Img2Vid Prompt Expert

Problem

Image-to-video prompting is not just adding “make it move” to an image. The input image fixes the starting frame, so the harder task is converting a few seconds of action, camera behavior, style, and effects into executable constraints. Without that, models may warp unpredictably, move in the wrong direction, or miss the intended effect.

How It Works

The skill structures prompts in five layers: base image context, motion, camera language, style/atmosphere, and cinematic effects. The workflow identifies the subject and desired change, selects action verbs and adverbs, maps terms like Pan, Tilt, Zoom, Dolly, and Tracking Shot, then layers lighting, tone, and effects such as Slow Motion, Motion Blur, and Lens Flare. It outputs English and Chinese versions, aligning details for RunwayML, Sora, Pika, Kling, and similar platforms, with camera notes, suggested parameters, and variants.

Boundaries

It is best for short image-to-video prompts where action, camera movement, and visual style are clear. It is not designed for long narratives, exact character identity preservation, or high-fidelity physics simulation. Chinese prompts should be adapted to local model expectations rather than treated as literal translations.