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Ra Video Title

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Pluviobyte
ra-video-title

视频标题生成与落盘工作流。Use when the user asks to title a finished or planned video, especially 抖音/小红书视频标题, 视频标题.md, 成片同级目录, 对标标题共性, 两段式标题, 基于视频主题起标题, 洗稿后标题, or replacing generic dbs-xhs-title for video titles. It derives the real video theme first, studies benchmark title patterns when provided, generates 8-12 theme-first two-part candidates, recommends/selects one, and writes 视频标题.md next to the final MP4 when requested.

Overview

PublisherPluviobyte
Repositoryrnskill
Skill namera-video-title
Stars
1.6K
Forks
181
Bundled files
2
Links
  • 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 Pluviobyte on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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/Pluviobyte/rnskill.git /tmp/rnskill
mkdir -p .claude/skills
cp -r /tmp/rnskill/skills/ra-video-title .claude/skills/ra-video-title
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ra Video Title 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 Ra Video Title 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 Ra Video Title 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.

视频标题 Skill

核心原则

先定主题,再起标题。视频标题必须服务这条视频的核心命题,不能只套“AI 工具”“翻车”“原因找到了”这类泛钩子。

默认替代 dbs-xhs-title 处理视频标题。dbs-xhs-title 仍可用于通用小红书图文标题或纯公式浏览;视频成片、视频洗稿、对标标题、两段式抖音标题一律走本 Skill。

两段式流程中的位置

在「洗稿(Claude)→ 待制作队列 → 制作(Codex)」两段式流程里,本 skill 在洗稿阶段运行,输入是刚洗好的最终脚本(主题最清楚的时刻):

  • 只产出候选:8-12 个两段式候选 + Top 3 推荐理由,写入交接稿「标题候选」一节
  • 不在洗稿阶段定稿:最终标题由用户发布时人工从候选里选
  • 制作端与发布标题无关:不起标题、不应用标题、不生成 视频标题.md

工作流

  1. 锁定视频主题

    • 优先读用户给出的最终脚本、视频制作简报、narration_segments.json、项目说明或成片目录上下文。
    • 输出一句主题判断,格式为:这条视频讲的是:...
    • 标题候选必须能回扣这句主题。
  2. 拆对标标题

    • 如果用户给对标标题,提炼共性:结构、前半句钩子、后半句补充、情绪、专业词、结果承诺。
    • 不复制对标的具体表达,不把别人的账号人设写进标题。
    • 默认重点检查“两段式”:前半句抛场景/冲突/问题,后半句给结果/解释/悬念。
  3. 生成候选

    • 生成 8-12 个候选。
    • 默认用两段式,常见连接符:
    • 每条候选都要同时满足:
      • 命中视频主题,不是泛 AI 标题;
      • 前半句有钩子;
      • 后半句补充方向或悬念;
      • 口语化,适合短视频平台;
      • 不把视频答案全说完;
      • 资讯类主题(新论文/新产品/新事件):前半句直接给事实主体(谁+发了什么),不用比喻/拟人当首要钩子,比喻最多出现在后半句补充里。
  4. 筛选与推荐

    • 给出 Top 3,并说明一句理由。
    • 如果用户要求“你选定”“直接写入”“替我选”,选 1 个最终标题。
    • 如果用户明确说“我来选”,只给候选并等待编号。
  5. 写入文件

    • 两段式洗稿流程中:写入目标只有交接稿「标题候选」一节(8-12 候选 + Top 3 推荐),不写 frontmatter、不生成 视频标题.md,最终由用户人工选定。
    • 其他场景当用户要求写入时,在最终 MP4 所在的 成片/ 目录新建或更新 视频标题.md
    • 文件第一行只写最终标题。
    • 只有在用户要求保留或候选对后续有价值时,才追加 ## 候选标题 小节。
    • 使用 apply_patch 编辑 视频标题.md;不要改动 MP4 或其他成片文件。

标题评分

每个候选用下面 5 项心里过一遍:

  • 主题贴合:离视频主题越近越好;能套到任何 AI 视频上的标题扣分。
  • 两段式张力:前后两段要有递进,不是简单重复。
  • 点击理由:用户为什么要点开?是怕落后、怕踩坑、想省事、想变强,还是想看争议?
  • 信息差:标题要留缺口,不要把结论说满。
  • 口语感:像抖音标题,不像论文标题或课程标题。

禁用项

  • 不要在没读主题的情况下直接起标题。
  • 资讯类视频不要用比喻/拟人起手的标题(如「跟AI说别想金门大桥,它满脑子都是金门大桥」);事实主体(如「Anthropic 新论文」「Anthropic 造出读心工具」)必须出现在前半句。
  • 不要只围绕工具名起标题,例如只写 Claude Code 翻车原因,除非视频主题就是该工具故障。
  • 不要让标题偏离视频,比如主题是 Model × Harness,标题却变成普通 AI 工作流提效
  • 不要为了追热点滥用“接管”“破甲”“零报错”;这些词只有贴合主题时才用。
  • 不要默认把候选标题全部写入文件;文件优先保持干净。

参考

两段式标题模式和本工作区沉淀的样例见 references/two-part-video-title.md。需要生成候选或解释对标共性时读取它。

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 Ra Video Title AI skill do?

视频标题生成与落盘工作流。Use when the user asks to title a finished or planned video, especially 抖音/小红书视频标题, 视频标题.md, 成片同级目录, 对标标题共性, 两段式标题, 基于视频主题起标题, 洗稿后标题, or replacing generic dbs-xhs-title for video titles. It derives the real video theme first, studies benchmark title patterns when provided, generates 8-12 theme-first two-part candidates, recommends/selects one, and writes 视频标题.md next to the final MP4 when requested.

Why use Ra Video Title on TypingMind?

Because you install it once and use it with any model. Ra Video Title 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 Ra Video Title in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Pluviobyte/rnskill/tree/main/skills/ra-video-title. 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 Ra Video Title?

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 Ra Video Title?

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

Is the Ra Video Title AI skill free?

It is published on GitHub by Pluviobyte. 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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