Rich Video Clips: Enhancing Semantic Density and User Engagement Through Contextualized Micro-Video Content Abstract The proliferation of short-form video platforms has shifted user expectations from raw footage to semantically dense, highly engaging clips. This paper introduces the concept of Rich Video Clips (RVCs) — video segments augmented with multi-modal layers including metadata, scene understanding, interactive hotspots, emotional arcs, and cross-modal summaries. We propose a framework for generating RVCs from raw video using vision-language models, audio analysis, and user interaction logs. A user study (N=120) shows that RVCs improve information retention by 38%, navigation efficiency by 52%, and subjective engagement by 47% compared to standard trimmed clips. We conclude with design principles and applications in education, e-commerce, and sports analytics. 1. Introduction Traditional video clips are linear, passive, and information-sparse. A “rich video clip” goes beyond temporal truncation; it embeds structured knowledge, interactive elements, and contextual cues directly into the playback experience.