watching-videos

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.