media-processing▌
mrgoonie/claudekit-skills · updated Apr 8, 2026
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Process video, audio, and images using FFmpeg and ImageMagick command-line tools for conversion, optimization, streaming, and manipulation tasks.
Media Processing Skill
Process video, audio, and images using FFmpeg and ImageMagick command-line tools for conversion, optimization, streaming, and manipulation tasks.
When to Use This Skill
Use when:
- Converting media formats (video, audio, images)
- Encoding video with codecs (H.264, H.265, VP9, AV1)
- Processing images (resize, crop, effects, watermarks)
- Extracting audio from video
- Creating streaming manifests (HLS/DASH)
- Generating thumbnails and previews
- Batch processing media files
- Optimizing file sizes and quality
- Applying filters and effects
- Creating composite images or videos
Tool Selection Guide
FFmpeg: Video/Audio Processing
Use FFmpeg for:
- Video encoding, conversion, transcoding
- Audio extraction, conversion, mixing
- Live streaming (RTMP, HLS, DASH)
- Video filters (scale, crop, rotate, overlay)
- Hardware-accelerated encoding
- Media file inspection (ffprobe)
- Frame extraction, concatenation
- Codec selection and optimization
ImageMagick: Image Processing
Use ImageMagick for:
- Image format conversion (PNG, JPEG, WebP, GIF)
- Resizing, cropping, transformations
- Batch image processing (mogrify)
- Visual effects (blur, sharpen, sepia)
- Text overlays and watermarks
- Image composition and montages
- Color adjustments, filters
- Thumbnail generation
Decision Matrix
| Task | Tool | Why |
|---|---|---|
| Video encoding | FFmpeg | Native video codec support |
| Audio extraction | FFmpeg | Direct stream manipulation |
| Image resize | ImageMagick | Optimized for still images |
| Batch images | ImageMagick | mogrify for in-place edits |
| Video thumbnails | FFmpeg | Frame extraction built-in |
| GIF creation | FFmpeg or ImageMagick | FFmpeg for video source, ImageMagick for images |
| Streaming | FFmpeg | Live streaming protocols |
| Image effects | ImageMagick | Rich filter library |
Installation
macOS
brew install ffmpeg imagemagick
Ubuntu/Debian
sudo apt-get install ffmpeg imagemagick
Windows
# Using winget
winget install ffmpeg
winget install ImageMagick.ImageMagick
# Or download binaries
# FFmpeg: https://ffmpeg.org/download.html
# ImageMagick: https://imagemagick.org/script/download.php
Verify Installation
ffmpeg -version
ffprobe -version
magick -version
# or
convert -version
Quick Start Examples
Video Conversion
# Convert format (copy streams, fast)
ffmpeg -i input.mkv -c copy output.mp4
# Re-encode with H.264
ffmpeg -i input.avi -c:v libx264 -crf 22 -c:a aac output.mp4
# Resize video to 720p
ffmpeg -i input.mp4 -vf scale=-1:720 -c:a copy output.mp4
Audio Extraction
# Extract audio (no re-encoding)
ffmpeg -i video.mp4 -vn -c:a copy audio.m4a
# Convert to MP3
ffmpeg -i video.mp4 -vn -q:a 0 audio.mp3
Image Processing
# Convert format
magick input.png output.jpg
# Resize maintaining aspect ratio
magick input.jpg -resize 800x600 output.jpg
# Create square thumbnail
magick input.jpg -resize 200x200^ -gravity center -extent 200x200 thumb.jpg
Batch Image Resize
# Resize all JPEGs to 800px width
mogrify -resize 800x -quality 85 *.jpg
# Output to separate directory
mogrify -path ./output -resize 800x600 *.jpg
Video Thumbnail
# Extract frame at 5 seconds
ffmpeg -ss 00:00:05 -i video.mp4 -vframes 1 -vf scale=320:-1 thumb.jpg
HLS Streaming
# Generate HLS playlist
ffmpeg -i input.mp4 \
-c:v libx264 -preset fast -crf 22 -g 48 \
-c:a aac -b:a 128k \
-f hls -hls_time 6 -hls_playlist_type vod \
playlist.m3u8
Image Watermark
# Add watermark to corner
magick input.jpg watermark.png -gravity southeast \
-geometry +10+10 -composite output.jpg
Common Workflows
Optimize Video for Web
# H.264 with good compression
ffmpeg -i input.mp4 \
-c:v libx264 -preset slow -crf 23 \
-c:a aac -b:a 128k \
-movflags +faststart \
output.mp4
Create Responsive Images
# Generate multiple sizes
for size in 320 640 1024 1920; do
magick input.jpg -resize ${size}x -quality 85 "output-${size}w.jpg"
done
Extract Video Segment
# From 1:30 to 3:00 (re-encode for precision)
ffmpeg -i input.mp4 -ss 00:01:30 -to 00:03:00 \
-c:v libx264 -c:a aac output.mp4
Batch Image Optimization
# Convert PNG to optimized JPEG
mogrify -path ./optimized -format jpg -quality 85 -strip *.png
Video GIF Creation
# High quality GIF with palette
ffmpeg -i input.mp4 -vf "fps=15,scale=640:-1:flags=lanczos,split[s0][s1];[s0]palettegen[p];[s1][p]paletteuse" output.gif
Image Blur Effect
# Gaussian blur
magick input.jpg -gaussian-blur 0x8 output.jpg
Advanced Techniques
Multi-Pass Video Encoding
