Download YouTube video transcripts when user provides a YouTube URL or asks to download/get/fetch a transcript from YouTube. Also use when user wants to transcribe or get captions/subtitles from a YouTube video.
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
skills listSkill Instructions
name: youtube-transcript description: Download YouTube video transcripts when user provides a YouTube URL or asks to download/get/fetch a transcript from YouTube. Also use when user wants to transcribe or get captions/subtitles from a YouTube video. allowed-tools: Bash,Read,Write
YouTube Transcript Downloader
This skill helps download transcripts (subtitles/captions) from YouTube videos using yt-dlp.
When to Use This Skill
Activate this skill when the user:
- Provides a YouTube URL and wants the transcript
- Asks to "download transcript from YouTube"
- Wants to "get captions" or "get subtitles" from a video
- Asks to "transcribe a YouTube video"
- Needs text content from a YouTube video
How It Works
Priority Order:
- Check if yt-dlp is installed - install if needed
- List available subtitles - see what's actually available
- Try manual subtitles first (
--write-sub) - highest quality - Fallback to auto-generated (
--write-auto-sub) - usually available - Last resort: Whisper transcription - if no subtitles exist (requires user confirmation)
- Confirm the download and show the user where the file is saved
- Optionally clean up the VTT format if the user wants plain text
Installation Check
IMPORTANT: Always check if yt-dlp is installed first:
which yt-dlp || command -v yt-dlp
If Not Installed
Attempt automatic installation based on the system:
macOS (Homebrew):
brew install yt-dlp
Linux (apt/Debian/Ubuntu):
sudo apt update && sudo apt install -y yt-dlp
Alternative (pip - works on all systems):
pip3 install yt-dlp
# or
python3 -m pip install yt-dlp
If installation fails: Inform the user they need to install yt-dlp manually and provide them with installation instructions from https://github.com/yt-dlp/yt-dlp#installation
Check Available Subtitles
ALWAYS do this first before attempting to download:
yt-dlp --list-subs "YOUTUBE_URL"
This shows what subtitle types are available without downloading anything. Look for:
- Manual subtitles (better quality)
- Auto-generated subtitles (usually available)
- Available languages
Download Strategy
Option 1: Manual Subtitles (Preferred)
Try this first - highest quality, human-created:
yt-dlp --write-sub --skip-download --output "OUTPUT_NAME" "YOUTUBE_URL"
Option 2: Auto-Generated Subtitles (Fallback)
If manual subtitles aren't available:
yt-dlp --write-auto-sub --skip-download --output "OUTPUT_NAME" "YOUTUBE_URL"
Both commands create a .vtt file (WebVTT subtitle format).
Option 3: Whisper Transcription (Last Resort)
ONLY use this if both manual and auto-generated subtitles are unavailable.
Step 1: Show File Size and Ask for Confirmation
# Get audio file size estimate
yt-dlp --print "%(filesize,filesize_approx)s" -f "bestaudio" "YOUTUBE_URL"
# Or get duration to estimate
yt-dlp --print "%(duration)s %(title)s" "YOUTUBE_URL"
IMPORTANT: Display the file size to the user and ask: "No subtitles are available. I can download the audio (approximately X MB) and transcribe it using Whisper. Would you like to proceed?"
Wait for user confirmation before continuing.
Step 2: Check for Whisper Installation
command -v whisper
If not installed, ask user: "Whisper is not installed. Install it with pip install openai-whisper (requires ~1-3GB for models)? This is a one-time installation."
Wait for user confirmation before installing.
Install if approved:
pip3 install openai-whisper
Step 3: Download Audio Only
yt-dlp -x --audio-format mp3 --output "audio_%(id)s.%(ext)s" "YOUTUBE_URL"
Step 4: Transcribe with Whisper
# Auto-detect language (recommended)
whisper audio_VIDEO_ID.mp3 --model base --output_format vtt
# Or specify language if known
whisper audio_VIDEO_ID.mp3 --model base --language en --output_format vtt
Model Options (stick to base for now):
tiny- fastest, least accurate (~1GB)base- good balance (~1GB) ← USE THISsmall- better accuracy (~2GB)medium- very good (~5GB)large- best accuracy (~10GB)
Step 5: Cleanup
After transcription completes, ask user: "Transcription complete! Would you like me to delete the audio file to save space?"
