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ffmpeg▌

digitalsamba/claude-code-video-toolkit · updated Apr 8, 2026

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$npx skills add https://github.com/digitalsamba/claude-code-video-toolkit --skill ffmpeg
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summary

Video and audio processing with format conversion, resizing, compression, and Remotion asset preparation.

  • ›Covers 10+ common operations: GIF-to-MP4 conversion, video resizing, compression, audio extraction, trimming, speed adjustment, concatenation, and fade effects
  • ›Includes Remotion-specific patterns for speed adjustment, demo recording preparation, and batch GIF conversion with proper codec settings
  • ›Provides platform-specific optimization workflows for YouTube, Twitter/X, LinkedIn,
skill.md

FFmpeg for Video Production

FFmpeg is the essential tool for video/audio processing. This skill covers common operations for Remotion video projects.

Quick Reference

GIF to MP4 (Remotion-compatible)

ffmpeg -i input.gif -movflags faststart -pix_fmt yuv420p \
  -vf "scale=trunc(iw/2)*2:trunc(ih/2)*2" output.mp4

Why these flags:

  • -movflags faststart - Moves metadata to start for web streaming
  • -pix_fmt yuv420p - Ensures compatibility with most players
  • scale=trunc(...) - Forces even dimensions (required by most codecs)

Resize Video

# To 1920x1080 (maintain aspect ratio, add black bars)
ffmpeg -i input.mp4 -vf "scale=1920:1080:force_original_aspect_ratio=decrease,pad=1920:1080:(ow-iw)/2:(oh-ih)/2" output.mp4

# To 1920x1080 (crop to fill)
ffmpeg -i input.mp4 -vf "scale=1920:1080:force_original_aspect_ratio=increase,crop=1920:1080" output.mp4

# Scale to width, auto height
ffmpeg -i input.mp4 -vf "scale=1280:-2" output.mp4

Compress Video

# Good quality, smaller file (CRF 23 is default, lower = better quality)
ffmpeg -i input.mp4 -c:v libx264 -crf 23 -preset medium -c:a aac -b:a 128k output.mp4

# Aggressive compression for web preview
ffmpeg -i input.mp4 -c:v libx264 -crf 28 -preset fast -c:a aac -b:a 96k output.mp4

# Target file size (e.g., ~10MB for 60s video = ~1.3Mbps)
ffmpeg -i input.mp4 -c:v libx264 -b:v 1300k -c:a aac -b:a 128k output.mp4

Extract Audio

# Extract to MP3
ffmpeg -i input.mp4 -vn -acodec libmp3lame -q:a 2 output.mp3

# Extract to AAC
ffmpeg -i input.mp4 -vn -acodec aac -b:a 192k output.m4a

# Extract to WAV (uncompressed)
ffmpeg -i input.mp4 -vn output.wav

Convert Audio Formats

# M4A to MP3 (for ElevenLabs voice samples)
ffmpeg -i input.m4a -codec:a libmp3lame -qscale:a 2 output.mp3

# WAV to MP3
ffmpeg -i input.wav -codec:a libmp3lame -b:a 192k output.mp3

# Adjust volume
ffmpeg -i input.mp3 -filter:a "volume=1.5" output.mp3

Trim/Cut Video

# Cut from timestamp to duration (recommended - reliable)
ffmpeg -i input.mp4 -ss 00:00:30 -t 00:00:15 -c:v libx264 -c:a aac output.mp4

# Cut from timestamp to timestamp
ffmpeg -i input.mp4 -ss 00:00:30 -to 00:00:45 -c:v libx264 -c:a aac output.mp4

# Stream copy (faster but may lose frames at cut points)
# Only use when source has frequent keyframes
ffmpeg -i input.mp4 -ss 00:00:30 -t 00:00:15 -c copy output.mp4

Note: Re-encoding is recommended for trimming. Stream copy (-c copy) can silently drop video if the seek point doesn't align with a keyframe.

