watching-videos — Claude Code skill: what it does, how to install
Processes local video files and links through scene-aware frame extraction, OCR, and speech transcription. It lets the agent answer questions using verified timestamps.
npx skills add oxbshw/watch-skill --skill watching-videos -a claude-codeWhat watching-videos does
The skill runs video content through a structured indexing pipeline. It extracts keyframes without duplicates, runs OCR on visible text, and transcribes speech using subtitles or local Whisper. All output is stored in a local index, so previously processed videos never need to be re-analyzed.
For longer recordings, the --start and --end flags focus frame sampling on a specific time range. If only the audio matters, the --transcript-only flag skips video processing entirely. The watch-skill batch command indexes entire folders or playlists while isolating errors so one broken video does not stop the run.
No API keys are required because transcription and text extraction run directly on your hardware. If required dependencies like ffmpeg or yt-dlp are missing, running watch-skill doctor installs them automatically.
What it helps with
- extract on-screen text from screen recordings via OCR
- transcribe speech from local video files without external APIs
- query recorded meetings by timestamps and visual evidence
- index multiple video files or playlists in batch mode
Example prompts for the agent
- Watch
meeting.mp4and summarize the key decisions with timestamps. - Find the exact moment in
screencast.mp4where the terminal shows an error. - Transcribe
lecture.mp4using transcript mode without saving frame images.
How to install watching-videos
1Skills CLI (Vercel)
npx skills add oxbshw/watch-skill --skill watching-videos -a claude-code2Manually: put the files in place
~/.claude/skills/watching-videos/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/watching-videos/
1Skills CLI (Vercel)
npx skills add oxbshw/watch-skill --skill watching-videos -a codex2Manually: put the files in place
.agents/skills/watching-videos/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add oxbshw/watch-skill --skill watching-videos -a cursor2Manually: put the files in place
.cursor/skills/watching-videos/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install oxbshw/watch-skill watching-videos2Manually: put the files in place
.github/skills/watching-videos/SKILL.md1Skills CLI (Vercel)
npx skills add oxbshw/watch-skill --skill watching-videos -a gemini-cli2Platform CLI
gemini skills install https://github.com/oxbshw/watch-skill --path skills/watching-videosManually: put the files in place
.devin/skills/watching-videos/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add oxbshw/watch-skill --skill watching-videos -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about watching-videos
How to install watching-videos in Claude Code?
Run npx skills add oxbshw/watch-skill --skill watching-videos -a claude-code. The skill file will be created at ~/.claude/skills/watching-videos/SKILL.md.
What does the watching-videos skill do?
It processes video files or links by extracting scene-aware frames, running OCR on visual text, and generating speech transcripts. Everything is stored in an index so the model can cite exact timestamps.
Does watching-videos require external API keys?
No API keys are required. Speech transcription runs locally with Whisper or extracts existing subtitles, and the video never leaves your machine.
Source text
SKILL.md · MIT
--- name: watching-videos version: "1.4.3" description: 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. license: MIT user-invocable: true allowed-tools: Bash, Read --- # 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.
© oxbshw · MIT · oxbshw/watch-skill