image-to-video
Convert still images to animated videos with model selection, motion prompting, and camera control.
Works with
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2
this week
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Install Skill
Run in your terminal
2
installs
2
this week
304
stars
What it does
Six models available (Wan 2.5 i2v, Seedance, Fabric, Grok) with guidance on when to use each based on content type and motion style
Motion prompting framework covering camera movement (pan, dolly, orbit, crane), subject motion (natural elements, character, liquid), and atmospheric effects
Best practices emphasizing subtle motion over dramatic action, with structured prompt templates an
Installation Guide
How to use image-to-video 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
image-to-video
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches image-to-video from inferen-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 image-to-video. Access via /image-to-video 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
Image to Video
Convert still images to animated videos via inference.sh CLI.
Quick Start
Requires inference.sh CLI (
infsh). Install instructions
infsh login
# Generate a still image
infsh app run falai/flux-dev-lora --input '{
"prompt": "serene mountain lake at sunset, snow-capped peaks reflected in still water, golden hour light, landscape photography",
"width": 1248,
"height": 832
}'
# Animate it
infsh app run falai/wan-2-5-i2v --input '{
"prompt": "gentle ripples on the lake surface, clouds slowly drifting, warm light shifting, birds flying in the distance",
"image": "path/to/lake-image.png"
}'
Model Selection
| Model | App ID | Best For | Motion Style |
|---|---|---|---|
| Wan 2.5 i2v | falai/wan-2-5-i2v |
Realistic motion, natural movement | Photorealistic, subtle |
| WAN-I2V (Pruna) | pruna/wan-i2v |
Economical, fast, 480p/720p | Natural, efficient |
| Seedance 1.5 Pro | bytedance/seedance-1-5-pro |
Stylized, creative, animation-like | Artistic, expressive |
| Seedance 1.0 Pro | bytedance/seedance-1-0-pro |
General purpose, good quality | Balanced |
| Fabric 1.0 | falai/fabric-1-0 |
Cloth, fabric, liquid, flowing materials | Physics-based flow |
| Grok Imagine Video | xai/grok-imagine-video |
General animation, text-guided | Versatile |
When to Use Each
| Scenario | Best Model | Why |
|---|---|---|
| Landscape with water/clouds | Wan 2.5 i2v | Best at natural, realistic motion |
| Portrait with subtle expression | Wan 2.5 i2v | Maintains face fidelity |
| Product with fabric/cloth | Fabric 1.0 | Specialized in material physics |
| Flag waving, curtain flowing | Fabric 1.0 | Cloth simulation |
| Illustrated/artistic image | Seedance | Matches stylized content |
| General "bring to life" | Seedance 1.5 Pro | Good all-rounder |
| Quick test/iteration | Seedance 1.0 Lite | Fastest, 720p |
Motion Types
Camera Movement
| Movement | Prompt Keyword | Effect |
|---|---|---|
| Push in / Dolly forward | "slow dolly forward", "camera pushes in" | Increasing intimacy/focus |
| Pull out / Dolly back | "camera pulls back", "slow zoom out" | Reveal, context |
| Pan left/right | "camera pans slowly to the right" | Scanning, following |
| Tilt up/down | "camera tilts upward" | Revealing height |
| Orbit | "camera orbits around the subject" | 3D exploration |
| Crane up | "camera rises upward" | Grand reveal |
| Static | (no camera movement prompt) | Subject motion only |
Subject Motion
| Type | Prompt Examples |
|---|---|
| Natural elements | "water rippling", "clouds drifting", "leaves rustling in breeze" |
| Hair/clothing | "hair blowing gently in wind", "dress fabric flowing" |
| Atmospheric | "fog slowly rolling", "dust particles floating in light beams" |
| Character | "person slowly turns to camera", "subtle breathing motion" |
| Mechanical | "gears turning", "clock hands moving" |
| Liquid | "coffee steam rising", "paint dripping", "water pouring" |
Prompting Best Practices
The Golden Rule: Subtle > Dramatic
AI video models produce better results with gentle, subtle motion than dramatic action. Requesting too much movement causes distortion and artifacts.