Speed Up / Slow Down

# 2x speed (video and audio)
ffmpeg -i input.mp4 -filter_complex "[0:v]setpts=0.5*PTS[v];[0:a]atempo=2.0[a]" -map "[v]" -map "[a]" output.mp4

# 0.5x speed (slow motion)
ffmpeg -i input.mp4 -filter_complex "[0:v]setpts=2.0*PTS[v];[0:a]atempo=0.5[a]" -map "[v]" -map "[a]" output.mp4

# Video only (no audio)
ffmpeg -i input.mp4 -filter:v "setpts=0.5*PTS" -an output.mp4

Concatenate Videos

# Create file list
echo "file 'clip1.mp4'" > list.txt
echo "file 'clip2.mp4'" >> list.txt
echo "file 'clip3.mp4'" >> list.txt

# Concatenate (same codec/resolution)
ffmpeg -f concat -safe 0 -i list.txt -c copy output.mp4

# Concatenate with re-encoding (different sources)
ffmpeg -f concat -safe 0 -i list.txt -c:v libx264 -c:a aac output.mp4

Add Fade In/Out

# Fade in first 1 second, fade out last 1 second (30fps video)
ffmpeg -i input.mp4 -vf "fade=t=in:st=0:d=1,fade=t=out:st=9:d=1" -c:a copy output.mp4

# Audio fade
ffmpeg -i input.mp4 -af "afade=t=in:st=0:d=1,afade=t=out:st=9:d=1" -c:v copy output.mp4

Get Video Info

# Duration, resolution, codec info
ffprobe -v error -show_entries format=duration -of default=noprint_wrappers=1:nokey=1 input.mp4

# Full info
ffprobe -v quiet -print_format json -show_format -show_streams input.mp4

Remotion-Specific Patterns

Video Speed Adjustment for Remotion

When to use FFmpeg vs Remotion playbackRate:

Scenario Use FFmpeg Use Remotion
Constant speed (1.5x, 2x) Either works ✅ Simpler
Extreme speeds (>4x or <0.25x) ✅ More reliable May have issues
Variable speed (accelerate over time) ✅ Pre-process Complex workaround needed
Need perfect audio sync ✅ Guaranteed Usually fine
Demo needs to fit voiceover timing ✅ Pre-calculate Runtime adjustment

Remotion limitation: playbackRate must be constant. Dynamic interpolation like playbackRate={interpolate(frame, [0, 100], [1, 5])} won't work correctly because Remotion evaluates frames independently.

# Speed up demo to fit a scene (e.g., 60s demo into 20s = 3x speed)
ffmpeg -i demo-raw.mp4 \
  -filter_complex "[0:v]setpts=0.333*PTS[v];[0:a]atempo=3.0[a]" \
  -map "[v]" -map "[a]" \
  public/demos/demo-fast.mp4

# Slow motion for emphasis (0.5x speed)
ffmpeg -i action.mp4 \
  -filter_complex "[0:v]setpts=2.0*PTS[v];[0:a]atempo=0.5[a]" \
  -map "[v]" -map "[a]" \
  public/demos/action-slow.mp4

# Speed up without audio (common for screen recordings)
ffmpeg -i demo.mp4 -filter:v "setpts=0.5*PTS" -an public/demos/demo-2x.mp4

# Timelapse effect (10x speed, drop audio)
ffmpeg -i long-demo.mp4 -filter:v "setpts=0.1*PTS" -an public/demos/timelapse.mp4

Calculate speed factor:

  • To fit X seconds of video into Y seconds of scene: speed = X / Y
  • setpts multiplier = 1 / speed (e.g., 3x speed = setpts=0.333*PTS)
  • atempo value = speed (e.g., 3x speed = atempo=3.0)

Extreme speed (>2x audio): Chain atempo filters (each limited to 0.5-2.0 range):

