Ömer Karışman

Video Prompting Guide

设计创意v0.1.5
作者:Ömer Karışman更新于 2026-05-17共 2 个版本 · 最新版本发布于 2026-02-18video-prompting-guide@clawhub_okaris/video-prompting-guide
视频处理视觉素材#Video Generation#Prompt Engineering

据 AlphaMoat 统计,截至 2026-09,Video Prompting Guide 累计下载 2,456 次、获 3 个星标,在全部 5,078 个 AI 技能中排名第 4,136 位,在「设计创意」分类(512 个)中排名第 404 位。

累计安装
187
累计下载
2,456
星标
3
全站排名
#4,136
全站前 82% · 「设计创意」前 79%
平台累计安装累计下载星标评论
ClawHub ↗712,3472-
SkillHub ↗1872,4563—

各平台的计数口径不同,统计时间不一致。

这个技能是做什么的

该指南建议按镜头类型、主体、动作、场景、光线、风格和技术要求组织提示,并说明运镜、照明关键词、节奏和负面提示词等写作要素。它提供的是提示词技巧与示例,不代表已调用任何视频生成服务。

资料发布于 2026-10-27

可以用来做什么

  • 为 AI 视频生成任务组织画面提示词
  • 调整镜头、运镜、光线和视觉风格描述

什么时候用

  • 需要改进 AI 视频提示词的清晰度和结构时
  • 准备根据目标画面补充镜头或光线描述时

示例提示词

以下是根据技能文档生成的示例,不代表实际运行结果。

把这个视频想法整理成包含主体、动作、场景和光线的提示词
为这段镜头描述补充合适的运镜和视觉风格要素

月度数据趋势

累计下载2,456
1,2711,9082,5442026-03 · 累计下载 1,3592026-05 · 累计下载 1,7832026-06 · 累计下载 1,9262026-07 · 累计下载 2,1382026-08 · 累计下载 2,2532026-09 · 累计下载 2,45626-0326-09
星标3
2332026-03 · 星标 22026-05 · 星标 22026-06 · 星标 32026-07 · 星标 32026-08 · 星标 32026-09 · 星标 326-0326-09

2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。

月份累计下载环比星标
2026-092,456—3
2026-082,253+5.4%3
2026-072,138+11.0%3
2026-061,926+8.0%3
2026-051,783—2
2026-031,359—2

SKILL.md 原文

以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。

7.8 KB · ClawHub v0.1.5
---
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, getting consistent results, professional video prompts. Triggers: video prompt, how to prompt video, veo prompts, video generation tips, better ai video, video prompt engineering, video prompt guide, video prompt template, ai video tips, video prompt best practices, video prompt examples, cinematography prompts"
allowed-tools: Bash(infsh *)
---

# Video Prompting Guide

Best practices for writing effective AI video generation prompts via [inference.sh](https://inference.sh).
展开全部(共 244 行)
![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"
}'
```

> **Install note:** The [install script](https://cli.inference.sh) only detects your OS/architecture, downloads the matching binary from `dist.inference.sh`, and verifies its SHA-256 checksum. No elevated permissions or background processes. [Manual install & verification](https://dist.inference.sh/cli/checksums.txt) available.

## 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

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Ömer Karışman 的其他技能

数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。