colingpt9/clips-studio/clips-kitty

Claude Code and agent skill by colingpt9/clips-studio

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Turn long videos and streams into short vertical clips with Clips Kitty, running locally on this computer. Use when someone wants clips, Shorts, Reels or TikToks made from a YouTube, Twitch or Kick link or a video file, or wants to read back or export clips Clips Kitty already made.

Install

npx vskill@latest install colingpt9/clips-studio/clips-kitty

SKILL.md

Clips Kitty

Clips Kitty finds the moments worth posting in a long video, crops them to 9:16 with the speaker kept in frame, burns in captions and writes titles. Everything runs on the user's own machine: no account, no upload, no API key.

Connecting

The tools come from Clips Kitty's MCP server, which talks to the engine on 127.0.0.1:8765.

bash
claude mcp add clips-kitty -- python main.py mcp # from a source checkout

In an installed build the engine's binary is api.exe, inside the app's resources\backend folder, so the command is api.exe mcp.

Clips Kitty has to be running, either the app itself or python main.py serve. If a tool reports the engine is not answering, say so and stop: starting it is the user's call, not something to work around.

How to work

  1. Queue with queue_video (a link) or queue_local_file (a file on disk).
  2. Check back with job_status. Processing a two-hour stream takes tens of minutes on

a good machine. Never sit in a polling loop: report the job id, and check when the user next asks or after a long wait.

  1. Read the results with list_clips, which gives each clip's id, score and title.
  2. Export with export_clip when the user names a folder.

Things that will otherwise catch you out

  • A queued job is not guaranteed. queue_video returns "Not queued" when that video

was processed before, because redoing it costs an hour and duplicates its clips. Offer list_clips on the existing video, or force if they really meant it.

  • An unknown video id looks like a video with no clips, because the API returns an

empty list either way. Check list_videos before concluding a video produced nothing.

  • A paused queue looks like a broken app. queue_status reports it. Check it before

telling anyone nothing is happening.

  • Scores are the model's ranking, 0-100, not a promise. The user picks what to post.
  • Gaming uses its own framing. Set gaming=true for its webcam/game layout and

existing layout detector. Omit gaming_layout for automatic detection, or pass the user's selected layout and boxes. An installed game-specific detector is chosen with pipeline={"id":"publisher/name"}; discovery and permissions remain in the app.

What it will not do

There is no cloud tier, no upload of the user's footage anywhere, and no posting to social platforms except YouTube, which the user switches on themselves with their own Google key. Do not offer those.

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
128
Repository forks
27
7-day trend score
0

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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