Install
openclaw skills install @yash-kavaiya/viral-reels-creatorFull-featured viral Reels creator and editor powered by ffmpeg. Use this skill whenever the user wants to create, edit, find, or produce viral Instagram Reels, TikTok videos, YouTube Shorts, or any vertical short-form video content. Triggers include: "create a reel", "make a viral video", "make a short video", "Instagram reel", "TikTok video", "YouTube Shorts", "vertical video", "reels editor", "video editor", "add subtitles to video", "auto captions", "merge clips", "slideshow video", "add music to video", "beat sync video", "sync cuts to music", "video transitions", "caption video", "color grade video", "slow motion", "speed ramp", "text animation on video", "video effects", "video overlay", "ken burns effect", "video filter", "find best moments in video", "find highlights", "scene detection", "export for TikTok", "export for multiple platforms", "batch export video", "viral hook", "viral opening", "make my video go viral", or any request involving ffmpeg-based video editing for social media. Also trigger when the user uploads video/image/audio files and asks to combine, trim, stylize, color grade, beat-sync, or export them as a reel. Supports all formats: mp4, mov, avi, mkv, webm, jpg, png, gif, mp3, wav, aac, and more.
openclaw skills install @yash-kavaiya/viral-reels-creatorA comprehensive ffmpeg-based skill for creating viral Instagram Reels, TikTok videos, and YouTube Shorts — including finding the best moments in raw footage, beat-synced editing, multi-platform export, and viral content strategy.
apt-get update && apt-get install -y ffmpeg fonts-noto fonts-noto-color-emoji fontconfig
# For scene detection + beat sync:
pip install --break-system-packages opencv-python numpy librosa soundfile
/mnt/user-data/uploads/ for user assets./home/claude/ before processing./mnt/user-data/outputs/ and present to user.| Property | Instagram / TikTok / YT Shorts |
|---|---|
| Resolution | 1080×1920 (9:16 portrait) |
| FPS | 30 fps (60fps for YouTube Shorts) |
| Max Duration | 90s (IG/FB) · 60s (TikTok/YT/Snap) |
| Codec | H.264 (libx264) |
| Audio Codec | AAC, 44100 Hz, stereo |
| Pixel Format | yuv420p |
| Container | .mp4 |
Base output flags (always use):
-c:v libx264 -preset slow -crf 18 -pix_fmt yuv420p -r 30 -c:a aac -ar 44100 -ac 2 -movflags +faststart
For full platform-specific specs and export commands → references/platform-specs.md
User Request
├── "Find best moments / highlights"?
│ └── Run scripts/scene-detect.py → get timestamps → trim clips
├── "Make it viral" / "viral hook"?
│ └── Load references/viral-hooks.md → apply hook formula
├── Single video input?
│ ├── Trim/Cut → Section: TRIMMING
│ ├── Add captions → load references/caption-templates.md
│ ├── Add music → Section: AUDIO MIXING
│ ├── Sync cuts to beats → load references/beat-sync.md + scripts/beat-detect.py
│ ├── Color grade → load references/color-grading.md
│ ├── Speed change → Section: SPEED RAMP
│ ├── Add effects/anim → load references/animations.md
│ └── Resize only → Section: RESIZING
├── Multiple video inputs?
│ └── Merge with transitions → load references/transitions.md
├── Images input (slideshow)?
│ └── Ken Burns / Slideshow → Section: SLIDESHOW
├── Export for multiple platforms?
│ └── Run scripts/batch-export.sh → exports all platforms at once
├── Full reel from scratch?
│ └── Combine all: scene detect → hook → content → beat sync → captions + music
└── "Make it look good" / generic?
└── Auto-resize + color grade (Golden Hour or Clarendon) + caption template + fade transitions
IMPORTANT: For captions, animations, color grading, transitions, viral strategy, beat sync, and platform specs — always read the corresponding reference file before generating ffmpeg commands.
When the user has raw footage and wants the best clips extracted:
# Find top 10 most visually interesting moments
python scripts/scene-detect.py raw_footage.mp4 --top 10 --thumbnail
# Extract a specific number of clips for a 30s reel (5s each = 6 clips)
python scripts/scene-detect.py raw_footage.mp4 --top 6 --clip-duration 5 --thumbnail
# For fast-paced content with many scene changes
python scripts/scene-detect.py video.mp4 --threshold 0.2 --top 15
# Output as JSON for further processing
python scripts/scene-detect.py video.mp4 --json > moments.json
Then trim each moment using the generated ffmpeg commands from the script output.
