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jev-skip

Browser extension that reads the caption track and paints a sponsor-probability overlay on the YouTube seek bar before the intro ends, with no crowd database. The author reports catching 77% of SponsorBlock's sponsor seconds across 23 videos at $0.0008 per video.

View on GitHub →

Hands-on review

Finds YouTube sponsor segments on videos nobody has labelled, by judging transcript windows. Honest about what it catches and what it costs you.

Good for

  • Small channels and new uploads that crowd-sourced labels never reach
  • A browser extension that states its false-skip rate up front
  • Seeing a transcript-window classifier written plainly

Watch out for

  • Video transcripts go to a third party, per video you watch
  • It skips on a probability, so it will occasionally cut real content
  • Three stars; a browser extension you install from source

Tested Sep 20, 2026 at 6837e3e0f1a4 · Node 24 in Docker, offline; 52 tests across 7 files

How we reviewed this: we ran its 52 tests in Docker on Node 24, offline, and read the request builder. We did not load the extension into a browser, and we made no Jev calls.

What it does

jev-skip, by valentynkit, does what SponsorBlock does — except SponsorBlock needs someone to have watched and labelled the video first. This judges the transcript itself, so it works on a video uploaded minutes ago.

The README leads with its own measured numbers: the share of crowd-marked sponsor seconds it catches, its false-skip rate per hour, cost per video, and how quickly slices appear on the bar. Those are the author’s figures on their sample of videos, and stating a false skip rate next to the catch rate is the honest way to present this — the failure mode people care about is cutting real content, not missing an ad.

52 tests pass offline.

What to know

The transcript of every video you watch with it enabled goes to a third party. That’s the mechanism, not a slip, but it’s a different privacy profile from a crowd-sourced database that only ever sees a video id.

And skipping is probabilistic: the threshold trades missed sponsors against cut content, and you own that dial.

Verdict

A neat answer to the cold-start problem in crowd labelling, and unusually candid about its own error rate. If you watch a lot of small channels, it fills the gap the crowd never gets to.

For the same author’s other small tools, see the projects list.

See how it compares with other tools in Best Jev tools, tested hands-on.

Review updated Sep 20, 2026. Numbers quoted from the project are its author's own; we don't publish our own measurements of Jev.

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