❌ "person running and jumping over obstacles while the camera spins"
✅ "person slowly walking forward, gentle breeze, camera follows alongside"
❌ "explosion with debris flying everywhere"
✅ "candle flame flickering gently, warm ambient light shifting"
❌ "fast zoom into the eyes with dramatic camera shake"
✅ "slow dolly forward toward the subject, subtle focus shift"
Prompt Structure
[Camera movement] + [Subject motion] + [Atmospheric effects] + [Mood/pace]
Examples by Scenario
# Landscape animation
infsh app run falai/wan-2-5-i2v --input '{
"prompt": "gentle camera pan right, water reflecting moving clouds, trees swaying slightly in breeze, warm golden light, peaceful and slow",
"image": "landscape.png"
}'
# Portrait animation
infsh app run falai/wan-2-5-i2v --input '{
"prompt": "subtle breathing motion, slight head turn, natural eye blink, hair moving gently, soft ambient lighting shifts",
"image": "portrait.png"
}'
# Product shot animation
infsh app run bytedance/seedance-1-5-pro --input '{
"prompt": "slow 360 degree orbit around the product, gentle spotlight movement, subtle reflections shifting, premium product showcase, smooth motion",
"image": "product.png"
}'
# Fabric/cloth animation
infsh app run falai/fabric-1-0 --input '{
"prompt": "fabric flowing and rippling in gentle wind, natural cloth physics, soft movement",
"image": "fabric-scene.png"
}'
# Architectural visualization
infsh app run falai/wan-2-5-i2v --input '{
"prompt": "slow dolly forward through the entrance, slight camera tilt upward, ambient light filtering through windows, dust particles in light beams",
"image": "building-interior.png"
}'
Duration Guidelines
| Duration | Quality | Use For |
|---|---|---|
| 2-3 seconds | Highest quality | GIFs, looping backgrounds, cinemagraphs |
| 4-5 seconds | High quality | Social media posts, product reveals |
| 6-8 seconds | Good quality | Short clips, transitions |
| 10+ seconds | Quality degrades | Avoid unless stitching shorter clips |
Extending Duration
For longer videos, generate multiple short clips and stitch:
# Generate 3 clips from the same image with progressive motion
infsh app run falai/wan-2-5-i2v --input '{
"prompt": "slow pan left, gentle water motion",
"image": "scene.png"
}' --no-wait
infsh app run falai/wan-2-5-i2v --input '{
"prompt": "continuing pan, clouds shifting, light changing",
"image": "scene.png"
}' --no-wait
# Stitch together
infsh app run infsh/media-merger --input '{
"media": ["clip1.mp4", "clip2.mp4"]
}'
The Full Workflow
Still-to-Final-Video Pipeline
# 1. Generate source image (best quality)
infsh app run bytedance/seedream-4-5 --input '{
"prompt": "cinematic landscape, misty mountains at dawn, lake in foreground, dramatic clouds, golden hour, 4K quality, professional photography",
"size": "2K"
}'
# 2. Animate the image
infsh app run falai/wan-2-5-i2v --input '{
"prompt": "gentle mist rolling through the valley, lake surface rippling, clouds slowly moving, birds in distance, warm light shifting",
"image": "landscape.png"
}'
# 3. Upscale video if needed
infsh app run falai/topaz-video-upscaler --input '{
"video": "animated-landscape.mp4"
}'
# 4. Add ambient audio
infsh app run infsh/hunyuanvideo-foley --input '{
"video": "animated-landscape.mp4",
"prompt": "gentle nature ambience, distant birds, soft wind, water lapping"
}'
# 5. Merge video with audio
infsh app run infsh/video-audio-merger --input '{
"video": "upscaled-landscape.mp4",
"audio": "ambient-audio.mp3"
}'
Cinemagraph Effect
A cinemagraph is a still photo where only one element moves (e.g., waterfall moving in an otherwise frozen scene). To achieve this:
- Generate the still image with the motion element clearly defined
- Prompt for motion only in that specific element
- Keep to 2-4 seconds for seamless looping
infsh app run falai/wan-2-5-i2v --input '{
"prompt": "only the waterfall is moving, everything else remains perfectly still, water cascading smoothly, rest of scene frozen",
"image": "waterfall-scene.png"
}'
Common Mistakes
| Mistake | Problem | Fix |
|---|---|---|
| Too much motion requested | Distortion, artifacts, warping | Subtle > dramatic, always |
| Wrong model for content type | Poor results | Use selection guide above |
| Clips too long (10s+) | Quality degrades significantly | Keep to 3-5 seconds, stitch if needed |
| No camera movement specified | Random/unpredictable motion | Always specify camera behavior |
| Conflicting motion directions | Chaotic, unnatural | One primary motion direction |
| Low-res source image | Low-res video output | Start with highest quality source |
| Complex action scenes | Models can't handle | Keep motion simple and natural |
Related Skills
npx skills add inference-sh/skills@ai-video-generation
npx skills add inference-sh/skills@ai-image-generation
npx skills add inference-sh/skills@p-video
npx skills add inference-sh/skills@video-prompting-guide
npx skills add inference-sh/skills@prompt-engineering
Browse all apps: infsh app list
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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7affaan-m/everything-claude-code
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6remotion-dev/skills
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Reviews
- AAmina Dixit★★★★★Dec 20, 2024
image-to-video fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- KKofi White★★★★★Dec 4, 2024
image-to-video is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- RRahul Santra★★★★★Nov 23, 2024
image-to-video fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- PPratham Ware★★★★★Oct 14, 2024
image-to-video has been reliable in day-to-day use. Documentation quality is above average for community skills.
- AAmina Lopez★★★★★Sep 21, 2024
Solid pick for teams standardizing on skills: image-to-video is focused, and the summary matches what you get after install.
- SSakshi Patil★★★★★Sep 17, 2024
Keeps context tight: image-to-video is the kind of skill you can hand to a new teammate without a long onboarding doc.
- IIsabella Desai★★★★★Sep 9, 2024
image-to-video is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- CChen Jain★★★★★Aug 28, 2024
image-to-video reduced setup friction for our internal harness; good balance of opinion and flexibility.
- KKofi Gill★★★★★Aug 12, 2024
I recommend image-to-video for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- CChaitanya Patil★★★★★Aug 8, 2024
We added image-to-video from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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