Load references/viral-hooks.md for the full strategy. Core principles:
The viral reel formula:
[0–3s] HOOK → Bold text claim or pattern interrupt
[3–7s] SETUP → Context, "here's what you'll see"
[7–20s] CONTENT → Core value, fast cuts, visual variety
[20–25s] PAYOFF → Reveal, transformation, punchline
[25–30s] CTA → "Save this", "Comment X for part 2"
Load references/beat-sync.md for the full workflow.
# Step 1: Detect beats
python scripts/beat-detect.py music.mp3
# → outputs timestamps like: 0.469, 0.938, 1.407, 1.876...
# Step 2: Use beat timestamps as cut points
# (see beat-sync.md for full ffmpeg multi-clip assembly)
# Step 3: Add zoom pulse on every beat (120 BPM = 2Hz)
ffmpeg -i video.mp4 -filter_complex "
zoompan=z='1+0.05*abs(sin(PI*t*2))':
x='iw/2-(iw/zoom/2)':y='ih/2-(ih/zoom/2)':d=1:s=1080x1920:fps=30
" OUTPUT_FLAGS zoom_pulse.mp4
# Scale + crop (fill frame — preferred for Reels)
ffmpeg -i input.mp4 -vf "scale=1080:1920:force_original_aspect_ratio=increase,crop=1080:1920" OUTPUT_FLAGS output.mp4
# Blurred background fill (cinematic — best for landscape source)
ffmpeg -i input.mp4 -filter_complex "
[0:v]scale=1080:1920:force_original_aspect_ratio=increase,crop=1080:1920,boxblur=20:5[bg];
[0:v]scale=1080:1920:force_original_aspect_ratio=decrease[fg];
[bg][fg]overlay=(W-w)/2:(H-h)/2
" OUTPUT_FLAGS output.mp4
# Fast trim (copy — no re-encode)
ffmpeg -ss 00:00:05 -i input.mp4 -t 00:00:30 -c copy trimmed.mp4
# Precise trim (re-encode for frame accuracy)
ffmpeg -i input.mp4 -ss 00:00:05 -to 00:00:35 OUTPUT_FLAGS trimmed.mp4
# 0.5x 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_FLAGS slow.mp4
# 2x speed
ffmpeg -i input.mp4 -filter_complex "[0:v]setpts=0.5*PTS[v];[0:a]atempo=2.0[a]" -map "[v]" -map "[a]" OUTPUT_FLAGS fast.mp4
# Speed ramp: normal → slow → normal
ffmpeg -i input.mp4 -filter_complex "
[0:v]trim=0:3,setpts=PTS-STARTPTS[v1];
[0:v]trim=3:6,setpts=2*(PTS-STARTPTS)[v2];
[0:v]trim=6:10,setpts=PTS-STARTPTS[v3];
[v1][v2][v3]concat=n=3:v=1:a=0[v]
" -map "[v]" OUTPUT_FLAGS ramp.mp4
# Mix original audio + music (music at 30% volume)
ffmpeg -i video.mp4 -i music.mp3 -filter_complex "
[0:a]volume=1.0[voice];
[1:a]volume=0.3[music];
[voice][music]amix=inputs=2:duration=shortest
" -map 0:v OUTPUT_FLAGS output.mp4
# Fade music in/out
ffmpeg -i video.mp4 -i music.mp3 -filter_complex "
[1:a]afade=t=in:st=0:d=3,afade=t=out:st=27:d=3,volume=0.3[music];
[0:a]volume=1.0[voice];
[voice][music]amix=inputs=2:duration=shortest
" -map 0:v OUTPUT_FLAGS output.mp4
# Ken Burns (zoom + pan)
ffmpeg -loop 1 -i image.jpg -vf "
scale=2160:3840,
zoompan=z='min(zoom+0.001,1.5)':x='iw/2-(iw/zoom/2)':y='ih/2-(ih/zoom/2)':d=150:s=1080x1920:fps=30
" -t 5 OUTPUT_FLAGS kenburns.mp4
Always read the reference file before generating ffmpeg commands for these features.
