Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
zrt-ai-lab avatar

Videocut Install

  • 166 installs
  • 263 repo stars
  • Updated July 22, 2026
  • zrt-ai-lab/opencode-skills

Helps with ai & agent building tasks during AI-assisted development.

About

videocut-install is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • videocut-install
  • AI & Agent Building
  • AI-coding skill

Videocut Install by the numbers

  • 166 all-time installs (skills.sh)
  • Ranked #3,133 of 16,556 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 3, 2026 (Skillselion catalog sync)
npx skills add https://github.com/zrt-ai-lab/opencode-skills --skill videocut-install

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs166
repo stars263
Last updatedJuly 22, 2026
Repositoryzrt-ai-lab/opencode-skills

What it does

Helps with ai & agent building tasks during AI-assisted development.

Files

SKILL.mdMarkdownGitHub ↗

<!-- input: 无 output: 环境就绪 pos: 前置 skill,首次使用前运行

架构守护者:一旦我被修改,请同步更新: 1. ../README.md 的 Skill 清单 2. /CLAUDE.md 路由表 -->

安装

首次使用前的环境准备

快速使用

用户: 安装环境
用户: 初始化
用户: 下载模型

依赖清单

依赖用途安装命令
funasr口误识别pip install funasr
modelscope模型下载pip install modelscope
openai-whisper字幕生成pip install openai-whisper
ffmpeg视频剪辑brew install ffmpeg

模型清单

FunASR 模型(口误识别用)

首次运行自动下载到 ~/.cache/modelscope/

模型大小用途
paraformer-zh953MB语音识别(带时间戳)
punc_ct1.1GB标点预测
fsmn-vad4MB语音活动检测
小计~2GB

Whisper 模型(字幕生成用)

首次运行自动下载到 ~/.cache/whisper/

模型大小用途
large-v32.9GB字幕转录(质量最好)

总计

5GB 模型文件

安装流程

1. 安装 Python 依赖
       ↓
2. 安装 FFmpeg
       ↓
3. 下载 FunASR 模型(口误识别)
       ↓
4. 下载 Whisper 模型(字幕生成)
       ↓
5. 验证环境

执行步骤

1. 安装 Python 依赖

pip install funasr modelscope openai-whisper

2. 安装 FFmpeg

# macOS
brew install ffmpeg

# Ubuntu
sudo apt install ffmpeg

# 验证
ffmpeg -version

3. 下载 FunASR 模型(约2GB)

from funasr import AutoModel

model = AutoModel(
    model="paraformer-zh",
    vad_model="fsmn-vad",
    punc_model="ct-punc",
)
print("FunASR 模型下载完成")

4. 下载 Whisper 模型(约3GB)

import whisper

model = whisper.load_model("large-v3")
print("Whisper 模型下载完成")

5. 验证环境

from funasr import AutoModel

model = AutoModel(
    model="paraformer-zh",
    vad_model="fsmn-vad",
    punc_model="ct-punc",
    disable_update=True
)

# 测试转录(用任意音频/视频)
result = model.generate(input="test.mp4")
print("文本:", result[0]['text'][:50])
print("时间戳数量:", len(result[0]['timestamp']))
print("✅ 环境就绪")

常见问题

Q1: 模型下载慢

解决:使用国内镜像或手动下载

Q2: ffmpeg 命令找不到

解决:确认已安装并添加到 PATH

which ffmpeg  # 应该输出路径

Q3: funasr 导入报错

解决:检查 Python 版本(需要 3.8+)

python3 --version

Related skills

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.