UML state machines and activity diagrams. To address this limitation, we introduce a framework centered on a Common Declarative Language (CDL), which encodes execution traces as Prolog facts and provides a reusable foundation for analysis. On top of CDL, a Python engine, called Timed Event Logic Analyzer (TELA), evaluates Linear Temporal Logic (LTL) queries through recursive finite-trace semantics. Supporting both Prolog queries and LTL property checks, the framework enables interactive, on-demand reasoning directly over recorded traces without regenerating models or exploring full state spaces. The key contribution of this work is the integration of CDL as a unifying declarative layer with TELA as an interactive analysis engine, providing flexibility, portability, and iterative “what-if” reasoning across diverse modeling notations and application domains.