oxbshw/watch-skill

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".

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/oxbshw/watch-skill --skill watching-videos

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

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

bash
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):

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

One video

bash
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)

bash
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.

관련 작업

같은 저장소의 Skills

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모든 Skills
oxbshw
커뮤니티

asking-with-evidence

The user asks a question about a video that was already watched or indexed — "what did they say about X", "what error code appears", "what happens at 2:30", "does the video show Y". Use this to answer from the persistent index with timestamped evidence and a confidence score instead of re-watching or guessing.

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2
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configuring-vision

The user wants to connect an LLM or vision provider, already has an API key, asks "can I use OpenAI/Anthropic/Gemini/OpenRouter", wants local Ollama, or needs different cheap and strong models. Use this to configure provider-neutral visual understanding without tying Watch Skill to one agent or model vendor.

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extracting-structure

The user wants structure pulled out of a watched video — "make chapters for this video", "where does the bug appear in this recording", "turn this screen recording into a bug report", "how strong is my intro/hook". Use this for deterministic extraction from the index — chapters with timestamps, a fileable bug report with the exact frame, or a scored hook analysis.

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learning-from-mistakes

The user corrected an answer about a video — "no, it actually says X", "that's the wrong timestamp", "you misread the error code" — or asks why a video answer was wrong. Use this to record the correction as a lesson so future answers on similar questions improve, and to show what the system has learned and saved.

설치 수
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GitHub Stars
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