
youtube-processor
Process YouTube videos into summarized Obsidian notes. Use when given a YouTube URL to summarize, extract insights, or turn videos into notes. Triggers on "summarize this video", "process this YouTube", "what's this video about", or any YouTube URL shared for processing.
Process YouTube videos into summarized Obsidian notes. Use when given a YouTube URL to summarize, extract insights, or turn videos into notes. Triggers on "summarize this video", "process this YouTube", "what's this video about", or any YouTube URL shared for processing.
YouTube Processor
What This Does
Takes a YouTube URL, extracts the transcript, and you (Claude) summarize it. Outputs Obsidian-ready markdown. Zero friction: share a link, get actionable notes.
When to Use
- "Summarize this video: [URL]"
- "Turn this YouTube into notes"
- "What's this video about?"
- "Process this for my newsletter"
- Any YouTube URL shared for processing
Location
This skill's tools live at:
/Users/eddale/Documents/GitHub/powerhouse-lab/skills/youtube-processor/tools/
How It Works
Step 1: Python extracts the transcript (no API key needed)
Step 2: You (Claude) summarize using your intelligence + context
Step 3: You write the Obsidian-formatted output
This approach means you can use mission-context, newsletter-coach, and other skills during summarization.
Instructions
Which Method to Use
| Environment | Method |
|---|---|
| Claude Code | Local Python script (Step 1a) |
| Claude.ai / Mac Client | API via WebFetch (Step 1b) |
Step 1a: Extract Transcript (Claude Code)
Run the Python tool to get the transcript:
cd /Users/eddale/Documents/GitHub/powerhouse-lab/skills/youtube-processor/tools && \
python3 get_transcript.py --url "[URL]"
For JSON output (easier to parse):
python3 get_transcript.py --url "[URL]" --json
Step 1b: Extract Transcript (Claude.ai / Mac Client)
Use the API endpoint via WebFetch:
WebFetch: https://youtube-processor-eight.vercel.app/transcript?url=[VIDEO_URL]
The API returns JSON:
{
"success": true,
"video_id": "abc123",
"language": "en",
"transcript": "...",
"char_count": 5000,
"word_count": 850
}
Example prompt for WebFetch:
"Extract the transcript text from the response"
Step 2: Summarize the Transcript
Once you have the transcript, summarize it based on what the user needs:
Quick Summary:
- Headline (1 sentence)
- Key points (3-5 bullets)
- Main takeaway
Detailed Analysis:
- Headline summary
- Key points with context
- Main takeaways
- Action items mentioned
- How this relates to Ed's work (if relevant)
Newsletter Mining:
- Hook ideas for an article
- Core insight/framework
- Story beats for anecdotes
- Takeaways for readers
- Newsletter angle for The Little Blue Report
Step 3: Format for Obsidian
Create markdown with this structure:
---
source: YouTube
video_id: [ID]
url: [URL]
processed: [YYYY-MM-DD HH:MM]
tags: [youtube, video-notes]
mission_areas: [BlackBelt, Powerhouse, Newsletter, Prototyping, Daily workflow, Skill building]
action_verdict: [Act now | Bookmark | Ignore | Research]
---
# [Video Title or Topic]
**Link**: [URL]
**Processed**: [Date]
## Summary
[Your summary here]
## Mission Relevance
**Applies to:** [Tag which mission areas this content is relevant to]
- **BlackBelt** - Coaching program work
- **Powerhouse** - AI Amplified program / members
- **Newsletter** - The Little Blue Report
- **Prototyping** - Building leverage tools
- **Daily workflow** - Personal productivity
- **Skill building** - Improving the system itself
[Brief explanation of why it matters to each tagged area]
## Action Verdict
**Verdict:** [Act now | Bookmark | Ignore | Research]
[Specific recommendation and next step if applicable]
- **Act now** - Worth immediate attention. Next step: [specific action]
- **Bookmark** - Know it exists, use when relevant
- **Ignore** - Not applicable to Ed's mission
- **Research** - Needs more info before deciding
## Learning Triggers
[Any questions or opportunities this surfaces for Ed's system]
- **Questions raised:** [What this makes you wonder about]
- **Skill opportunities:** [Could this improve an existing skill?]
- **Newsletter angles:** [Story hook or insight for The Little Blue Report]
- **Follow-up research:** [Would a research-swarm help clarify something?]
---
## Full Transcript
[The transcript]
---
_Generated by youtube-processor skill_
Step 4: Save (Optional)
Save to Ed's Zettelkasten:
/Users/eddale/Documents/COPYobsidian/MAGI/Zettelkasten/
Filename format: YT - [Topic] - YYYY-MM-DD.md
Error Handling
| Error | Meaning | What to Do |
|---|---|---|
| "Transcripts disabled" | Creator turned off captions | Video can't be processed |
| "No transcript found" | No English captions available | Try a different video |
| "Video unavailable" | Private, deleted, or age-restricted | Check the URL |
Examples
Example 1: Quick Summary
User says:
Summarize this: https://www.youtube.com/watch?v=VIDEO_ID
You do:
- Run:
python3 get_transcript.py --url "https://www.youtube.com/watch?v=VIDEO_ID" - Read the transcript output
- Provide a summary to the user
Example 2: Save to Obsidian
User says:
Turn this video into notes and save it: [URL]
You do:
- Extract transcript with the Python tool
- Summarize the content
- Format as Obsidian markdown
- Use Write tool to save to Zettelkasten
- Confirm: "Saved to [filepath]"
Example 3: Newsletter Mining
User says:
I want to write about this video for the newsletter: [URL]
You do:
- Extract transcript
- Analyze for newsletter angles (hooks, insights, story beats)
- Present the angles
- Offer to hand off to newsletter-coach skill
Integration Points
- newsletter-coach: After extracting video insights, hand off for article development
- mission-context: Use Ed's voice and style when summarizing
- task-clarity-scanner: Action items from videos can be added to daily notes
Dependencies
The Python tool requires:
youtube-transcript-api
Install if needed:
pip3 install youtube-transcript-api
Version History
| Version | Date | Changes |
|---|---|---|
| 1.1 | 2026-01-03 | Added Vercel API for Claude.ai/Mac client support |
| 1.0 | 2026-01-02 | Initial build with transcript extraction |
Notes & Learnings
- youtube-transcript-api works without API keys
- Most videos have auto-generated English captions
- Claude doing the summarization is better than Python calling the API (can use context)
- ~3-5 second transcript extraction for typical videos
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