# Pass 1 (analysis)
ffmpeg -y -i input.mkv -c:v libx264 -b:v 2600k -pass 1 -an -f null /dev/null
# Pass 2 (encoding)
ffmpeg -i input.mkv -c:v libx264 -b:v 2600k -pass 2 -c:a aac output.mp4
Hardware-Accelerated Encoding
# NVIDIA NVENC
ffmpeg -hwaccel cuda -i input.mp4 -c:v h264_nvenc -preset fast -crf 22 output.mp4
# Intel QuickSync
ffmpeg -hwaccel qsv -c:v h264_qsv -i input.mp4 -c:v h264_qsv output.mp4
Complex Image Pipeline
# Resize, crop, border, adjust
magick input.jpg \
-resize 1000x1000^ \
-gravity center \
-crop 1000x1000+0+0 +repage \
-bordercolor black -border 5x5 \
-brightness-contrast 5x10 \
-quality 90 \
output.jpg
Video Filter Chains
# Scale, denoise, watermark
ffmpeg -i video.mp4 -i logo.png \
-filter_complex "[0:v]scale=1280:720,hqdn3d[v];[v][1:v]overlay=10:10" \
-c:a copy output.mp4
Animated GIF from Images
# Create with delay
magick -delay 100 -loop 0 frame*.png animated.gif
# Optimize size
magick animated.gif -fuzz 5% -layers Optimize optimized.gif
Media Analysis
Inspect Video Properties
# Detailed JSON output
ffprobe -v quiet -print_format json -show_format -show_streams input.mp4
# Get resolution
ffprobe -v error -select_streams v:0 \
-show_entries stream=width,height \
-of csv=s=x:p=0 input.mp4
Image Information
# Basic info
identify image.jpg
# Detailed format
identify -verbose image.jpg
# Custom format
identify -format "%f: %wx%h %b\n" image.jpg
Performance Tips
- Use CRF for quality control - Better than bitrate for video
- Copy streams when possible - Avoid re-encoding with
-c copy - Hardware acceleration - GPU encoding 5-10x faster
- Appropriate presets - Balance speed vs compression
- Batch with mogrify - In-place image processing
- Strip metadata - Reduce file size with
-strip - Progressive JPEG - Better web loading with
-interlace Plane - Limit memory - Prevent crashes on large batches
- Test on samples - Verify settings before batch
- Parallel processing - Use GNU Parallel for multiple files
Reference Documentation
Detailed guides in references/:
- ffmpeg-encoding.md - Video/audio codecs, quality optimization, hardware acceleration
- ffmpeg-streaming.md - HLS/DASH, live streaming, adaptive bitrate
- ffmpeg-filters.md - Video/audio filters, complex filtergraphs
- imagemagick-editing.md - Format conversion, effects, transformations
- imagemagick-batch.md - Batch processing, mogrify, parallel operations
- format-compatibility.md - Format support, codec recommendations
Common Parameters
FFmpeg Video
-c:v- Video codec (libx264, libx265, libvpx-vp9)-crf- Quality (0-51, lower=better, 23=default)-preset- Speed/compression (ultrafast to veryslow)-b:v- Video bitrate (e.g., 2M, 2500k)-vf- Video filters
FFmpeg Audio
-c:a- Audio codec (aac, mp3, opus)-b:a- Audio bitrate (e.g., 128k, 192k)-ar- Sample rate (44100, 48000)
ImageMagick Geometry
800x600- Fit within (maintains aspect)800x600!- Force exact size800x600^- Fill (may crop)800x- Width onlyx600- Height only50%- Scale percentage
Troubleshooting
FFmpeg "Unknown encoder"
# Check available encoders
ffmpeg How to use media-processing 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 media-processing
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches media-processing from GitHub repository mrgoonie/claudekit-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 media-processing. Access the skill through slash commands (e.g., /media-processing) 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▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★61 reviews- ★★★★★Pratham Ware· Dec 16, 2024
Keeps context tight: media-processing is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Nia Zhang· Dec 16, 2024
media-processing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Hiroshi Harris· Dec 12, 2024
We added media-processing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Mia Haddad· Dec 4, 2024
Solid pick for teams standardizing on skills: media-processing is focused, and the summary matches what you get after install.
- ★★★★★Mia Malhotra· Nov 23, 2024
media-processing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Yash Thakker· Nov 7, 2024
media-processing has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Advait Kim· Nov 7, 2024
Solid pick for teams standardizing on skills: media-processing is focused, and the summary matches what you get after install.
- ★★★★★Sakura Rao· Nov 7, 2024
Useful defaults in media-processing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Sakura Smith· Nov 3, 2024
media-processing reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Dhruvi Jain· Oct 26, 2024
Solid pick for teams standardizing on skills: media-processing is focused, and the summary matches what you get after install.
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