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YogirajAYogirajA/Claude-Skills/watch/SKILL.md

watch

Skill1 starsChanged 56 days agoMITView on GitHub

Watch and analyze any YouTube video by fetching its transcript, then summarizing it, extracting key takeaways, pulling quotes, building timestamped chapter notes, listing action items, or answering a specific question about it. Use this whenever the user shares a YouTube link (youtube.com or youtu.be) and wants to know what's in it, says "watch this", "summarize this video", "give me the key points / notes / takeaways from this talk", "what does this video say about X", "tldr this YouTube video", or wants to skip watching something and get the content fast. Trigger even when the user just pastes a YouTube URL with a brief instruction, and even if they never say the word "watch".

  • Installs packages

48 other projects use a version of this.

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Used with

Projects with it also use decision-map, map and 6 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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The file

We split this skill into the rules it gives an agent

5 rules. 0 are common, 4 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 44 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Prefer the most robust method available.

    line 26
  2. Distinctive:

    If neither tool is installed, tell the user once, plainly:

    line 48
  3. Distinctive:

    Don't loop on install errors.

    line 53
  4. Very specific:

    Keep timestamps where useful.

    line 66
  5. Distinctive:

    If you could not get a transcript, say so and stop, then ask the user to paste it.

    line 92

“Common” is measured: kept by at least 6 in 10 of the 44 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Watch (YouTube-first video analysis)

Point Claude at a YouTube video and get its content back as structured notes, without watching it yourself. The skill fetches the transcript, then analyzes it for whatever you need: a summary, timestamped chapters, key takeaways, action items, quotes, or answers to a specific question.

There is no magic here. The model cannot "see" a video; everything depends on getting a text transcript first. So the skill's real job is to (1) reliably pull the transcript, (2) clean it, (3) analyze it well, and (4) be honest when the transcript can't be obtained instead of inventing content.

Step 1 - Identify the video

Extract the video ID and note the URL form: youtube.com/watch?v=ID, youtu.be/ID, /shorts/ID, or /live/ID. If the user pasted a non-YouTube link, say this skill is YouTube-first and offer the paste-the-transcript fallback (Step 4).

Step 2 - Fetch the transcript

Prefer the most robust method available. Check what is installed and degrade gracefully.

Method A - yt-dlp (most robust; also gets metadata). Handles auto-generated captions when manual ones are absent.

yt-dlp --skip-download --write-auto-subs --write-subs --sub-langs "en.*" --sub-format vtt --convert-subs srt -o "%(id)s.%(ext)s" "<URL>"
yt-dlp --skip-download --print "%(title)s :: %(uploader)s :: %(duration_string)s :: %(upload_date)s" "<URL>"

Then read the resulting .srt / .vtt. Auto-captions repeat rolling lines, so dedupe: each line of speech should appear once, keeping its earliest timestamp.

Method B - youtube-transcript-api (cleanest timestamped text).

python -c "import json,sys; from youtube_transcript_api import YouTubeTranscriptApi as Y; print(json.dumps(Y.get_transcript(sys.argv[1])))" <VIDEO_ID>

Returns [{text, start, duration}, ...], already clean. Good when it works; falls over if transcripts are disabled for the video.

If neither tool is installed, tell the user once, plainly:

I need a transcript tool. Install either with pip install yt-dlp or pip install youtube-transcript-api, or paste the transcript here and I'll work from that.

Don't loop on install errors. Surface the problem and offer the paste fallback.

Step 3 - Analyze for the user's intent

With no specific ask, default to the Structured summary template below. Otherwise match the request:

  • Deep notes - section-by-section detail, faithful to the speaker's logic.
  • Action items - concrete, do-able steps the video recommends.
  • Quotes - the most striking verbatim lines, with timestamps.
  • Chapters - a timestamped table of contents.
  • Answer a question - answer only from the transcript; if it isn't covered, say so.

Keep timestamps where useful. Deep-link form: https://youtu.be/<id>?t=<seconds>.

Structured summary (default)

# <Title> - <Uploader> (<duration>)
**TL;DR:** <2-3 sentence gist>

## Key takeaways
- <takeaway> [mm:ss]
- ...

## Section notes
### <Section title> [mm:ss]
<what's covered>

## Worth quoting
> "<quote>" [mm:ss]

Offer to save the output to a markdown file if it's long or the user wants to keep it. In a repo with a knowledgebase/ wiki, save the capture under knowledgebase/raw/ and offer to hand it to write-wiki for ingest.

Step 4 - Honesty guardrail

If you could not get a transcript, say so and stop, then ask the user to paste it. Never summarize a video you don't have the transcript for, never guess at content from the title, and don't present a thumbnail or description as if it were the video. A wrong summary is worse than an honest "I couldn't fetch it."

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