Raw Video Processing
This is for cleaning up screen recordings when you've got long pauses and keyboard noise cluttering your video. It runs two FFmpeg scripts in sequence: first strips out silent segments using an aggressive threshold tuned for typing sounds, then speeds up what's left by 1.2x. The silence detection is pretty configurable if the defaults cut too much, and there's a dry run mode so you can preview before committing. It's opinionated about the workflow order, which makes sense since speeding up first would mess with the audio characteristics. The main limitation is that long videos take a few minutes to process since each segment gets handled individually.
- skills.sh installs
- 3.9K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add zc277584121/marketing-skills --skill raw-video-processing --agent claude-codeInstalls into .claude/skills of the current project.
Files
Skill: Raw Video Processing
Post-process raw screen recordings to improve pacing — remove silent segments, then speed up the result.
Prerequisite: FFmpeg and uv must be installed.
When to Use
The user has recorded a screencast and wants to clean it up before publishing. Typical issues in raw recordings:
- Long pauses / dead air while thinking or waiting for loading
- Keyboard typing sounds and other low-level background noise that should be treated as silence
- Overall pacing feels slow and could benefit from a slight speed boost
Default Workflow
When the user provides a raw video file, run both scripts in sequence by default:
Step 1: Remove Silent Segments
uv run --python 3.12 /path/to/skills/raw-video-processing/scripts/remove_silence.py <input.mp4> -t="-20dB" -d 0.5
This detects and cuts out silent portions (including keyboard sounds), producing <input>_nosilence.mp4.
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- Repository
- github.com/zc277584121/marketing-skills
- Categories
- Python, Marketing & SEO, CLI & Terminal, Generative Media, Video & Audio Editing
- First seen
- May 16, 2026
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