get_frame_burst
Extract multiple frames evenly distributed across a video time range for motion and vibration analysis, such as detecting shaking or flickering.
Instructions
Extract multiple frames evenly distributed across a time range.
Designed for motion and vibration analysis where scene-change detection fails because the "scene" doesn't change — only the position/state of objects does.
Example: get_frame_burst(url, "0:15", "0:17", 10) → 10 frames in 2 seconds
AI sees the object in different positions across frames → understands the vibration
Works for: shaking, flickering, animations, fast scrolling, loading spinners
Supports: Loom (loom.com/share/...), YouTube/Vimeo/TikTok/Instagram/X/Twitch/Dailymotion/Facebook (requires yt-dlp), direct video URLs (.mp4, .webm, .mov), and local video files (absolute path or file:// URI).
Args:
url: Video source (URL or local path)
from: Start timestamp (e.g., "0:15")
to: End timestamp (e.g., "0:17")
count: Number of frames (default: 5, max: 30)
Returns: N images evenly distributed between the from and to timestamps.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | End timestamp (e.g., "0:17") | |
| url | Yes | Video source: Loom share link, platform video URL (YouTube, Vimeo, TikTok, Instagram, X, Twitch, Dailymotion, Facebook), direct .mp4/.webm/.mov URL, or absolute path to a local video file | |
| from | Yes | Start timestamp (e.g., "0:15") | |
| count | No | Number of frames to extract (default: 5) | |
| returnBase64 | No | Return frames as base64 inline instead of file paths |