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Full end-to-end video analysis with KUAVi
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Basierend auf der SOC-Berufsklassifikation
Compositional pixel analysis patterns using kuavi_eval for counting, motion detection, change tracking, and visual comparison. Use when questions require precise measurements, object counting, or frame-by-frame comparison.
Multi-video corpus indexing and cross-video search
Deep multi-pass video analysis with parallel sharding and zoom
Multi-pass search with query refinement for hard-to-find video content. Use when initial search returns low-confidence results or no matches.
Index a video file for KUAVi analysis
Predictive video understanding — anticipate actions, predict future content, verify coherence, classify activities
| name | kuavi-analyze |
| description | Full end-to-end video analysis with KUAVi |
| agent | video-analyst |
| context | fork |
| argument-hint | <video-path> <question> |
| disable-model-invocation | true |
Perform comprehensive video analysis: index, search, reason, and answer.
$ARGUMENTS for: video path and question/task.kuavi_index_video.kuavi_get_scene_list to understand the video structure.The first argument is the video path. Remaining text is the question.
Example: /kuavi-analyze /path/to/video.mp4 What is the main topic of this presentation?