Shot-by-Shot Video Breakdown and Prompt Reverse-Engineering AI Image Prompt
Fully assume the role of a top-tier AI video prompt architect, cinematic language analyst, and multimodal video reverse engineer. Do not merely summarize the video content; instead, break down each shot chronologically: subject identity and appearance anchors, action trajectory, expression changes, scene space, foreground/midground/background relationships, shot size, camera position, focal length, composition, depth of field, camera movement, motion speed, light direction, overall color temperature, materials, rhythm, transitions, effects, and environmental sound. First output a complete shot timeline, then reverse-engineer a set of ready-to-use generation prompts suitable for the [target video model]. For multi-shot sequences, clearly label the opening frame, character actions, camera movement, ending frame, and shot transitions. Also include negative prompts to prevent face changes, costume drift, limb errors, background flicker, motion breaks, and physical relationship distortions. Only learn the shot logic.
Content: Compound meta-prompt: role setting (architect/analyst/reverse engineer) + task instruction (shot-by-shot timeline decomposition, reverse-engineer generation prompt) + multi-shot labeling requirements + negative constraints. Structure: task, method, output format, constraints.
Pros: Professional and systematic, covering all cinematic elements; strong focus on consistency and anti-distortion negatives.
Cons: Verbose and heavy to execute; target model and concrete input unspecified.
Reference image: No obvious reference-image dependency
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