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Watching videos

Skill oxbshw/watch-skill/skills/watching-videos

The user shared a video URL, a YouTube/TikTok/stream link, a local video file, a screen recording, a meeting recording, or a playlist/folder of videos — "watch this", "summarize this video", "what's in this recording". Use this to actually watch the video — download, extract frames, OCR, transcribe, and index it — instead of guessing from the title or asking the user to describe it.From its SKILL.md

Install
npx -y skills add oxbshw/watch-skill --skill watching-videos

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.4 KB, as published. Nobody here has run it

Watching videos

You don't have a video input; this skill gives you one. Anything a user hands you — a YouTube link, a TikTok, a lecture, a meeting recording, a screen capture, an .mp4 on disk — goes through the same pipeline: frames (scene-aware, deduplicated), OCR, transcript (captions first, local Whisper offline fallback), all persisted into one index.

Before watching: check the index

watch-skill list

If the video was already analyzed — this session or any earlier one — do NOT watch it again. Ask it directly (see the asking-with-evidence skill):

watch-skill ask <video_id> "<question>"

One video

watch-skill watch "<url-or-path>" [--start T --end T] [--max-frames N] [--transcript-only]
  • Works on any yt-dlp-supported site (1800+), direct media URLs, HLS/DASH manifests (--duration 60 bounds live streams), and local files.
  • Video over ~10 minutes and the user cares about one part → use --start/--end for dense sampling of that window.
  • User only needs what was said → --transcript-only (fastest, often no video download at all).

The report prints Indexed: <video_id>, frames with t=MM:SS timestamps, OCR text, and the transcript. Read every frame path listed — in a single message, parallel Read calls — then answer from frames + OCR

  • transcript, citing timestamps.

Many videos (playlist, channel, folder)

watch-skill batch "<playlist-url-or-folder>" [--limit N]

Everything lands in the same index; one broken video never stops the rest. Afterwards a single watch-skill search "<phrase>" spans the whole batch.

First run on a machine

If any command fails with a dependency error, run watch-skill doctor once — it installs missing ffmpeg/yt-dlp itself. No API key is required for any of this; transcription is local by default and the video file never leaves the machine.

Keep looking

Skills are one crate of 627,801. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.