If yes:
rm audio_VIDEO_ID.mp3
Getting Video Information
Extract Video Title (for filename)
yt-dlp --print "%(title)s" "YOUTUBE_URL"
Use this to create meaningful filenames based on the video title. Clean the title for filesystem compatibility:
- Replace
/with- - Replace special characters that might cause issues
- Consider using sanitized version:
$(yt-dlp --print "%(title)s" "URL" | tr '/' '-' | tr ':' '-')
Post-Processing
Convert to Plain Text (Recommended)
YouTube's auto-generated VTT files contain duplicate lines because captions are shown progressively with overlapping timestamps. Always deduplicate when converting to plain text while preserving the original speaking order.
python3 -c "
import sys, re
seen = set()
with open('transcript.en.vtt', 'r') as f:
for line in f:
line = line.strip()
if line and not line.startswith('WEBVTT') and not line.startswith('Kind:') and not line.startswith('Language:') and '-->' not in line:
clean = re.sub('<[^>]*>', '', line)
clean = clean.replace('&', '&').replace('>', '>').replace('<', '<')
if clean and clean not in seen:
print(clean)
seen.add(clean)
" > transcript.txt
Complete Post-Processing with Video Title
# Get video title
VIDEO_TITLE=$(yt-dlp --print "%(title)s" "YOUTUBE_URL" | tr '/' '_' | tr ':' '-' | tr '?' '' | tr '"' '')
# Find the VTT file
VTT_FILE=$(ls *.vtt | head -n 1)
# Convert with deduplication
python3 -c "
import sys, re
seen = set()
with open('$VTT_FILE', 'r') as f:
for line in f:
line = line.strip()
if line and not line.startswith('WEBVTT') and not line.startswith('Kind:') and not line.startswith('Language:') and '-->' not in line:
clean = re.sub('<[^>]*>', '', line)
clean = clean.replace('&', '&').replace('>', '>').replace('<', '<')
if clean and clean not in seen:
print(clean)
seen.add(clean)
" > "${VIDEO_TITLE}.txt"
echo "✓ Saved to: ${VIDEO_TITLE}.txt"
# Clean up VTT file
rm "$VTT_FILE"
echo "✓ Cleaned up temporary VTT file"
Output Formats
- VTT format (
.vtt): Includes timestamps and formatting, good for video players - Plain text (
.txt): Just the text content, good for reading or analysis
Tips
- The filename will be
{output_name}.{language_code}.vtt(e.g.,transcript.en.vtt) - Most YouTube videos have auto-generated English subtitles
- Some videos may have multiple language options
- If auto-subtitles aren't available, try
--write-subinstead for manual subtitles
Complete Workflow Example
VIDEO_URL="https://www.youtube.com/watch?v=dQw4w9WgXcQ"
# Get video title for filename
VIDEO_TITLE=$(yt-dlp --print "%(title)s" "$VIDEO_URL" | tr '/' '_' | tr ':' '-' | tr '?' '' | tr '"' '')
OUTPUT_NAME="transcript_temp"
# ============================================
# STEP 1: Check if yt-dlp is installed
# ============================================
if ! command -v yt-dlp &> /dev/null; then
echo "yt-dlp not found, attempting to install..."
if command -v brew &> /dev/null; then
brew install yt-dlp
elif command -v apt &> /dev/null; then
sudo apt update && sudo apt install -y yt-dlp
else
pip3 install yt-dlp
fi
fi
# ============================================
# STEP 2: List available subtitles
# ============================================
echo "Checking available subtitles..."
yt-dlp --list-subs "$VIDEO_URL"
# ============================================
# STEP 3: Try manual subtitles first
# ============================================
echo "Attempting to download manual subtitles..."
if yt-dlp --write-sub --skip-download --output "$OUTPUT_NAME" "$VIDEO_URL" 2>/dev/null; then
echo "✓ Manual subtitles downloaded successfully!"
ls -lh ${OUTPUT_NAME}.*
else
# ============================================
# STEP 4: Fallback to auto-generated
# ============================================
echo "Manual subtitles not available. Trying auto-generated..."
if yt-dlp --write-auto-sub --skip-download --output "$OUTPUT_NAME" "$VIDEO_URL" 2>/dev/null; then
echo "✓ Auto-generated subtitles downloaded successfully!"
ls -lh ${OUTPUT_NAME}.*
else
# ============================================
# STEP 5: Last resort - Whisper transcription
# ============================================
echo "⚠ No subtitles available for this video."
