Videocut Install

Community

zrt-ai-lab

videocut-install

环境准备。安装依赖、下载模型、验证环境。触发词：安装、环境准备、初始化

Overview

Publisher	zrt-ai-lab
Repository	`opencode-skills`
Skill name	`videocut-install`
Stars	293
Forks	75
Bundled files	Instructions only
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by zrt-ai-lab on GitHub. Read the source before you install it.

Installation

Install the Videocut Install AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/zrt-ai-lab/opencode-skills/tree/main/videocut-install
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/zrt-ai-lab/opencode-skills.git /tmp/opencode-skills
mkdir -p .claude/skills
cp -r /tmp/opencode-skills/videocut-install .claude/skills/videocut-install

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Videocut Install in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Videocut Install on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Videocut Install is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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-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

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-v3	2.9GB	字幕转录（质量最好）

总计

约 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

bash
pip install funasr modelscope openai-whisper

2. 安装 FFmpeg

bash
# macOS
brew install ffmpeg

# Ubuntu
sudo apt install ffmpeg

# 验证
ffmpeg -version

3. 下载 FunASR 模型（约2GB）

python
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）

python
import whisper

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

5. 验证环境

python
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

bash
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+）

bash
python3 --version

Frequently asked questions

What does the Videocut Install AI skill do?

环境准备。安装依赖、下载模型、验证环境。触发词：安装、环境准备、初始化

Why use Videocut Install on TypingMind?

Because you install it once and use it with any model. Videocut Install is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Videocut Install in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zrt-ai-lab/opencode-skills/tree/main/videocut-install. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Videocut Install?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Videocut Install?

As many as you like. As long as a model supports skills, you can use Videocut Install with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Videocut Install AI skill free?

It is published on GitHub by zrt-ai-lab. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

安装

快速使用

依赖清单

模型清单

FunASR 模型（口误识别用）

Whisper 模型（字幕生成用）

总计

安装流程

执行步骤

1. 安装 Python 依赖

2. 安装 FFmpeg

3. 下载 FunASR 模型（约2GB）

4. 下载 Whisper 模型（约3GB）

5. 验证环境

常见问题

Q1: 模型下载慢

Q2: ffmpeg 命令找不到

Q3: funasr 导入报错

Frequently asked questions

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