Videocut Clip Oral

Community

zrt-ai-lab

videocut-clip-oral

口播视频转录和口误识别。生成审查稿和删除任务清单。触发词：剪口播、处理视频、识别口误

Overview

Publisher	zrt-ai-lab
Repository	`opencode-skills`
Skill name	`videocut-clip-oral`
Stars	293
Forks	75
Bundled files	2
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.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by zrt-ai-lab on GitHub. Read the source before you install it.

Installation

Install the Videocut Clip Oral 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-clip-oral
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-clip-oral .claude/skills/videocut-clip-oral

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

Use it in TypingMind

Enable Videocut Clip Oral 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 Clip Oral 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 Clip Oral 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.

剪口播

转录 + 口误/静音识别 → 生成审查稿

快速使用


用户: 帮我剪这个口播视频
用户: 处理一下这个视频

流程


1. FunASR 30s 分段转录（字符级时间戳）
    ↓
2. 识别口误（逐句检查）
    ↓
3. 识别微口误（VAD 检测短片段）
    ↓
4. 识别语气词（嗯/哎/诶 等）
    ↓
5. 识别静音（≥1s）
    ↓
6. 生成审查稿（时间戳驱动）
    ↓
7. 输出删除任务 TodoList
    ↓
【等待用户确认】→ 用户确认后，执行 /videocut:剪辑

⚠️ 为什么用 30s 分段

FunASR 长视频有时间戳漂移，30s 分段可避免。

进度 TodoList

启动时创建：


- [ ] 读取「转录最佳实践」→ 转录视频
- [ ] 读取「口误识别方法论」→ 识别口误
- [ ] VAD 检测微口误（短片段 < 0.5s）
- [ ] 扫描语气词（嗯/哎/诶 等）
- [ ] 识别静音（≥1s）
- [ ] 生成审查稿
- [ ] 输出删除任务清单

⚠️ 必须先读方法论再执行

阶段	先读	再执行
转录	`tips/转录最佳实践.md`	调用ASR
识别口误	`tips/口误识别方法论.md`	逐句分析

核心：时间戳驱动

删除任务格式

每项必须标注精确时间戳 (start-end)：


口误（N处）：
- [ ] 1. `(start-end)` 删"错误文本" → 保留"正确文本"

语气词（N处）：
- [ ] 1. `(前字end-后字start)` 删"嗯" 上下文: XX【嗯】YY

静音（N处）：
- [ ] 1. `(start-end)` 静音Xs

口误类型

类型	示例	删除策略
重复型	`拉满新拉满`	只删差异（"新"）
替换型	`AI就是AI就会`	删第一个完整版本（"AI就是"）
卡顿型	`听会会`	删第一个重复字

⚠️ 关键规则

时间戳驱动：审查稿直接标注时间戳，剪辑不再搜索文本
逐token分析：对于"删前面保后面"的口误，必须逐token查时间戳
检查时间跨度：如果口误时间跨度 > 2秒，必有静音，需拆分

输出文件


01-xxx-v1_transcript.json  # 转录结果（含时间戳）
01-xxx-v1_审查稿.md        # 口误审查稿

展示要求

生成审查稿后，必须展示给用户：

写入文件 01-xxx-v1_审查稿.md
读取并展示内容
等待用户确认要删除哪些项目

方法论

详见 tips/口误识别方法论.md：

口误识别方法（逐句检查）
"删前面保后面"的精确处理
FunASR 时间戳对齐规则

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Videocut Clip Oral AI skill do?

口播视频转录和口误识别。生成审查稿和删除任务清单。触发词：剪口播、处理视频、识别口误

Why use Videocut Clip Oral on TypingMind?

Because you install it once and use it with any model. Videocut Clip Oral 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 Clip Oral in TypingMind?

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

Which AI models can use Videocut Clip Oral?

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 Clip Oral?

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

Is the Videocut Clip Oral 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

剪口播

快速使用

流程

⚠️ 为什么用 30s 分段

进度 TodoList

⚠️ 必须先读方法论再执行

核心：时间戳驱动

删除任务格式

口误类型

⚠️ 关键规则

输出文件

展示要求

方法论

Bundled files

Frequently asked questions

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