# Get file size
FILE_SIZE=$(yt-dlp --print "%(filesize_approx)s" -f "bestaudio" "$VIDEO_URL")
DURATION=$(yt-dlp --print "%(duration)s" "$VIDEO_URL")
TITLE=$(yt-dlp --print "%(title)s" "$VIDEO_URL")
echo "Video: $TITLE"
echo "Duration: $((DURATION / 60)) minutes"
echo "Audio size: ~$((FILE_SIZE / 1024 / 1024)) MB"
echo ""
echo "Would you like to download and transcribe with Whisper? (y/n)"
read -r RESPONSE
if [[ "$RESPONSE" =~ ^[Yy]$ ]]; then
# Check for Whisper
if ! command -v whisper &> /dev/null; then
echo "Whisper not installed. Install now? (requires ~1-3GB) (y/n)"
read -r INSTALL_RESPONSE
if [[ "$INSTALL_RESPONSE" =~ ^[Yy]$ ]]; then
pip3 install openai-whisper
else
echo "Cannot proceed without Whisper. Exiting."
exit 1
fi
fi
# Download audio
echo "Downloading audio..."
yt-dlp -x --audio-format mp3 --output "audio_%(id)s.%(ext)s" "$VIDEO_URL"
# Get the actual audio filename
AUDIO_FILE=$(ls audio_*.mp3 | head -n 1)
# Transcribe
echo "Transcribing with Whisper (this may take a few minutes)..."
whisper "$AUDIO_FILE" --model base --output_format vtt
# Cleanup
echo "Transcription complete! Delete audio file? (y/n)"
read -r CLEANUP_RESPONSE
if [[ "$CLEANUP_RESPONSE" =~ ^[Yy]$ ]]; then
rm "$AUDIO_FILE"
echo "Audio file deleted."
fi
ls -lh *.vtt
else
echo "Transcription cancelled."
exit 0
fi
fi
fi
# ============================================
# STEP 6: Convert to readable plain text with deduplication
# ============================================
VTT_FILE=$(ls ${OUTPUT_NAME}*.vtt 2>/dev/null || ls *.vtt | head -n 1)
if [ -f "$VTT_FILE" ]; then
echo "Converting to readable format and removing duplicates..."
python3 -c "
import sys, re
seen = set()
with open('$VTT_FILE', 'r') as f:
for line in f:
line = line.strip()
if line and not line.startswith('WEBVTT') and not line.startswith('Kind:') and not line.startswith('Language:') and '-->' not in line:
clean = re.sub('<[^>]*>', '', line)
clean = clean.replace('&', '&').replace('>', '>').replace('<', '<')
if clean and clean not in seen:
print(clean)
seen.add(clean)
" > "${VIDEO_TITLE}.txt"
echo "✓ Saved to: ${VIDEO_TITLE}.txt"
# Clean up temporary VTT file
rm "$VTT_FILE"
echo "✓ Cleaned up temporary VTT file"
else
echo "⚠ No VTT file found to convert"
fi
echo "✓ Complete!"
Note: This complete workflow handles all scenarios with proper error checking and user prompts at each decision point.
Error Handling
Common Issues and Solutions:
1. yt-dlp not installed
- Attempt automatic installation based on system (Homebrew/apt/pip)
- If installation fails, provide manual installation link
- Verify installation before proceeding
2. No subtitles available
- List available subtitles first to confirm
- Try both
--write-suband--write-auto-sub - If both fail, offer Whisper transcription option
- Show file size and ask for user confirmation before downloading audio
3. Invalid or private video
- Check if URL is correct format:
https://www.youtube.com/watch?v=VIDEO_ID - Some videos may be private, age-restricted, or geo-blocked
- Inform user of the specific error from yt-dlp
4. Whisper installation fails
- May require system dependencies (ffmpeg, rust)
- Provide fallback: "Install manually with:
pip3 install openai-whisper" - Check available disk space (models require 1-10GB depending on size)
5. Download interrupted or failed
- Check internet connection
- Verify sufficient disk space
- Try again with
--no-check-certificateif SSL issues occur
6. Multiple subtitle languages
- By default, yt-dlp downloads all available languages
- Can specify with
--sub-langs enfor English only - List available with
--list-subsfirst
Best Practices:
- ✅ Always check what's available before attempting download (
--list-subs) - ✅ Verify success at each step before proceeding to next
- ✅ Ask user before large downloads (audio files, Whisper models)
- ✅ Clean up temporary files after processing
- ✅ Provide clear feedback about what's happening at each stage
- ✅ Handle errors gracefully with helpful messages
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