carrot1445

Deadspace Remover For TikTok Instagram Reels — Communication skill for Claude Code

Communication community

Claude Code skill: cut the dead space out of talking-head videos — between sentences only, tight to speech, never clips a word.

How to install Deadspace Remover For TikTok Instagram Reels

This entry records only its repository, not the path inside it, so there is no exact command to give. Open carrot1445/Deadspace-Remover-for-Tiktok-instagram-reels and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Deadspace Remover For TikTok Instagram Reels does

Claude Code skill: cut the dead space out of talking-head videos — between sentences only, tight to speech, never clips a word. Local ffmpeg + faster-whisper.

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README

tight-cut: a Claude Code skill for cutting dead space

Drop your raw talking-head videos into Claude Code and say "edit these". You get back the same videos with the dead air between sentences removed.

  • Tight: each clip starts the instant you start talking and ends the instant you stop, with zero gap between sentences.
  • Safe: it never cuts inside a sentence and never clips a word. Soft word endings like the "-ting" in "marketing" are kept, while breaths, mouth clicks and room noise are cut.
  • Looks right: it checks the frames so a clip doesn't end on you reaching to stop the recording.
  • Local and free: ffmpeg plus faster-whisper. No API keys, and nothing is uploaded.
  • Organized: output goes to finished videos//.

Made for phone selfie videos (TikTok, Reels, Shorts, UGC), where you record several takes back to back and just want the pauses gone.

Install

git clone https://github.com/carrot1445/tight-cut-skill
cp -r tight-cut-skill/tight-cut ~/.claude/skills/        # personal skill, every project
# or: cp -r tight-cut-skill/tight-cut /.claude/skills/

pip install -r ~/.claude/skills/tight-cut/requirements.txt

You also need `ffmpeg` on your PATH (`brew install ffmpeg` / `apt install ffmpeg` / `winget install ffmpeg`). The first run downloads the whisper `small` model (~460 MB, cached after that).

Use

In Claude Code:

edit these: ~/Downloads/clip1.MP4 ~/Downloads/clip2.MP4

or `/tight-cut ~/Downloads/clip1.MP4`. Claude runs the cutter, checks that no words were lost, reads the frame sheet for start/stop-recording reaches, and tells you where the files are.

Or run the script yourself without Claude:

python ~/.claude/skills/tight-cut/scripts/tight_cut.py clip1.MP4 clip2.MP4 --verify
clip1.MP4: 76.06s -> 57.19s, removed 18.87s, 14 clips
   -> finished videos/2026-10-14/clip1_tight.mp4
   edge sheet -> finished video