Use when the user mentions a video file (.mp4, .mov, .avi, .mkv, .webm), a YouTube URL, asks to watch/analyze/review a video, or references video content in conversation
Installs just this skill. Get the whole plugin for auto-invocation.
⚡ How it fires
How this skill gets triggered: by you, by Claude, or both.
Fires itselfClaude auto-loads it when your prompt matches the work.
You can call itInvoke it directly when you want it.
Slash command/video-perception
👁️ Context preview
The summary Claude sees to decide when to auto-load this skill.
Use when the user mentions a video file (.mp4, .mov, .avi, .mkv, .webm), a YouTube URL, asks to watch/analyze/review a video, or references video content in conversation
📊 Stats
Stars1,031
Forks120
LanguageTypeScript
LicenseMIT
📦 Ships with claude-video-vision
</> SKILL.md
video-perception.SKILL.md
---name: video-perception
description: Use when the user mentions a video file (.mp4, .mov, .avi, .mkv, .webm), a YouTube URL, asks to watch/analyze/review a video, or references video content in conversation
---# Video Perception
You have access to video understanding tools via the claude-video-vision MCP server.
## Available Tools
- `video_analyze` — Analyze video structure with ffmpeg filters (scene changes, silence, motion, etc.). Use this BEFORE extracting frames to plan your strategy.
- `video_watch` — Extract frames + process audio from a video. Supports variable FPS/resolution per segment.
- `video_detail` — Drill into specific segments. Separates extraction from viewing — extract many frames, view few at a time.
- `video_info` — Get video metadata without processing.
- `video_configure` — Change settings (backend, resolution, enable_index, etc.).
- `video_setup` — Check/install dependencies.
## Workflow
**IMPORTANT: You MUST follow these steps in order. Do NOT skip step 2.**
1. Always start with `video_info` to get duration, resolution, and audio presence.
If the user gives a YouTube URL, pass the URL directly as `path`.
The MCP server downloads it with `yt-dlp`, prefers YouTube subtitles/auto-captions
for transcription, and falls back to the configured audio backend only when
captions are missing, empty, or suspiciously incomplete.
2. **REQUIRED for videos > 30s:** Call `video_analyze` BEFORE extracting any frames.
This is NOT optional — it gives you structural data to make smart extraction decisions.
Select filters relevant to the user's question:
| User intent | Filters to select |
|---|---|
| "What happens in this video?" | scene_changes, silence, transcription |
| "Find the scene transitions" | scene_changes, black_intervals |
| "Are there frozen/stuck parts?" | freeze, blur |
| "Is this a talking head or action?" | motion |
| "When does the music start?" | silence, loudness |
| "Analyze the lighting" | exposure |
| "Summarize this lecture" | transcription, scene_changes, silence |
| General / unclear intent | scene_changes, silence, transcription |
Always include `transcription: true` when the video has audio — the transcription
tells you WHERE to look visually.
3. Use the analysis results and transcription to plan your frame extraction strategy:
- Low FPS (0.1-0.5) for static or predictable segments
- Higher FPS (1-3) only around scene changes, motion peaks, or moments
referenced in speech ("look at this", "as you can see", "let me show you")
- Never exceed the minimum FPS needed for the task
- Prefer fewer segments at lower FPS — you can always drill deeper
4. Call `video_watch` to extract frames:
- For **short videos (< 2 minutes):** Use `fps: "auto"` without `view_sample` — short videos need full coverage to avoid missing brief moments. The auto FPS already adapts to duration.
- For **long videos (> 2 minutes):** Use `segments` based on analysis data with variable FPS, and `view_sample` to limit initial frame count. You can always drill deeper with `video_detail`.
5. Use `video_detail` to drill into specific moments:
- Start with 3-5 second windows around points of interest
- Use `view_sample: 3` to preview (first, middle, last frame)
- Then request specific timestamps with `view` if you need more detail
- Expand the window only if the initial view is insufficient
- Treat frame viewing like a binary search — narrow down to what matters
- Never view all extracted frames at once
6. When the user asks follow-up questions about the same video, consult
the manifest already in your context. Do not re-extract frames you
already have at the same resolution. Do not re-request frames you
already have in context.
## Parameter Guide
**fps:** `"auto"` for general overview. Use the video's original fps (from `video_info`) for frame-by-frame detail. Use 5-10 for analyzing specific short moments. Use 0.1-0.5 for long videos.
**resolution:** 256-512 for quick scans. 512-768 for normal analysis. 1024+ when reading on-screen text or fine details.
**segments:** Use when you have analysis data. Each segment can have its own fps and resolution. Overrides global fps/start_time/end_time.
**view_sample:** Returns N evenly spaced frames from the extracted set. Use this to avoid flooding context with too many images.
**skip_audio:** Set to true when you only need visual analysis.
**YouTube URLs:** Pass supported YouTube URLs directly as `path`. Treat
`transcription_source: "youtube_subtitles"` as stronger than
`youtube_auto_captions`; auto-captions can still have recognition errors.
## Working with Results
You receive:
- **Manifest** (when enable_index is on) — index of all cached frames by resolution and timestamp. Use this to avoid redundant requests.
- **Frames** as images — look at them to understand what's happening visually
- **Audio transcription** with timestamps — read the speech content
- **Analysis data** — scene changes, silence intervals, motion levels, etc.
Combine all sources to form a complete understanding. Use analysis + transcription to guide where you look visually. The analysis tells you WHEN things happen; the frames tell you WHAT happens.
