Video Prompting Guide

---
name: video-prompting-guide
description: 'Best practices and techniques for writing effective AI video generation
  prompts. Covers: Veo, Seedance, Wan, Grok, Kling, Runway, Pika, Sora prompting strategies.
  Learn: shot types, camera movements, lighting, pacing, style keywords, negative
  prompts. Use for: improving video quality, gett...'
allowed-tools: Bash(infsh *)
risk: safe
source: community
license: MIT
---
# Video Prompting Guide

## When to Use

Use this skill as needed to perform the specified automation task.

Best practices for writing effective AI video generation prompts via [inference.sh](https://inference.sh).

![Video Prompting Guide](https://cloud.inference.sh/app/files/u/4mg21r6ta37mpaz6ktzwtt8krr/01kg2c0egyg243mnyth4y6g51q.jpeg)

## Quick Start

```bash
curl -fsSL https://cli.inference.sh | sh && infsh login

# Well-structured video prompt
infsh app run google/veo-3-1-fast --input '{
  "prompt": "Cinematic tracking shot of a red sports car driving through Tokyo at night, neon lights reflecting on wet streets, rain falling, 4K, shallow depth of field"
}'
```

## Prompt Structure Formula

```
[Shot Type] + [Subject] + [Action] + [Setting] + [Lighting] + [Style] + [Technical]
```

### Example Breakdown

```
"Slow motion close-up of coffee being poured into a white ceramic cup,
steam rising, morning sunlight streaming through window, warm color grading,
cinematic, 4K, shallow depth of field"
```

- **Shot Type**: Slow motion close-up
- **Subject**: Coffee
- **Action**: Being poured
- **Setting**: White ceramic cup, window
- **Lighting**: Morning sunlight
- **Style**: Warm color grading, cinematic
- **Technical**: 4K, shallow depth of field

## Shot Types

| Shot Type | Description | Use For |
|-----------|-------------|---------|
| Wide shot | Shows entire scene | Establishing location |
| Medium shot | Waist-up framing | Conversations, actions |
| Close-up | Face or detail | Emotion, product detail |
| Extreme close-up | Single feature | Drama, texture |
| Aerial shot | Bird's eye view | Landscapes, scale |
| Low angle | Camera looking up | Power, grandeur |
| High angle | Camera looking down | Vulnerability |
| Dutch angle | Tilted camera | Unease, tension |
| POV shot | First person view | Immersion |

## Camera Movements

| Movement | Description | Effect |
|----------|-------------|--------|
| Tracking shot | Camera follows subject | Dynamic, engaging |
| Dolly in/out | Camera moves toward/away | Focus, reveal |
| Pan | Horizontal rotation | Survey scene |
| Tilt | Vertical rotation | Reveal height |
| Crane shot | Vertical + horizontal | Dramatic reveal |
| Handheld | Slight shake | Realism, urgency |
| Steadicam | Smooth following | Professional, cinematic |
| Zoom | Lens zoom in/out | Quick focus change |
| Static | No movement | Contemplation, stability |

## Lighting Keywords

| Keyword | Effect |
|---------|--------|
| Golden hour | Warm, soft, romantic |
| Blue hour | Cool, moody, twilight |
| High key | Bright, minimal shadows |
| Low key | Dark, dramatic shadows |
| Rim lighting | Subject outlined with light |
| Backlit | Light from behind subject |
| Soft lighting | Gentle, flattering |
| Hard lighting | Sharp shadows, contrast |
| Neon | Colorful, urban, cyberpunk |
| Natural lighting | Realistic, documentary |

## Style Keywords

### Cinematic Styles

```
cinematic, film grain, anamorphic lens, letterbox,
shallow depth of field, bokeh, 35mm film,
color grading, theatrical
```

### Visual Aesthetics

```
minimalist, maximalist, vintage, retro, futuristic,
cyberpunk, steampunk, noir, pastel, vibrant,
muted colors, high contrast, desaturated
```

### Quality Keywords

```
4K, 8K, high resolution, photorealistic,
hyperrealistic, ultra detailed, professional,
broadcast quality, HDR
```

## Prompt Examples by Use Case

### Product Demo

```bash
infsh app run google/veo-3-1-fast --input '{
  "prompt": "Smooth tracking shot around a sleek smartphone on a white pedestal, soft studio lighting, product photography style, reflections on surface, 4K, shallow depth of field"
}'
```

### Nature Documentary

```bash
infsh app run google/veo-3-1 --input '{
  "prompt": "Slow motion extreme close-up of a hummingbird hovering at a red flower, wings in motion blur, shallow depth of field, golden hour lighting, National Geographic style"
}'
```

### Urban Lifestyle

```bash
infsh app run google/veo-3 --input '{
  "prompt": "Tracking shot following a cyclist through busy city streets, morning rush hour, natural lighting, handheld camera feel, documentary style, authentic and candid"
}'
```

### Food Content

```bash
infsh app run bytedance/seedance-1-5-pro --input '{
  "prompt": "Close-up of chocolate sauce being drizzled over ice cream, slow motion, steam rising, soft lighting, food photography style, appetizing, commercial quality"
}'
```

### Tech/Futuristic

```bash
infsh app run xai/grok-imagine-video --input '{
  "prompt": "Futuristic control room with holographic displays, camera slowly pans across the space, blue and cyan lighting, sci-fi atmosphere, Blade Runner aesthetic, 4K",
  "duration": 5
}'
```

## Common Mistakes to Avoid

| Mistake | Problem | Better Approach |
|---------|---------|-----------------|
| Too vague | "A nice video" | Specify shot, subject, style |
| Too complex | Multiple scenes | One scene per prompt |
| No motion | Static description | Include camera movement or action |
| Conflicting styles | "Minimalist maximalist" | Choose one aesthetic |
| No lighting | Undefined mood | Specify lighting conditions |

## Model-Specific Tips

### Google Veo

- Excels at realistic, cinematic content
- Supports audio generation (Veo 3+)
- Best with detailed, professional prompts
- Frame interpolation available in 3.1

### Seedance

- Strong at dance and human motion
- First-frame control available
- Good for consistent character motion
- Works well with reference images

### Wan 2.5

- Best for image-to-video
- Animates still images naturally
- Good motion prediction
- Works with any image style

### Grok

- Good general-purpose video
- Configurable duration (5-10s)
- Creative interpretations
- Works well with abstract concepts

## Workflow: Iterative Prompting

```bash
# 1. Start with basic prompt
infsh app run google/veo-3-1-fast --input '{
  "prompt": "A woman walking through a forest"
}'

# 2. Add specificity
infsh app run google/veo-3-1-fast --input '{
  "prompt": "Medium tracking shot of a woman in a red dress walking through an autumn forest"
}'

# 3. Add style and technical details
infsh app run google/veo-3-1-fast --input '{
  "prompt": "Cinematic medium tracking shot of a woman in a flowing red dress walking through an autumn forest, golden hour sunlight filtering through leaves, shallow depth of field, film grain, 4K"
}'
```

## Related Skills

```bash
# Generate videos
npx skills add inference-sh/skills@ai-video-generation

# Google Veo specific
npx skills add inference-sh/skills@google-veo

# Generate images for image-to-video
npx skills add inference-sh/skills@ai-image-generation

# General prompt engineering
npx skills add inference-sh/skills@prompt-engineering

# Full platform skill
npx skills add inference-sh/skills@inference-sh
```

Browse all video apps: `infsh app list --category video`

## Documentation

- [Running Apps](https://inference.sh/docs/apps/running) - How to run apps via CLI
- [Video Generation Guide](https://inference.sh/blog/guides/video-generation) - Comprehensive video guide