raw-video-processing
Post-process raw screen recordings by removing silent segments and applying speed adjustments. Uses FFmpeg-based Python scripts to optimize video pacing automatically.
How do I install this agent skill?
npx skills add https://github.com/zc277584121/marketing-skills --skill raw-video-processingIs this agent skill safe to install?
- Gen Agent Trust Hubpass
This skill provides automated video processing capabilities by wrapping FFmpeg commands in Python scripts. It allows users to remove silent segments from recordings and adjust playback speed. The implementation follows standard practices for command execution.
- Socketpass
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- Snykpass
Risk: LOW · No issues
- Runlayerpass
1/3 files flagged
- ZeroLeakspass
Score: 93/100 · 2 sections analyzed
What does this agent skill do?
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.
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.mp4
This 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 remove_silence before speed_video. 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 — remove_silence uses stream copy (no re-encoding), while speed_video re-encodes with FFmpeg defaults.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/zc277584121/marketing-skills/raw-video-processing">View raw-video-processing on skillZs</a>