Agent skill

Learning Notes Automation

by chubbyguan in chubbyguan/chubbyskills

学习笔记自动化:视频/播客转录 → 知识点提取 → 闪卡生成 → 知识图谱更新。触发词:学习笔记、闪卡、Anki、知识提取、视频学习

MITAuto-check passedMedia & Creative

Install Learning Notes Automation

skills CLI
$ npx skills add chubbyguan/chubbyskills --skill learning-notes-automation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install chubbyguan/chubbyskills learning-notes-automation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/chubbyguan/chubbyskills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/learning-notes-automation .claude/skills/learning-notes-automation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
learning-notes-automation
GitHub stars
1.2k
Token cost
~898 tokens
SKILL.md length
119 words
Files
2 (incl. scripts)
Skills in repo
14
Repo updated
First seen
Licence
MIT

At a glance

学习笔记自动化:视频/播客转录 → 知识点提取 → 闪卡生成 → 知识图谱更新。触发词:学习笔记、闪卡、Anki、知识提取、视频学习

  • Works in 7 steps: 内容转录 → + 3: 知识点提取 + 闪卡生成(一步到位) → 闪卡生成 → …
  • Tasks that involve Study guides and flashcards
  • SKILL.md covers 核心价值, 输入源, 工作流程 and 输出格式, plus 3 more sections
  • Runs Python scripts from its folder; calls python3; reaches youtube.com and bilibili.com; needs DEEPSEEK_API_KEY

What it does

Learning Notes Automation is an agent skill from chubbyguan/chubbyskills. 学习笔记自动化:视频/播客转录 → 知识点提取 → 闪卡生成 → 知识图谱更新。触发词:学习笔记、闪卡、Anki、知识提取、视频学习

Its SKILL.md is about 900 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/make_notes.py`).

It sits in Media & Creative, covering Study guides and flashcards and Transcription. It works with YouTube, Bilibili, Douyin and WeChat. The repository describes itself as: 把中文全渠道内容(抖音 / B站 / 小红书 / 公众号 / X / 播客)采集进个人知识库的 14 个 AI Skill:图文存图、视频转文字稿、字幕优先免 GPU、RSS/YouTube 订阅调度与每日情报简报,附带知识库 MCP server。| Ingest Chinese content into your personal knowledge… The licence is MIT.

When your agent uses it

  • Tasks that involve Study guides and flashcards
  • Tasks that involve Transcription

Example prompts

  • “/learning-notes-automation”

Requirements

  • Python 3
  • A credential in DEEPSEEK_API_KEY

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. 内容转录
  2. + 3: 知识点提取 + 闪卡生成(一步到位)
  3. 闪卡生成
  4. 知识图谱更新
  5. Anki 闪卡文件
  6. 学习笔记 Markdown
  7. 知识库条目

What it can do on your machine

Read from SKILL.md and the folder at commit 1b759b1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • youtube.com
    • bilibili.com
    • xiaoyuzhoufm.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • DEEPSEEK_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Learning Notes Automation loads about 898 tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 119 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
When it runs · the whole SKILL.md, loaded when a task matches
~898

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from chubbyguan/chubbyskills at commit 1b759b1, republished under its MIT licence (© chubbyguan). 119 words, ~898 tokens.

Download SKILL.mdSave it as .claude/skills/learning-notes-automation/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
learning-notes-automation
description
学习笔记自动化:视频/播客转录 → 知识点提取 → 闪卡生成 → 知识图谱更新。触发词:学习笔记、闪卡、Anki、知识提取、视频学习
metadata.triggers
["学习笔记", "闪卡", "Anki", "知识提取", "视频学习", "提取知识点"]
metadata.version
1.0
metadata.created
2026-06-02
metadata.tags
["learning", "notes", "anki", "knowledge-extraction"]

学习笔记自动化

核心价值

被动学习 → 主动记忆:看视频 ≠ 学会,生成闪卡 = 记住

输入源

输入类型工具输出格式
YouTube 视频youtube-transcribe转录文本
B站视频bilibili-transcribe转录文本
播客podcast-transcribe转录文本
抖音douyin-transcribe转录文本
公众号文章wechat-article-ingestMarkdown

工作流程

Phase 1: 内容转录

复用本仓库的转录 skill(相对路径,按需替换为你的安装位置):

bash
# YouTube(自动翻译)
python3 ../youtube-transcribe/scripts/transcribe.py "https://youtube.com/watch?v=xxx" -o ./

