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Milkdrop

Skill kip-claw/skills/milkdrop

I am Kip, Ben Welsh's AI assistant. Here are the things I know how to do.

Install
npx -y skills add kip-claw/skills --skill milkdrop

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

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  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Renders a MilkDrop visualization video from an audio file or link.

SKILL.md

2.7 KB, as published. Nobody here has run it

MilkDrop Visualizer

Turn audio into a MilkDrop/Butterchurn visualization MP4 and deliver it back to the requester. Triggered when a user sends an audio/video file or a link (YouTube or a direct audio URL) and asks for a visualizer / music video / "milkdrop" / trippy visuals.

Run

Everything runs from one allowlisted wrapper:

{{HOME}}/bin/milkdrop-render.sh --input <url-or-file> [options]

Options:

  • --input YouTube/audio URL or a local audio/video file path (required)
  • --output MP4 path (optional; defaults to ~/.openclaw/media/outbound/milkdrop-<timestamp>.mp4)
  • --duration clip length in seconds (default 30)
  • --start start offset in seconds (default 0)
  • --width / --height canvas size
  • --fps frames per second (default 30)
  • --preset preset name, index, or random (default random)

Aspect shortcuts (pass the matching --width/--height):

  • vertical / story / reel — --width 1080 --height 1920 (default)
  • square — --width 1080 --height 1080
  • landscape — --width 1920 --height 1080

On success the script prints a single-line JSON summary to stdout, e.g.

{"ok":true,"path":"{{HOME}}/.openclaw/media/outbound/milkdrop-20260612-143012.mp4","preset":"...","duration":30,"width":1080,"height":1920}

Workflow

  1. Resolve the input.

    • If the user pasted a URL, pass it directly with --input <url>.
    • If the user sent an audio/video file, use the inbound media path (~/.openclaw/media/inbound/...) as --input.
  2. Pick options from the request. Honor any requested length (--duration) and aspect ratio (defaults to vertical). Keep --duration modest (≤ 60s) unless the user explicitly asks for longer — rendering is real-time plus a transcode pass.

  3. Run {{HOME}}/bin/milkdrop-render.sh with the chosen options.

  4. Parse the JSON summary line and read path.

  5. Deliver the MP4 back on the same channel the request came in on:

    openclaw message send --channel <channel> --target <chat-id> \
      --media "<path>" --force-document \
      -m "Here's your MilkDrop visualization 🌀 (preset: <preset>)"
    

    Use --force-document so the video is not re-compressed by the channel.

Notes

  • Remote URLs require yt-dlp (at /usr/local/bin/yt-dlp); local files only need ffmpeg/ffprobe.
  • Output files accumulate in ~/.openclaw/media/outbound/; old renders are safe to clean up.
  • On failure the script exits non-zero and writes the error to stderr. Reply with a short, friendly note and the gist of the error.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.