A new approach to long-form video understanding has been proposed to address the challenges posed by complex temporal and spatial elements in extensive video content. While large language models have demonstrated partial effectiveness in video analysis, they still face limitations when processing information-dense hour-long videos. The innovative method aims to enhance these models' capabilities, making them more effective in handling extensive video material. This development seeks to overcome current obstacles by improving the models' ability to analyze and interpret long-duration videos comprehensively. By focusing on agentic search with tool use, the approach targets the intricate nature of long-form video data. The proposal reflects ongoing efforts to advance video understanding technologies, building on the progress made by large language models. Overall, this method represents a positive step toward more efficient and accurate long-form video processing.