This skill helps download transcripts (subtitles/captions) from YouTube videos using yt-dlp.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionyoutube-transcriptExecute the skills CLI command in your project's root directory to begin installation:
Fetches youtube-transcript from michalparkola/tapestry-skills-for-claude-code and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate youtube-transcript. Access via /youtube-transcript in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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This skill helps download transcripts (subtitles/captions) from YouTube videos using yt-dlp.
Activate this skill when the user:
--write-sub) - highest quality--write-auto-sub) - usually availableIMPORTANT: Always check if yt-dlp is installed first:
which yt-dlp || command -v yt-dlp
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
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:
Try this first - highest quality, human-created:
yt-dlp --write-sub --skip-download --output "OUTPUT_NAME" "YOUTUBE_URL"
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).
ONLY use this if both manual and auto-generated subtitles are unavailable.
# 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.
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
yt-dlp -x --audio-format mp3 --output "audio_%(id)s.%(ext)s" "YOUTUBE_URL"
# 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)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
yt-dlp --print "%(title)s" "YOUTUBE_URL"
Use this to create meaningful filenames based on the video title. Clean the title for filesystem compatibility:
/ with -$(yt-dlp --print "%(title)s" "URL" | tr '/' '-' | tr ':' '-')YouTube's auto-generated VTT files contain duplicate lines because captions are shown progressively with overlapping timestamps. Always deduplicate when converting to plain text while preserving the original speaking order.
python3 -c "
import sys, re
seen = set()
with open('transcript.en.vtt', 'r') as f:
for line in f:
line = line.strip()
if line and not line.startswith('WEBVTT') and not line.startswith('Kind:') and not line.startswith('Language:') and '-->' not in line:
clean = re.sub('<[^>]*>', '', line)
clean = clean.replace('&', '&').replace('>', '>').replace('<', '<')
if clean and clean not in seen:
print(clean)
seen.add(clean)
" > transcript.txt
# Get video title
VIDEO_TITLE=$(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"
.vtt): Includes timestamps and formatting, good for video players.txt): Just the text content, good for reading or analysis{output_name}.{language_code}.vtt (e.g., transcript.en.vtt)--write-sub instead for manual subtitlesVIDEO_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."
✓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
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share 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
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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4.8★★★★★57 reviews- MMeera Torres★★★★★Dec 28, 2024
Useful defaults in youtube-transcript — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- MMei Iyer★★★★★Dec 20, 2024
youtube-transcript reduced setup friction for our internal harness; good balance of opinion and flexibility.
- WWilliam Lopez★★★★★Dec 16, 2024
We added youtube-transcript from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- MMeera Park★★★★★Dec 16, 2024
Useful defaults in youtube-transcript — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- NNeel Khan★★★★★Dec 4, 2024
Keeps context tight: youtube-transcript is the kind of skill you can hand to a new teammate without a long onboarding doc.
- HHenry Abbas★★★★★Dec 4, 2024
youtube-transcript is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- SSakshi Patil★★★★★Nov 23, 2024
Keeps context tight: youtube-transcript is the kind of skill you can hand to a new teammate without a long onboarding doc.
- LLuis Ghosh★★★★★Nov 23, 2024
Useful defaults in youtube-transcript — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- AAisha Harris★★★★★Nov 19, 2024
youtube-transcript is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- MMei Srinivasan★★★★★Nov 11, 2024
Registry listing for youtube-transcript matched our evaluation — installs cleanly and behaves as described in the markdown.
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