# 4x speed audio
-filter_complex "[0:a]atempo=2.0,atempo=2.0[a]"

# 8x speed audio
-filter_complex "[0:a]atempo=2.0,atempo=2.0,atempo=2.0[a]"

Prepare Demo Recording for Remotion

# Standard 1080p, 30fps, Remotion-ready
ffmpeg -i raw-recording.mp4 \
  -vf "scale=1920:1080:force_original_aspect_ratio=decrease,pad=1920:1080:(ow-iw)/2:(oh-ih)/2,fps=30" \
  -c:v libx264 -crf 18 -preset slow \
  -c:a aac -b:a 192k \
  -movflags faststart \
  public/demos/demo.mp4

Screen Recording to Remotion Asset

# From iPhone/iPad recording (usually 60fps, variable resolution)
ffmpeg -i iphone-recording.mov \
  -vf "scale=1920:-2,fps=30" \
  -c:v libx264 -crf 20 \
  -an \
  public/demos/mobile-demo.mp4

Batch Convert GIFs

for f in assets/*.gif; do
  ffmpeg -i "$f" -movflags faststart -pix_fmt yuv420p \
    -vf "scale=trunc(iw/2)*2:trunc(ih/2)*2" \
    "public/demos/$(basename "$f" .gif).mp4"
done

Common Issues

"Height not divisible by 2"

Add scale filter: -vf "scale=trunc(iw/2)*2:trunc(ih/2)*2"

Video won't play in browser

Use: -movflags faststart -pix_fmt yuv420p -c:v libx264

Audio out of sync after speed change

Use filter_complex with atempo: -filter_complex "[0:v]setpts=0.5*PTS[v];[0:a]atempo=2.0[a]"

File too large

Increase CRF (23→28) or reduce resolution

Quality Guidelines

Use Case CRF Preset Notes
Archive/Master 18 slow Best quality, large files
Production 20-22 medium Good balance
Web/Preview 23-25 fast Smaller files
Draft/Quick 28+ veryfast Fast encoding

Platform-Specific Output Optimization

After Remotion renders your video (typically to out/video.mp4), use FFmpeg to optimize for each distribution platform.

Workflow Integration

Remotion render (master)     FFmpeg optimization      Platform upload
       ↓                            ↓                       ↓
   out/video.mp4  ────────→  out/video-youtube.mp4  ───→  YouTube
                  ────────→  out/video-twitter.mp4  ───→  Twitter/X
                  ────────→  out/video-linkedin.mp4 ───→  LinkedIn
                  ────────→  out/video-web.mp4      ───→  Website embed

YouTube (Recommended Settings)

YouTube re-encodes everything, so upload high quality:

# YouTube optimized (1080p)
ffmpeg -i out/video.mp4 \
how to use ffmpeg

How to use ffmpeg 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 ffmpeg
2

Execute installation command

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

$npx skills add https://github.com/digitalsamba/claude-code-video-toolkit --skill ffmpeg

The skills CLI fetches ffmpeg from GitHub repository digitalsamba/claude-code-video-toolkit 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/ffmpeg

Reload or restart Cursor to activate ffmpeg. Access the skill through slash commands (e.g., /ffmpeg) 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.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

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. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 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▌

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

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

Ratings

4.6★★★★★30 reviews
  • ★★★★★Shikha Mishra· Dec 24, 2024

    Registry listing for ffmpeg matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Ganesh Mohane· Dec 20, 2024

    ffmpeg has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • ★★★★★Ishan Desai· Dec 8, 2024

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

  • ★★★★★Amelia Huang· Nov 27, 2024

    ffmpeg reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★Sakshi Patil· Nov 11, 2024

    Solid pick for teams standardizing on skills: ffmpeg is focused, and the summary matches what you get after install.

  • ★★★★★Amelia Rahman· Oct 18, 2024

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

  • ★★★★★Chaitanya Patil· Oct 2, 2024

    We added ffmpeg from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • ★★★★★Kiara Smith· Sep 5, 2024

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

  • ★★★★★Amina Perez· Aug 24, 2024

    Useful defaults in ffmpeg — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • ★★★★★Amina Farah· Jul 15, 2024

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

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