video-to-gif▌
zc277584121/marketing-skills · updated May 22, 2026
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Convert a video file into multiple GIF variants with different parameters, so the user can visually compare and pick the best one.
Skill: Video to GIF
Convert a video file into multiple GIF variants with different parameters, so the user can visually compare and pick the best one.
Prerequisite: FFmpeg and uv must be installed. gifsicle is optional (enables lossy compression variants).
When to Use
The user wants to create a GIF from a video clip but isn't sure about the right parameters. GIF quality involves tradeoffs between:
- File size — smaller is better for sharing/embedding
- Color accuracy — fewer colors = smaller but may cause banding
- Smoothness — higher FPS = smoother but larger
- Resolution — wider = sharper detail but larger
Rather than guessing, this skill generates multiple variants and lets the user decide.
Default Workflow
When the user provides a video file:
uv run --python 3.12 /path/to/skills/video-to-gif/scripts/video_to_gif.py <input.mp4>
This generates GIFs in <input>_gifs/ directory with the full preset (18 variants):
- 3 FPS options: 10, 15, 20
- 3 widths: 480px, 640px, 800px
- 2 color counts: 128, 256
Output includes a sorted comparison table showing file size, FPS, width, and colors for each variant.
Presets
| Preset | Variants | Best For |
|---|---|---|
full |
~18 | General use — broad exploration of the parameter space |
minimal |
~4 | Quick comparison — just a few key tradeoff points |
lossy |
~12 | Smallest files — includes gifsicle lossy compression levels |
quality |
~12 | Best visuals — higher res, includes bayer dithering |
# Quick comparison with fewer variants
uv run --python 3.12 .../video_to_gif.py input.mp4 --presets minimal
# Include lossy compression (requires gifsicle)
uv run --python 3.12 .../video_to_gif.py input.mp4 --presets lossy
# Higher quality focus
uv run --python 3.12 .../video_to_gif.py input.mp4 --presets quality
Common Options
| Flag | Default | Description |
|---|---|---|
-o, --output-dir |
<input>_gifs/ |
Output directory for all GIF variants |
--start |
none | Start time in seconds (trim source) |
--end |
none | End time in seconds (trim source) |
--presets |
full |
Preset config: full, minimal, lossy, quality |
--fps |
preset | Override FPS values (e.g., --fps 10 15 20) |
--width |
preset | Override width values (e.g., --width 480 640) |
--colors |
preset | Override color counts (e.g., --colors 128 256) |
--lossy |
preset | Gifsicle lossy levels (e.g., --lossy 0 30 80) |
Examples
# Convert first 10 seconds of a video
uv run --python 3.12 .../video_to_gif.py demo.mp4 --end 10
# Extract a specific segment
uv run --python 3.12 .../video_to_gif.py demo.mp4 --start 5 --end 15
# Custom parameter sweep
uv run --python 3.12 .../video_to_gif.py demo.mp4 --fps 12 15 --width 480 800 --colors 256
# Lossy compression comparison (needs gifsicle)
uv run --python 3.12 .../video_to_gif.py demo.mp4 --lossy 0 30 60 100
How to Choose
After running, open the output directory and compare:
- Start with the smallest files — check if quality is acceptable
- Look for color banding — if visible, try 256 colors or bayer dithering (quality preset)
- Check smoothness — if too choppy, go up to 15 or 20 FPS
- Check clarity — if text is unreadable, go up to 640 or 800px width
The sweet spot for most screen recordings is usually around 640px, 15fps, 256 colors.
Important Notes
- Widths larger than the source video resolution are automatically skipped.
- The script uses FFmpeg's two-pass palette generation for optimal GIF quality (much better than single-pass).
- Lossy compression via gifsicle can reduce file size by 30-70% with minimal visual impact at level 30-60.
- For very long clips, consider trimming with
--start/--endfirst — GIFs over 10 seconds can get very large.
How to use video-to-gif 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 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-to-gif
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches video-to-gif from GitHub repository zc277584121/marketing-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate video-to-gif. Access the skill through slash commands (e.g., /video-to-gif) 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
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.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 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▌
- 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
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★62 reviews- ★★★★★Yusuf Thompson· Dec 28, 2024
We added video-to-gif from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Emma Mehta· Dec 28, 2024
Registry listing for video-to-gif matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Benjamin Abebe· Dec 12, 2024
I recommend video-to-gif for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yusuf Martin· Dec 4, 2024
video-to-gif reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Yusuf Yang· Nov 23, 2024
video-to-gif is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Nia Martinez· Nov 19, 2024
Keeps context tight: video-to-gif is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Diya Thompson· Nov 3, 2024
Solid pick for teams standardizing on skills: video-to-gif is focused, and the summary matches what you get after install.
- ★★★★★Camila Chen· Oct 22, 2024
video-to-gif has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Fatima Johnson· Oct 14, 2024
Keeps context tight: video-to-gif is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Yusuf Sharma· Oct 10, 2024
video-to-gif is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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