video-prompting-guide
Best practices for writing effective AI video generation prompts via inference.sh.
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Installation Guide
How to use video-prompting-guide on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
video-prompting-guide
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches video-prompting-guide from inference-sh/skills and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate video-prompting-guide. Access via /video-prompting-guide in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
Video Prompting Guide
Best practices for writing effective AI video generation prompts via inference.sh.

Quick Start
Requires inference.sh CLI (
infsh). Install instructions
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
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
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
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
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
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
# 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
# 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@infsh-cli
Browse all video apps: infsh app list --category video
Documentation
- Running Apps - How to run apps via CLI
- Video Generation Guide - Comprehensive video guide
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
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Reviews
- CChaitanya Patil★★★★★Dec 24, 2024
I recommend video-prompting-guide for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- VValentina White★★★★★Dec 20, 2024
video-prompting-guide fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- RRen Smith★★★★★Dec 12, 2024
video-prompting-guide reduced setup friction for our internal harness; good balance of opinion and flexibility.
- PPiyush G★★★★★Nov 15, 2024
Solid pick for teams standardizing on skills: video-prompting-guide is focused, and the summary matches what you get after install.
- AAva Gill★★★★★Nov 7, 2024
video-prompting-guide has been reliable in day-to-day use. Documentation quality is above average for community skills.
- MMia Malhotra★★★★★Nov 3, 2024
Registry listing for video-prompting-guide matched our evaluation — installs cleanly and behaves as described in the markdown.
- AAva Rao★★★★★Oct 26, 2024
video-prompting-guide fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- MMia Johnson★★★★★Oct 22, 2024
Useful defaults in video-prompting-guide — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- SShikha Mishra★★★★★Oct 6, 2024
video-prompting-guide is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- YYash Thakker★★★★★Sep 13, 2024
video-prompting-guide reduced setup friction for our internal harness; good balance of opinion and flexibility.
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