# B站
python3 ../bilibili-transcribe/scripts/transcribe.py "https://bilibili.com/video/xxx" ./

# 播客
python3 ../podcast-transcribe/scripts/transcribe.py "https://xiaoyuzhoufm.com/episode/xxx" ./

输出是一份转录 Markdown,作为 Phase 2 的输入。

Phase 2 + 3: 知识点提取 + 闪卡生成(一步到位)

把转录稿交给 make_notes.py,自动提取知识点并生成 Anki 兼容闪卡:

bash
export DEEPSEEK_API_KEY=***
python3 scripts/make_notes.py 转录稿.md --output ./notes --max-cards 20
# 产出:<标题>-学习笔记.md(核心要点+闪卡+关联知识) 和 <标题>-闪卡.csv(直接导入 Anki)

脚本用 DeepSeek 输出结构化 JSON,再渲染成下面约定的笔记与闪卡格式。 下面是各维度的设计说明,供理解和手动微调时参考。

提取维度:

  1. 核心概念(必须掌握)

    • 定义
    • 原理
    • 应用场景
  2. 关键事实(需要记忆)

    • 数据
    • 时间线
    • 人物/公司
  3. 方法论(可以复用)

    • 步骤
    • 框架
    • 最佳实践
  4. 金句/洞察(值得引用)

    • 精辟总结
    • 独特观点
Phase 3: 闪卡生成

闪卡格式(Anki 兼容):

markdown
## 闪卡类型

### 1. 概念卡(Cloze Deletion)
Q: {{c1::Transformer}} 架构的核心机制是 {{c2::自注意力(Self-Attention)}}
A: Transformer, 自注意力(Self-Attention)

### 2. 问答卡(Basic)
Q: 什么是 RAG?
A: Retrieval-Augmented Generation,检索增强生成。通过检索外部知识库来增强 LLM 的回答能力,解决幻觉问题。

### 3. 对比卡(Comparison)
Q: Fine-tuning vs RAG 的区别?
A: 
| 维度 | Fine-tuning | RAG |
|------|-------------|-----|
| 成本 | 高(需要训练) | 低(只检索) |
| 更新 | 需要重新训练 | 实时更新 |
| 适用 | 特定任务 | 知识问答 |

### 4. 步骤卡(Process)
Q: 如何构建一个 RAG 系统?
A: 
1. 文档分块(Chunking)
2. 向量化(Embedding)
3. 存入向量数据库
4. 检索相关片段
5. 拼接 Prompt
6. LLM 生成回答
Phase 4: 知识图谱更新

实体提取:

  • 人物(Who)
  • 概念(What)
  • 工具/产品(Tool)
  • 方法论(How)
  • 时间(When)

关系映射:

  • 发明了:人物 → 概念/工具
  • 属于:概念 → 领域
  • 替代了:新工具 → 旧工具
  • 依赖于:概念 → 概念

输出到知识库:

markdown
---
title: [概念名]
type: knowledge-card
platform: learning
tags: [学习, AI, ...]
source: [[视频/播客链接]]
created: YYYY-MM-DD
---

# [概念名]

## 定义
一句话定义

## 核心要点
1. ...
2. ...
3. ...

## 关联概念
- [[概念A]]:关系说明
- [[概念B]]:关系说明

## 应用场景
- 场景1:...
- 场景2:...

## 闪卡
(Anki 格式的闪卡内容)

输出格式

1. Anki 闪卡文件
csv
# 符号分隔格式,可直接导入 Anki
"问题","答案","标签"
"什么是 Transformer?","一种基于自注意力机制的深度学习架构,广泛用于 NLP 任务","AI,深度学习"
2. 学习笔记 Markdown
markdown
# [视频标题] - 学习笔记

**来源**:[链接]
**日期**:YYYY-MM-DD
**时长**:XX 分钟
**领域**:AI / 半导体 / ...

---

## 📝 核心要点

### 要点 1:[标题]
- 摘要:...
- 重要性:⭐⭐⭐⭐⭐

### 要点 2:[标题]
- 摘要:...
- 重要性:⭐⭐⭐⭐

---

## 🃏 闪卡(XX 张)

### 概念卡
1. Q: ... A: ...
2. Q: ... A: ...

### 问答卡
1. Q: ... A: ...

---

## 🔗 关联知识

- [[概念A]]:...
- [[概念B]]:...