| Feature | Reference File | What's Inside |
|---|---|---|
| Viral strategy & hooks | references/viral-hooks.md | Hook formulas, formats, retention tactics, CTAs |
| Beat-synced editing | references/beat-sync.md | Beat assembly, zoom pulse, drop effects |
| Multi-platform export | references/platform-specs.md | Specs, safe zones, aspect ratio variants |
| Caption Templates | references/caption-templates.md | 10 Instagram-style caption designs |
| Animations (50+) | references/animations.md | 50 text/video animations: bounce, typewriter, etc. |
| Color Grading | references/color-grading.md | 20 LUT-free color grades and Instagram filters |
| Transitions | references/transitions.md | 12+ transitions: fade, wipe, zoom, glitch, etc. |
| Script | Purpose |
|---|---|
scripts/scene-detect.py | Find best/most viral-worthy moments in raw footage |
scripts/beat-detect.py | Detect beat timestamps for sync-cut editing |
scripts/batch-export.sh | Export one reel to Instagram, TikTok, YouTube, etc. |
Stack effects in a single -filter_complex. Order matters:
1. Scale/crop to 1080x1920
2. Apply color grading
3. Apply speed changes
4. Apply animations/effects
5. Overlay captions/text
6. Add transitions (for multi-clip)
Example: Full viral reel pipeline
ffmpeg -i clip1.mp4 -i music.mp3 -filter_complex "
[0:v]scale=1080:1920:force_original_aspect_ratio=increase,crop=1080:1920,
eq=brightness=0.06:saturation=1.4:contrast=1.05,
vignette=PI/5,
drawtext=text='Wait for it...':fontfile=/usr/share/fonts/truetype/noto/NotoSans-Bold.ttf:
fontsize=72:fontcolor=white:borderw=4:bordercolor=black:
x=(w-tw)/2:y=(h-th)/2:enable='between(t,0,3)',
drawtext=text='Your Caption Here':fontfile=/usr/share/fonts/truetype/noto/NotoSans-Bold.ttf:
fontsize=56:fontcolor=white:borderw=3:bordercolor=black:
x=(w-tw)/2:y=h-th-250:enable='between(t,3,28)',
drawtext=text='Save this!':fontfile=/usr/share/fonts/truetype/noto/NotoSans-Bold.ttf:
fontsize=40:fontcolor=yellow:borderw=3:bordercolor=black:
x=(w-tw)/2:y=h-th-120:enable='between(t,25,30)',
fade=t=in:st=0:d=1,fade=t=out:st=28:d=2[v];
[1:a]afade=t=in:st=0:d=2,afade=t=out:st=27:d=3,volume=0.4[a]
" -map "[v]" -map "[a]" -t 30 \
-c:v libx264 -preset slow -crf 18 -pix_fmt yuv420p -r 30 \
-c:a aac -ar 44100 -ac 2 -movflags +faststart \
/mnt/user-data/outputs/reel_final.mp4
After finishing the reel, export for all platforms at once:
bash scripts/batch-export.sh /mnt/user-data/outputs/reel_final.mp4 my_reel all
# Creates: my_reel_instagram.mp4, my_reel_tiktok.mp4, my_reel_youtube_shorts.mp4,
# my_reel_facebook.mp4, my_reel_snapchat.mp4, my_reel_pinterest.mp4
Or export to specific platforms:
bash scripts/batch-export.sh reel.mp4 cooking_video instagram,tiktok,youtube
# Animated logo (fade in, semi-transparent)
ffmpeg -i video.mp4 -i logo.png -filter_complex "
[1:v]scale=120:-1,format=rgba,colorchannelmixer=aa=0.7[logo];
[0:v][logo]overlay=W-w-30:H-h-30
" OUTPUT_FLAGS output.mp4
pip install --break-system-packages openai-whisper pysrt
import whisper
model = whisper.load_model("base")
result = model.transcribe("audio.mp3", word_timestamps=True)
with open("captions.srt", "w") as f:
for i, seg in enumerate(result["segments"], 1):
start = seg["start"]
end = seg["end"]
text = seg["text"].strip()
f.write(f"{i}\n")
f.write(f"{int(start//3600):02}:{int(start%3600//60):02}:{start%60:06.3f} --> ")
f.write(f"{int(end//3600):02}:{int(end%3600//60):02}:{end%60:06.3f}\n")
f.write(f"{text}\n\n")
Then burn captions (see references/caption-templates.md for styled options):
ffmpeg -i video.mp4 -vf "subtitles=captions.srt:force_style='FontSize=22,PrimaryColour=&Hffffff,OutlineColour=&H000000,Outline=2,Alignment=2'" OUTPUT_FLAGS output.mp4
ffprobe -i input.mp4 -show_streams -select_streams a-an or generate silent audio: -f lavfi -i anullsrcapt-get install -y fonts-noto fonts-liberation-t 5 -preset ultrafast to render only 5 secondsfontfile=/usr/share/fonts/truetype/noto/NotoColorEmoji.ttf-movflags +faststart for web/mobile playbackBefore delivering the final video:
/mnt/user-data/outputs/batch-export.sh if needed