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utillayerutillayer/youtube-agent-skill/skills/yt-edit/SKILL.md

yt-edit

Skill10 starsChanged 28 days agoMITView on GitHub

Turn the transcript of a raw recording into a cut list - silences, filler and false starts, each with timecodes. Use for "edit this", "cut the dead air", "tighten this up", "I rambled", or any request to shorten footage from its transcript.

5 other projects use a version of this, 5 of them edited.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 5 edited versions we read keep these.

  • 0

    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. Very specific:

    No transcript yet? whisper, faster-whisper, or YouTube's own captions on an unlisted upload all work.

    line 23

“Common” is measured: kept by at least 6 in 10 of the 5 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

yt-edit

A cut list from a timestamped transcript. It tells you what to cut; your editor does the cutting.

python3 ${CLAUDE_SKILL_DIR}/deadair.py transcript.srt               # srt, vtt or whisper json
python3 ${CLAUDE_SKILL_DIR}/deadair.py transcript.srt --floor 0.35 --json

The tools live in this skill's folder. ${CLAUDE_SKILL_DIR} is that folder in Claude Code; anywhere it does not expand (claude.ai, Codex), use the folder this SKILL.md was loaded from.

No transcript yet? whisper, faster-whisper, or YouTube's own captions on an unlisted upload all work. YouTube's auto-caption .vtt goes in as it comes: word timings, rolling repeats and [Music]-style tags are cleaned on load. To fetch it from a link:

yt-dlp --skip-download --write-auto-subs --sub-langs en --sub-format vtt -o transcript "<video url>"

That writes transcript.en.vtt. Swap en for the video's language. Auto-captions carry no punctuation; a whisper transcript does, and gives cleaner sentence edges. Never guess timings.

What it finds

  • DEAD: gaps longer than the floor, trimmed from the middle so both sides keep a breath. Cutting tight against speech is what makes a tightened take sound breathless.
  • FILLER: cues that are nothing but filler - English ("um", "so yeah", "basically"), Spanish ("bueno", "o sea"), Hindi ("matlab", "accha", "मतलब") and Nepali ("ani", "khai", "अनि"). Other languages get DEAD and REPEAT only; say so.
  • REPEAT: a sentence started again. The abandoned attempt is the one cut, usually the shorter, and it is found even with an "um" between the two tries.

What it does not do

It never touches the media file and has no view on your B-roll. The percentage it reports is of speech: if the video has a long silent demo, the runtime it predicts is wrong. Check the list against the footage before trusting the final length.

Before you hand it over

This skill drafts; you publish. End with the copy-ready block and one question: post it as is, or another pass?

Download now (ZIP)

Does it work?

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What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

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