YouTube Transcript Skill

Download and analyze YouTube video transcripts with automatic frame extraction at visual reference points.

Usage

/youtube-transcript <youtube-url>

What This Skill Does

1. Downloads transcript with timestamps (YouTube auto-captions or manual subtitles)
2. Detects visual references in the text ("look at this diagram", "as you can see here")
3. Extracts frames at those timestamps for context
4. Presents transcript with embedded images for analysis

Requirements

macOS

brew install yt-dlp ffmpeg

Linux (Ubuntu/Debian)

sudo apt install ffmpeg
pip install yt-dlp

Linux (Arch)

sudo pacman -S yt-dlp ffmpeg

Instructions for Claude

When the user invokes /youtube-transcript <url>:

Step 1: Check Dependencies

command -v yt-dlp >/dev/null 2>&1 || echo "MISSING: yt-dlp"
command -v ffmpeg >/dev/null 2>&1 || echo "MISSING: ffmpeg"

If missing, show installation instructions for the user's platform.

Step 2: Create Output Directory

Use the scratchpad directory for output:

# Extract video ID from YouTube URL (POSIX-compatible, works on macOS and Linux)
# Handles: youtube.com/watch?v=ID, youtu.be/ID, youtube.com/embed/ID
URL="<url>"
VIDEO_ID=$(echo "$URL" | sed -E 's/.*[?&]v=([^&]+).*/\1/;s|.*/embed/([^?/]+).*|\1|;s|.*youtu\.be/([^?/]+).*|\1|')
OUTPUT_DIR="<scratchpad>/youtube-${VIDEO_ID}"
mkdir -p "${OUTPUT_DIR}/frames"

Step 3: Download Transcript

cd "${OUTPUT_DIR}"

# Try auto-generated subtitles first, fall back to manual
yt-dlp --write-auto-sub --sub-lang en,de --skip-download --convert-subs srt -o "transcript" "<url>" 2>/dev/null || \
yt-dlp --write-sub --sub-lang en,de --skip-download --convert-subs srt -o "transcript" "<url>"

Step 4: Analyze for Visual References

Read the transcript and identify timestamps where visual content is referenced. Look for patterns:

German:

• "schau(t)? (mal )?(hier|das)"
• "(dieses|das|dieser) (Diagramm|Bild|Schema|Chart|Graph|Screen|Slide)"
• "wie (du|ihr|Sie) (hier )?(siehst|sehen)"
• "auf (dem|diesem) (Bildschirm|Screen|Slide)"
• "hier sehen wir"

English:

• "look at this"
• "as you can see"
• "this (diagram|chart|slide|screen|image)"
• "let me show you"
• "here we have"
• "on the screen"

Step 5: Download Video and Extract Frames

Only if visual references were found:

# First, list available formats to find a working one
yt-dlp -F "<url>"

# Then download using a specific format ID (prefer combined formats like 18 for 360p)
# Format 18 is usually 360p mp4 with video+audio combined - most reliable
yt-dlp -f 18 -o "${OUTPUT_DIR}/video.mp4" "<url>"

# If format 18 not available, try other combined formats (22=720p, 18=360p)
# Or use: yt-dlp -f "best[height<=480]" -o "${OUTPUT_DIR}/video.mp4" "<url>"

# Extract frame at timestamp (example: 01:23)
ffmpeg -ss 00:01:23 -i "${OUTPUT_DIR}/video.mp4" -frames:v 1 -q:v 2 "${OUTPUT_DIR}/frames/01_23.jpg"

Important: Avoid -f worst or complex format selectors - they often hang due to yt-dlp JS runtime issues. Use explicit format IDs instead.

Extract frames for each detected visual reference timestamp.

Step 6: Present Results

Create a summary with:

1. Video metadata (title, duration, channel)
2. Full transcript with timestamps
3. Visual references - show the extracted frames inline where referenced
4. Ready for questions - offer to analyze specific parts

Example output format:

## Video: [Title]
**Channel:** [Channel Name]
**Duration:** [Duration]

---

## Transcript

[00:00] Introduction to the topic...

[01:23] As you can see in this diagram...
![Frame at 01:23](frames/01_23.jpg)

[02:45] Let's move on to the next point...

---

## Extracted Frames

| Timestamp | Context | Frame |
|-----------|---------|-------|
| 01:23 | "this diagram shows..." | frames/01_23.jpg |

---

Ready to answer questions about this video.

Cleanup

The output directory in scratchpad will be automatically cleaned up. If the user wants to keep the files, they should copy them to their project.

Limitations

• Requires yt-dlp and ffmpeg installed locally
• Some videos may not have transcripts available
• Age-restricted or private videos may not be accessible
• Very long videos (>2h) may take time to process

Troubleshooting

No transcript found:

• Video may not have captions enabled
• Try a different language: --sub-lang en,de,es,fr

Video download stuck at 0%:

• This is often caused by yt-dlp's format selection with JS runtime issues
• Solution: List formats first (yt-dlp -F <url>), then use explicit format ID (yt-dlp -f 18 <url>)
• Format 18 (360p mp4 combined) is usually the most reliable

JS Runtime Warning:

• yt-dlp may show "No supported JavaScript runtime" warning
• This is usually fine for downloads, but can cause format selection issues
• Install deno if needed: brew install deno or curl -fsSL https://deno.land/install.sh | sh

Connection timeouts:

• YouTube servers may be slow; retry with explicit format ID
• Kill stuck process: pkill -f "yt-dlp.*VIDEO_ID"

yt-dlp errors:

• Update yt-dlp: pip install -U yt-dlp or brew upgrade yt-dlp

ffmpeg errors:

• Ensure ffmpeg is installed with video codecs