skills/youtube-metadata-updater/SKILL.md
Download a YouTube video, transcribe it, generate optimized title/description/chapters/tags, create a thumbnail, and update the video via YouTube Data API. Use when the user shares a YouTube URL and wants title, description, chapters, tags, or thumbnail updated. Triggers: 'update youtube', 'need title and description', 'add chapters', 'fix youtube metadata', 'generate thumbnail for youtube', or when user shares a youtube.com/watch URL and asks for metadata.
npx skillsauth add razbakov/skills youtube-metadata-updaterInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Given a YouTube video URL, produce and apply optimized metadata: title, description with chapters, tags, and a thumbnail.
yt-dlp (audio download)localhost:8000 (transcription)~/.config/youtube/token.json (created on first run)~/Projects/ikigai/.bin/youtube-update.py# Extract video ID from URL (the ?v= parameter)
VIDEO_ID="HOzfntvOXMY"
MEETING_DIR="<project>/meetings/YYYY-MM-DD"
mkdir -p "$MEETING_DIR"
uvx yt-dlp -f "bestaudio" -o "$MEETING_DIR/livestream.%(ext)s" \
"https://www.youtube.com/watch?v=$VIDEO_ID"
Also fetch existing metadata for context:
uvx yt-dlp --dump-json --no-download "https://www.youtube.com/watch?v=$VIDEO_ID" | \
python3 -c "import json,sys; d=json.load(sys.stdin); print('Title:', d.get('title')); print('Duration:', d.get('duration_string')); print('Channel:', d.get('channel'))"
The faster-whisper server crashes on large files. Split into 2-minute chunks and transcribe sequentially using the small model.
# Split into 2-min m4a chunks (copy codec, fast)
DURATION=$(ffprobe -v error -show_entries format=duration -of csv=p=0 "$MEETING_DIR/livestream.m4a" | cut -d. -f1)
CHUNK=120
for i in $(seq 0 $CHUNK $((DURATION - 1))); do
idx=$(printf "%02d" $((i / CHUNK)))
ffmpeg -i "$MEETING_DIR/livestream.m4a" -ss $i -t $CHUNK -c copy "/tmp/mchunk_${idx}.m4a" -y
done
Transcribe all chunks with offset correction:
# Use Systran/faster-whisper-small (not large-v3, crashes on CPU)
# Add chunk offset to each segment's start time
# Save combined result to $MEETING_DIR/transcription.txt
# Format: [M:SS] text
Key lessons:
Systran/faster-whisper-large-v3 crashes after 1-2 chunks on CPU — use smallRead the full transcript. Identify:
Output format — save to $MEETING_DIR/youtube-metadata.md:
# YouTube Metadata — [Series] Meeting #N (YYYY-MM-DD)
**Title:** [Clickable title under 70 chars]
**Description:**
[2-3 sentence summary]
[Series context line]
Chapters:
0:00 [First chapter]
...
[Links section]
#tag1 #tag2 ...
**Tags:** tag1, tag2, ...
Also save $MEETING_DIR/youtube-update.json for the API:
{
"title": "...",
"description": "...",
"tags": ["..."],
"categoryId": "28"
}
Category IDs: 22=People & Blogs, 27=Education, 28=Science & Technology.
Create an HTML file ($MEETING_DIR/thumbnail.html) at 1280x720px with:
Capture at 2x resolution:
google-chrome --headless --screenshot="$MEETING_DIR/thumbnail.png" \
--window-size=1280,720 --force-device-scale-factor=2 \
"$MEETING_DIR/thumbnail.html"
Show the thumbnail to the user for approval before uploading.
uvx --from google-api-python-client --with google-auth-oauthlib --with google-auth-httplib2 \
python3 ~/Projects/ikigai/.bin/youtube-update.py $VIDEO_ID \
--meta "$MEETING_DIR/youtube-update.json" \
--thumbnail "$MEETING_DIR/thumbnail.png"
First run requires OAuth browser authorization. Token is cached at ~/.config/youtube/token.json.
If YouTube Data API is not enabled, direct user to:
https://console.developers.google.com/apis/api/youtube.googleapis.com/overview?project=PROJECT_ID
Verify the update by showing the video URL and confirming the title was applied.
| File | Purpose |
|------|---------|
| livestream.m4a | Downloaded audio |
| transcription.txt | Timestamped transcript |
| youtube-metadata.md | Human-readable metadata reference |
| youtube-update.json | API payload |
| thumbnail.html | Thumbnail source |
| thumbnail.png | Uploaded thumbnail |
tools
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documentation
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data-ai
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development
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