사용 방법
- 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
- 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
- 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/zc277584121/marketing-skills --skill raw-video-processing시작 전 확인
- 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
- 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.
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 0.5This detects and cuts out silent portions (including keyboard sounds), producing <input>_nosilence.mp4.
Always pass these parameters (tuned for screen recordings with keyboard noise):
-t="-20dB"— aggressive threshold that filters out keyboard typing and background noise (use=syntax to avoid argparse treating negative values as flags)-d 0.5— remove short silences too (0.5s minimum)-p 0.2— seconds of breathing room kept around speech boundaries (default, usually no need to pass)
The script prints a detailed summary: number of silent segments found, total silence removed, and all kept segments with timestamps. Review this output to confirm the result looks reasonable.
Step 2: Speed Up the Video
uv run --python 3.12 /path/to/skills/raw-video-processing/scripts/speed_video.py <input>_nosilence.mp4This applies a speed multiplier to the silence-removed video, producing <input>_nosilence_1.2x.mp4.
Default parameters:
--speed 1.2— 1.2x playback speed (a subtle boost that doesn't feel rushed)
Script Options
remove_silence.py
| Flag | Default | Description |
|---|---|---|
-o, --output | <input>_nosilence.mp4 | Custom output path |
-t, --threshold | -30dB | Silence threshold in dB (higher = more aggressive). Always use `-20dB` for screencasts — pass as -t="-20dB" to avoid argparse issues with negative values |
-d, --duration | 0.8 | Minimum silence duration in seconds to remove. Use `0.5` for screencasts |
-p, --padding | 0.2 | Padding kept around non-silent segments |
--dry-run | off | Only print detected segments, don't export |
speed_video.py
| Flag | Default | Description |
|---|---|---|
-o, --output | <input>_<speed>x.mp4 | Custom output path |
-s, --speed | 1.2 | Playback speed multiplier |
Custom Scenarios
- Only remove silence — run just Step 1.
- Only speed up — run just Step 2 directly on the input file.
- Conservative cleanup — use
-t="-30dB" -d 0.8if the default is cutting too much speech. - Extra aggressive cleanup — use
-t="-15dB" -d 0.3and--speed 1.5for maximum compression. - Preview before committing — use
--dry-runon remove_silence.py to see what would be cut without creating a file. - Custom output name — use
-oon either script to control the output path.
Important Notes
- Always run removesilence **before** speedvideo. Silence detection works on the original audio; speeding up first would alter the audio characteristics and make silence detection less accurate.
- For long videos (>30 min), the silence removal step may take a few minutes as it processes each segment individually.
- Both scripts preserve video quality — removesilence uses stream copy (no re-encoding), while speedvideo re-encodes with FFmpeg defaults.
