Video Generation Prompting Guide & Templates
This guide provides a unified structured prompting framework for AI video models (Sora 2, Runway Gen 4.5, Kling 2.6, Veo 3/3.1), covering cinematography, camera movement, lighting, and action description. Emphasizes specificity over vagueness and offers model-specific optimization techniques and failure mode fixes.
Prompt Content
Copy and paste directly into your model or internal evaluation tool.
[STYLE INTENT] — cinematic short film | documentary | commercial | music video [SHOT TYPE + FRAMING] — wide establishing shot | medium close-up | aerial [CAMERA MOVEMENT] — slow dolly-in | handheld ENG | crane boom up | static [SUBJECT + ACTION] — described in beats/counts, not vague adjectives [ENVIRONMENT] — foreground, midground, background, weather [LIGHTING] — source, direction, quality, color palette anchors [DURATION HINT] — 4s / 8s / 12s (models follow shorter clips more reliably)
Rule: One camera move + one subject action per shot.
Example: Cinematic commercial — Medium close-up, slight angle from behind Slow dolly in Cyclist pedals three times, brakes hard at crosswalk, front wheel skids Wet asphalt, neon reflections pooling in puddles Golden hour light with tungsten practicals; palette: warm amber + cream + walnut brown 8s
Note: Avoid vague adjectives like 'beautiful' or 'fast'; use verifiable concrete details instead.
Use Cases
Reference Output
An 8-second video of a cyclist braking hard at a crosswalk on wet asphalt, front wheel skidding, neon reflections pooling in puddles, shallow depth of field with warm golden hour lighting and tungsten accents.
Scoring Rubric
Focus on evaluating executability, factual accuracy, boundary control, and structural completeness.
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