Timestamped Video Summary logo

Timestamped Video Summary

Community
cnfjlhj
timestamped-video-summary

Generate a detailed, professional video content summary from timestamped subtitles/transcripts (e.g., lines starting with 00:00 / 1:23:45). Enforce strict per-segment structure (timestamp range + bold segment title + 2-paragraph body: first-person creator summary + expert 【导师评注】 critique with uncertainty handling). Use when the user provides time-coded subtitles and asks for a规范化纪要/内容纪要/逐段总结, and optionally wants a clean PDF export (do NOT include the full raw transcript in the PDF unless explicitly requested).

Overview

Publishercnfjlhj
Repositoryai-collab-playbook
Skill nametimestamped-video-summary
Stars
455
Forks
44
Bundled files
3
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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by cnfjlhj on GitHub. Read the source before you install it.

Installation

Install the Timestamped Video Summary 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.
    https://github.com/cnfjlhj/ai-collab-playbook/tree/main/skills/full/timestamped-video-summary
  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/cnfjlhj/ai-collab-playbook.git /tmp/ai-collab-playbook
mkdir -p .claude/skills
cp -r /tmp/ai-collab-playbook/skills/full/timestamped-video-summary .claude/skills/timestamped-video-summary
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Timestamped Video Summary 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 Timestamped Video Summary 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 Timestamped Video Summary 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.

Timestamped Video Summary

Overview

将“带时间戳的字幕/转录”整理为严格结构的视频内容纪要,并在用户要求“落盘/导出/PDF”时,把纪要渲染成排版清晰的中文 PDF(默认不附带原始逐行字幕材料)。

Workflow Decision Tree

  1. 只要文字纪要
  • 直接按“输出规范”生成 Markdown 纪要即可(无需落盘)。
  1. 需要落盘为 PDF(排版清楚)
  • 先生成符合规范的 Markdown 纪要 → 写入 *.md → 运行 scripts/validate_summary_md.py 校验 → 运行 scripts/render_pdf.py 生成 *.pdf。

Input Assumptions

  • 输入是带时间戳的字幕/转录文本,典型形态为:
    • 00:00 / 00:02 / 01:23 / 1:23:45 这样的时间戳行
    • 其下一行/多行是字幕内容
  • 允许字幕存在口误、ASR 错别字、英文大小写/空格 token 等噪声;纪要要“忠实还原 + 专业归纳”,不要凭空补剧情。

Output Spec (Strict)

对字幕的每个逻辑段落,输出必须包含且仅包含以下三部分(按顺序):

  1. 时间戳范围
  • 格式:时间戳范围: [开始时间 - 结束时间]
  1. 段落核心标题
  • 紧跟时间戳范围下一行
  • 必须用 Markdown 加粗:**标题**
  • 标题要“精准概括该段落内容”,避免空泛(如“介绍一下”“继续讲”)。
  1. 内容主体(两层,但不加额外小标题/前缀)
  • 第一段:核心内容总结(必须用博主第一人称:“我/我们”),忠实复述观点、论证、操作;用 加粗突出关键术语/核心结论/数据。
  • 第二段:另起一段,必须以 【导师评注】 开头;以顶尖专家口吻补充概念、指出漏洞/争议;若无法判断真伪,必须明确写出该点**“需要进一步验证”**,并给出具体验证思路/方法。

禁止项(默认规则):

  • 不要把“原始逐行字幕(每行时间戳+原文)”附在纪要或 PDF 后面(除非用户明确要求“把原字幕也附录进去”)。
  • 不要在内容主体里加“核心内容总结:/导师评注:”这类额外标题;导师段只允许前缀 【导师评注】。

Segmentation Heuristics (Practical)

将字幕分成“逻辑段落”时:

  • 以话题切换、板书/投影片章节、例子切换、从原理→实作等自然边界为主
  • 段落不要过碎(否则标题会变得重复、信息密度下降);也不要过大(否则难以检索)
  • 段落时间跨度建议落在 1–5 分钟量级;必要时可更长,但标题必须能覆盖主要内容

Quality Checklist (Before Final)

  • 每段都满足:时间戳范围 + 标题 + 两段正文(第二段以 【导师评注】 开头)
  • 第一段是否全程第一人称(我/我们),且没有混入“导师视角”
  • 关键术语/结论/数据是否用 加粗标出(不过度加粗)
  • 导师评注是否包含:概念补充 + 批判性审视 + 不确定性处理(需要进一步验证 + 验证方法)
  • 未出现“原始逐行字幕全文”

PDF Export (No Raw Transcript Appendix by Default)

落盘流程建议:

  1. 先把最终纪要写入 output.md
  2. 运行校验:python3 scripts/validate_summary_md.py output.md
  3. 生成 PDF:python3 scripts/render_pdf.py --input output.md --outdir .

命名规则(默认不覆盖):

  • 输出文件名默认形如:视频纪要_<主题短名>_<YYYYMMDD_HHMMSS>.pdf
  • 若同名已存在:自动追加 -v2/-v3

Resources

  • scripts/validate_summary_md.py:格式与硬性规范校验
  • scripts/render_pdf.py:把纪要 Markdown 渲染为 PDF(封面+目录+模块化段落;默认不附原字幕)

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 Timestamped Video Summary AI skill do?

Generate a detailed, professional video content summary from timestamped subtitles/transcripts (e.g., lines starting with 00:00 / 1:23:45). Enforce strict per-segment structure (timestamp range + bold segment title + 2-paragraph body: first-person creator summary + expert 【导师评注】 critique with uncertainty handling). Use when the user provides time-coded subtitles and asks for a规范化纪要/内容纪要/逐段总结, and optionally wants a clean PDF export (do NOT include the full raw transcript in the PDF unless explicitly requested).

Why use Timestamped Video Summary on TypingMind?

Because you install it once and use it with any model. Timestamped Video Summary 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 Timestamped Video Summary in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cnfjlhj/ai-collab-playbook/tree/main/skills/full/timestamped-video-summary. 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 Timestamped Video Summary?

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 Timestamped Video Summary?

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

Is the Timestamped Video Summary AI skill free?

It is published on GitHub by cnfjlhj. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