Best use case
videocut:安装 is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
环境准备。安装依赖、下载模型。触发词：安装、环境准备、初始化
Teams using videocut:安装 should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/videocut/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How videocut:安装 Compares
| Feature / Agent | videocut:安装 | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
环境准备。安装依赖、下载模型。触发词：安装、环境准备、初始化
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
<!--
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（本地模式）
## 快速使用
```
用户: 安装环境
用户: 初始化
```
### 依赖清单
| 依赖 | 用途 | 安装命令 |
|------|------|----------|
| Python 3.8+ | 运行 FunASR | `brew install python` |
| funasr | 语音识别 | `pip install funasr` |
| modelscope | 模型下载 | `pip install modelscope` |
| FFmpeg | 视频处理 | `brew install ffmpeg` |
| Node.js 18+ | 运行转录模块 | `brew install node` |
### 模型清单
首次运行自动下载到 `~/.cache/modelscope/`：
| 模型 | 大小 | 用途 |
|------|------|------|
| paraformer-zh | 953MB | 语音识别（带时间戳） |
| punc_ct | 1.1GB | 标点预测 |
| fsmn-vad | 4MB | 语音活动检测 |
| **小计** | **~2GB** | |
### 安装步骤
#### 1. 安装系统依赖
```bash
# macOS
brew install python node ffmpeg
# Ubuntu
sudo apt install python3 python3-pip nodejs ffmpeg
```
#### 2. 安装 Python 依赖
```bash
pip install funasr modelscope
```
#### 3. 下载模型（约2GB）
```bash
cd /path/to/videocut-skills/安装/scripts
# 自动下载所有模型
python test_funasr_local.py --download
```
#### 4. 验证环境
```bash
cd /path/to/videocut-skills/安装/scripts
# 快速验证（检查依赖）
python test_funasr_local.py
# 综合验证（加载完整模型）
python test_funasr_local.py --verify
```
成功输出：
```
🎉 本地模式完全就绪！可以使用以下命令转录：
python 剪口播/scripts/transcribe_local.py video.mp4
```
---
## 完整安装流程
```
1. 安装系统依赖（Python、Node.js、FFmpeg）
↓
2. 安装 Python 依赖（funasr、modelscope）
↓
3. 下载模型（约2GB）
↓
4. 验证环境
↓
5. 完成 ✅
```
---
## 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
```bash
which ffmpeg # 应该输出路径
```
### Q3: Node.js 版本太低
**解决**：需要 Node.js 18+
```bash
node --version # 需要 v18.x 或更高
```
### Q4: pip 和 python 版本不一致
**解决**：确保 pip 和 python 指向同一个版本
```bash
# 检查版本
python --version
pip --version
# 如果不一致，在 ~/.zshrc 添加 alias
alias python=python3.11
alias pip=pip3.11
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