colingpt9/clips-studio/clips-kitty
Claude Code and agent skill by colingpt9/clips-studio
- community
Checking that the SKILL.md file is still in the repository.
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-kittySKILL.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.
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
- Queue with
queue_video(a link) orqueue_local_file(a file on disk). - 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.
- Read the results with
list_clips, which gives each clip's id, score and title. - Export with
export_clipwhen the user names a folder.
Things that will otherwise catch you out
- A queued job is not guaranteed.
queue_videoreturns "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_statusreports 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=truefor 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
- SKILL.md in the repositoryCheckingskills/clips-kitty/SKILL.md
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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