Video context

Skill vusallyv/video-context-plugin/skills/video-context

Extract scene-change frames + audio transcript from any video so Claude can "watch" it. Use when user pastes a video URL or local video file path and asks to analyze, watch, summarize, or debug from a video. Triggers on .mp4/.mov/.webm/.mkv paths, video URLs (Loom, YouTube, raw mp4, private attachments), or phrases like "analyze this video", "watch this", "see the recording", "video shows the bug".From its SKILL.md

Install

npx -y skills add vusallyv/video-context-plugin --skill video-context

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

One thing to look at

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SKILL.md

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video-context

Claude reads images, not videos. This skill turns any video into scene-change frames + audio transcript so Claude can reason about it.

Standalone — works on any source: local file, public URL, or private URL with auth.

When to use

User shares a video and wants Claude to understand its content. Examples:

"Analyze this video: <url>"
"What does this recording show? /path/to/file.mp4"
"The bug is in this Loom: https://loom.com/share/..."
Bug ticket (Jira/Asana/GitHub/Linear) contains a video attachment.

How to use

${CLAUDE_PLUGIN_ROOT}/skills/video-context/extract.sh <url-or-path>

Script auto-resolves the source:

Source	How it's fetched
Local file path	Used directly.
Public URL (Loom, YouTube, Vimeo, public CDN, raw mp4)	`yt-dlp` first, falls back to `curl`.
Private URL needing auth	`curl` with `VIDEO_AUTH_HEADER` env var.

Private URL with auth

Set VIDEO_AUTH_HEADER to whatever the host needs:

# Bearer token
VIDEO_AUTH_HEADER="Authorization: Bearer $TOKEN" \
  ${CLAUDE_PLUGIN_ROOT}/skills/video-context/extract.sh "https://host.example/asset/123"

# Basic auth (e.g. Atlassian email + API token)
VIDEO_AUTH_HEADER="Authorization: Basic $(echo -n "$EMAIL:$TOKEN" | base64)" \
  ${CLAUDE_PLUGIN_ROOT}/skills/video-context/extract.sh "https://your-org.atlassian.net/rest/api/3/attachment/content/12345"

If user shares a private URL without a token, ask for one — or tell them to download the video and paste the local path.

After it runs

Script prints WORKDIR, frame paths, transcript path. Then:

Read each frame — Claude sees JPEGs natively.
Read the transcript at $WORKDIR/transcript.txt.
Combine frames + transcript to answer the user.

Tuning (env vars)

Var	Default	What
`SCENE_THRESHOLD`	`0.4`	Lower = more frames. Screen recordings often need `0.2`.
`MAX_FRAMES`	`20`	Hard cap; trimmed evenly across timeline.
`FRAME_WIDTH`	`1280`	Downscale to save tokens.
`WHISPER_MODEL`	`/opt/homebrew/share/whisper-cpp/ggml-base.en.bin`	whisper-cpp model path.

Requirements

ffmpeg (required)
yt-dlp (recommended — handles Loom/YouTube/Vimeo)
whisper-cpp + model (optional — for audio transcript)

Run /video-context:setup once for full install on macOS or Linux (apt/dnf/pacman/zypper; builds whisper-cpp from source). On macOS, extract.sh also auto-installs missing binaries via brew on first run; the whisper model (~150MB) is only fetched by setup.

Windows: install manually.