---

## 💡 个人思考

(基于内容的个人见解和应用想法)
3. 知识库条目

存入:wiki/📖 行业研究/[领域]/[概念名].md

Cron 配置(可选)

yaml
# 每周日整理本周学习内容
schedule: "0 20 * * 0"
prompt: "整理本周的所有学习笔记,生成周学习报告"

使用示例

用户:帮我把这个视频做成学习笔记
https://youtube.com/watch?v=xxx

Agent:
1. 转录视频
2. 提取 15 个知识点
3. 生成 20 张闪卡
4. 更新知识图谱
5. 输出 Anki 文件 + Markdown 笔记

反模式

  • ❌ 不要只提取不消化,必须有个人思考
  • ❌ 不要生成太多闪卡,质量 > 数量(单视频 15-30 张)
  • ❌ 不要忽略知识关联,孤立的知识容易遗忘
  • ✅ 闪卡必须可独立理解(不依赖上下文)
  • ✅ 每张闪卡只有一个知识点(原子性)
  • ✅ 优先生成「为什么」和「怎么做」的卡,而非「是什么」

© chubbyguan, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (scripts) in learning-notes-automation of chubbyguan/chubbyskills.

  • SKILL.md
  • scripts/make_notes.py

Open the folder on GitHubat commit 1b759b1

Compare with similar skills

Learning Notes Automation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Learning Notes Automation compared with similar skills
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Video SummaryLeoYeAI/openclaw-master-skills2.2k—~4.2kAutomated safety check: PassMIT
Video Podcast MakerAgents365-ai/video-podcast-maker1.7k—~4.9kAutomated safety check: PassMIT
Video To Subtitle Summaryimlewc/video-to-subtitle-summary-skill214—~4.6kAutomated safety check: NotesMIT
Media To TranscriptbozhouDev/video-skills-toolkit150—~1.8kAutomated safety check: NotesMIT

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Questions about Learning Notes Automation

What does Learning Notes Automation do?

学习笔记自动化:视频/播客转录 → 知识点提取 → 闪卡生成 → 知识图谱更新。触发词:学习笔记、闪卡、Anki、知识提取、视频学习. Learning Notes Automation is an agent skill from chubbyguan/chubbyskills.

When should I use Learning Notes Automation?

Learning Notes Automation fits situations like: tasks that involve Study guides and flashcards; tasks that involve Transcription.

How do I install Learning Notes Automation in Claude Code?

Run `npx skills add chubbyguan/chubbyskills --skill learning-notes-automation -a claude-code`. Or copy the skill folder (learning-notes-automation in chubbyguan/chubbyskills) into .claude/skills/learning-notes-automation in your project. Claude Code loads it when a task matches its description.

How do I install Learning Notes Automation in Codex?

Run `npx skills add chubbyguan/chubbyskills --skill learning-notes-automation -a codex`. Or copy the skill folder (learning-notes-automation in chubbyguan/chubbyskills) into .agents/skills/learning-notes-automation in your project. Codex loads it when a task matches its description.

Can I use Learning Notes Automation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add chubbyguan/chubbyskills --skill learning-notes-automation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/learning-notes-automation, .gemini/skills/learning-notes-automation, .github/skills/learning-notes-automation and .opencode/skills/learning-notes-automation in your project.

What does Learning Notes Automation need to run?

Going by SKILL.md and its folder, Learning Notes Automation needs Python for the scripts in its folder, the command-line tools its instructions call (python3) and credentials named DEEPSEEK_API_KEY. Our summary lists: Python 3; A credential in DEEPSEEK_API_KEY.

Does Learning Notes Automation access the network?

SKILL.md names 3 domains. In commands or code: youtube.com, bilibili.com and xiaoyuzhoufm.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Learning Notes Automation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Learning Notes Automation use?

Learning Notes Automation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Learning Notes Automation use?

About 898 tokens (SKILL.md is roughly 3.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Learning Notes Automation?

Skills that share tags, products or a category with Learning Notes Automation: Video Downloader (kangarooking/kangarooking-skills, 661 stars), Video Summary (LeoYeAI/openclaw-master-skills, 2.2k stars), Video Podcast Maker (Agents365-ai/video-podcast-maker, 1.7k stars) and Video To Subtitle Summary (imlewc/video-to-subtitle-summary-skill, 214 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Learning Notes Automation?

chubbyguan (a GitHub user) maintains it in chubbyguan/chubbyskills, which has 1,205 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 8, 2026.

Source: chubbyguan/chubbyskills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.