see-video

Extract frames from a video and inject them as a grid image + XML timestamps into LLM context.

Setup (first time only)

cd \x3Cskill directory>
npm install

Usage

node {baseDir}/scripts/inject.mjs \x3Cvideo_path> [--mode uniform|highlight] [--start N] [--end N]

On success, outputs JSON to stdout:

{
  "gridPath": "/tmp/video_llm-frames.jpg",
  "description": "\x3Cvideo_frames>...\x3C/video_frames>",
  "duration": 1326,
  "frameCount": 28,
  "layout": { "cols": 4, "rows": 7, "cellW": 384, "cellH": 216 },
  "videoWidth": 854,
  "videoHeight": 480,
  "inputSizeMb": 42.3
}

If the video exceeds 10 minutes and uniform mode was used without --start/--end, a hint field is included:

{
  "hint": "Video is 30 minutes long. This is a uniform overview. For better scene coverage re-run with --mode highlight, or use --start/--end to zoom into a specific section."
}

Recommended workflow for long videos:

1. First run with --mode highlight — shows key scene changes across the whole video
2. If the user wants detail on a specific section, re-run with --start N --end N

On error, writes ERROR: \x3Cmessage> + Hint: \x3Cdiagnosis> to stderr and exits 1.

Injection procedure

Step 1 — Run the script (bash tool):

node {baseDir}/scripts/inject.mjs "/path/to/video.mp4"

Step 2 — Parse JSON: Extract gridPath and description.

Step 3 — Inject image (read tool):

read \x3CgridPath>

The read tool injects the jpg as a native multimodal image block into context. After viewing the grid, use the description XML timestamps to reference frames:

"Look at the grid image above. Use the timestamps in the description XML to analyze the video. The number in the top-left of each cell is the frame index."

On error:

• Translate the Hint: message into natural language for the user. Do not paste raw error output.
• If read \x3CgridPath> fails — /tmp/ files are ephemeral. Re-run the script and read immediately.

Options

Diagnostics

Notes

• Frame count and cell size are determined automatically from video duration and aspect ratio
• Grid is ~1500×1500px, cell long side 384–512px
• Timestamps are in the description XML only, not overlaid on the image
• Portrait and landscape videos both supported
• Telegram users: if a video file is not attached to the message, check channels.telegram.mediaMaxMb in the OpenClaw config — the file may have been dropped at the channel level before reaching the agent