raw-video-processing▌
zc277584121/marketing-skills · updated Apr 8, 2026
Post-process raw screen recordings to improve pacing — remove silent segments, then speed up the result.
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.
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★69 reviews- ★★★★★Benjamin White· Dec 28, 2024
Solid pick for teams standardizing on skills: raw-video-processing is focused, and the summary matches what you get after install.
- ★★★★★Kofi Malhotra· Dec 28, 2024
We added raw-video-processing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Isabella Wang· Dec 28, 2024
I recommend raw-video-processing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Chen Kapoor· Dec 24, 2024
Keeps context tight: raw-video-processing is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Neel Yang· Dec 4, 2024
raw-video-processing reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Chen Lopez· Nov 23, 2024
raw-video-processing reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Kofi Flores· Nov 19, 2024
Registry listing for raw-video-processing matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Camila Torres· Nov 19, 2024
raw-video-processing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Charlotte Jain· Nov 19, 2024
raw-video-processing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Ava Flores· Nov 19, 2024
Useful defaults in raw-video-processing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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