video-prompting-guide

inferen-sh/skills · updated Apr 18, 2026

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$npx skills add https://github.com/inferen-sh/skills --skill video-prompting-guide
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summary

Structured prompting techniques for generating high-quality videos across multiple AI platforms.

  • Covers eight video generation models (Veo, Seedance, Wan, Grok, Kling, Runway, Pika, Sora) with model-specific optimization tips
  • Provides a reusable prompt formula combining shot type, subject, action, setting, lighting, style, and technical parameters
  • Includes reference tables for shot types, camera movements, lighting keywords, and visual aesthetics with practical examples
  • Demonstrat
skill.md

Video Prompting Guide

Best practices for writing effective AI video generation prompts via inference.sh.

Video Prompting Guide

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

how to use video-prompting-guide

How to use video-prompting-guide on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add video-prompting-guide
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/inferen-sh/skills --skill video-prompting-guide

The skills CLI fetches video-prompting-guide from GitHub repository inferen-sh/skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/video-prompting-guide

Reload or restart Cursor to activate video-prompting-guide. Access the skill through slash commands (e.g., /video-prompting-guide) or your agent's skill management interface.

Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

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

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate 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

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.732 reviews
  • Sofia Martinez· Dec 28, 2024

    video-prompting-guide is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Ira Martinez· Dec 20, 2024

    Keeps context tight: video-prompting-guide is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Maya Tandon· Nov 27, 2024

    Keeps context tight: video-prompting-guide is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Sofia Mehta· Nov 19, 2024

    video-prompting-guide reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Amina Liu· Nov 11, 2024

    Registry listing for video-prompting-guide matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Lucas Taylor· Oct 18, 2024

    video-prompting-guide is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Sofia Rahman· Oct 10, 2024

    Registry listing for video-prompting-guide matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ishan Khan· Oct 2, 2024

    video-prompting-guide reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Mei Iyer· Sep 25, 2024

    video-prompting-guide fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yuki Perez· Sep 21, 2024

    I recommend video-prompting-guide for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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