Automating YouTube Learning
I want to automate learning from YouTube videos inside OpenClaw.
Goal:
Given a YouTube URL, I want to automatically generate:
- Metadata (title, channel, publish date, duration)
- Full transcript (if available)
- Key ideas summary
- Actionable takeaways
- UX / product insights extraction
- Screenshots for visual evidence
My question is architectural:
Should this be implemented as:
1) A dedicated OpenClaw skill (youtube-study)?
2) A generic browser automation flow without a skill?
3) A hybrid approach (skill for logic + browser adapter abstraction)?
4) Something else entirely?
Constraints:
- Must work reliably.
- Must not depend on playback.
- Must handle transcript unavailable cases.
- Must always output a StudyPack artifact (never silent fail).
- Should work locally (WSL or VM).
- Should scale later (multiple videos).
What is the correct architectural approach for long-term reliability?
Goal:
Given a YouTube URL, I want to automatically generate:
- Metadata (title, channel, publish date, duration)
- Full transcript (if available)
- Key ideas summary
- Actionable takeaways
- UX / product insights extraction
- Screenshots for visual evidence
My question is architectural:
Should this be implemented as:
1) A dedicated OpenClaw skill (youtube-study)?
2) A generic browser automation flow without a skill?
3) A hybrid approach (skill for logic + browser adapter abstraction)?
4) Something else entirely?
Constraints:
- Must work reliably.
- Must not depend on playback.
- Must handle transcript unavailable cases.
- Must always output a StudyPack artifact (never silent fail).
- Should work locally (WSL or VM).
- Should scale later (multiple videos).
What is the correct architectural approach for long-term reliability?
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