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raw-video-processing原始视频处理

Agent Skill

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。它适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:raw-video-processing(原始视频处理)
来源仓库:https://github.com/zc277584121/marketing-skills
仓库路径:skills/raw-video-processing
安装命令:
npx skills add https://github.com/zc277584121/marketing-skills --skill raw-video-processing
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/zc277584121/marketing-skills --skill raw-video-processing

简介

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。

  • 适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。
  • 使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。
  • 安装方式:通过 GitHub 仓库安装,命令为 npx skills add https://github.com/zc277584121/marketing-skills --skill raw-video-processing。
  • 适用宿主:Codex、Claude、Cursor、Gemini CLI。

SKILL.md

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

FlagDefaultDescription
-o, --output<input>_nosilence.mp4Custom output path
-t, --threshold-30dBSilence threshold in dB (higher = more aggressive). Always use -20dB for screencasts — pass as -t="-20dB" to avoid argparse issues with negative values
-d, --duration0.8Minimum silence duration in seconds to remove. Use 0.5 for screencasts
-p, --padding0.2Padding kept around non-silent segments
--dry-runoffOnly print detected segments, don't export

speed_video.py

FlagDefaultDescription
-o, --output<input>_<speed>x.mp4Custom output path
-s, --speed1.2Playback 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 0.8 if the default is cutting too much speech.
  • Extra aggressive cleanup — use -t="-15dB" -d 0.3 and --speed 1.5 for maximum compression.
  • Preview before committing — use --dry-run on remove_silence.py to see what would be cut without creating a file.
  • Custom output name — use -o on 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.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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