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While these traces improve interpretability by grounding \\emph{where} and \\emph{when} evidence appears, they often leave the motion connecting observations, the \\textit{how}, implicit. This makes dynamic and trajectory-dependent claims difficult to supervise, verify, or penalize when unsupported by the video. We formalize this missing component as Spatial-Temporal-Trajectory (STT) reasoning and introduce \\textbf{Motion-o}, a motion-centric extension to vision-language models (VLMs) that makes trajectories explicit and verifiable. Motion-o augments evidence chains with Motion Chain of Thought (MCoT), a structured pathway that represents object motion through a discrete \\texttt{<motion/>} tag summarizing direction, speed, and scale change. 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Motion-o augments evidence chains with Motion Chain of Thought (MCoT), a structured pathway that represents object motion through a discrete \\texttt{<motion/>} tag summarizing direction, speed, and scale change. 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