Vidu Prompt Builder

Structure is what makes a Vidu video prompt reliable

When you prompt Shengshu Vidu, the quality of the clip depends far more on how you structure the request than on any clever phrase. Vidu is a text-to-video and image-to-video model built by China's Shengshu (生数科技), and it has three clear strengths: native audio-video, a real flair for anime and animation, and strong reference-to-video consistency for keeping a character or object on-model. A structured prompt names the subject and scene, states the action or story beat, fixes the camera move, sets the shot size, chooses one style, and describes the sound and mood. This builder keeps that structure for you: fill the fields, and it joins them into a clean prompt that opens with a vivid subject-and-scene line followed by clearly headed sections — action, camera, shot size, style, sound, duration, negatives — each prefixed with a Markdown-style heading, ready to paste into Vidu. The result is the kind of prompt a careful video director would write by hand, only assembled in seconds.

The single highest-leverage line is the subject and scene. "A ginger cat curled up at a neon-lit street stall on a rainy night" gives Vidu a concrete frame, lighting and mood in one sentence — far more useful than a list of adjectives. After that, the action and the camera move do the heavy lifting, because video is motion: the action says what changes over the few seconds of the shot, and the camera move tells Vidu how the viewpoint travels — a slow push-in, an orbit, a follow, or a locked-off frame. Vidu is genuinely good at coherent motion, so an explicit, physical description of movement is what stops a clip from looking stiff or jittery. Naming the shot size — close-up, medium, wide — then controls how much of the frame the subject fills, which is the difference between a cramped composition and one that breathes.

Camera, style and sound separate a clip from a shot

The fields people skip and regret are style, sound and negatives. Vidu shines at anime and animation as well as realism, but it works best when you commit to one main style and make it specific — "Japanese cel-shaded animation, soft palette" beats a vague mix that makes the look waver shot to shot. Sound is where Vidu is unusual: because it generates native audio-video, naming ambient sound, music or an emotional tone keeps the audio in step with the picture instead of leaving you to dub it later. And negatives — "no blur, no distortion, no extra fingers, no text watermark" — are a cheap, reliable way to dodge the artefacts that plague video generation. None of these fields limits the model; they focus it.

Because the output is structured plain text, the same prompt is portable: it is tuned for Vidu, but the subject, action, camera and style fields drop just as neatly into Kling, Jimeng, Runway or Sora. If you are using Vidu's reference-to-video to lock a character, keep the text prompt in line with the reference image — describing the same subject in words reinforces the visual lock and markedly improves consistency. And because the whole tool runs locally in your browser, you can iterate freely — tweak one field, copy again, and test in Vidu — without anything you type ever leaving your device, being sent to a model, or being stored. Treat the first prompt as a draft: generate it, see where the motion or look drifts, and tighten the matching field. Two or three rounds of that usually turn a rough clip into exactly the shot you wanted, and you keep a clean, reusable prompt at the end.