anything-to-notebooklm

🥈Silver

Processes content from WeChat, web pages, YouTube, PDFs, and Markdown into podcasts, PPTs, mind maps, and quizzes for NotebookLM. Ideal for operations teams needing automated content transformation.

755420Updated 2w ago

Intermediate30min to implementautomation

Saves ~180 min per use

Quick InstallView Source

git clone https://github.com/joeseesun/anything-to-notebooklm.git

Works with:

Claude

Overview

About This Skill

Processes content from WeChat, web pages, YouTube, PDFs, and Markdown into podcasts, PPTs, mind maps, and quizzes for NotebookLM. Ideal for operations teams needing automated content transformation.

How to Use

1. **Prepare Your Content:** Gather the source material (PDF, URL, Markdown, or WeChat link) and ensure it’s accessible. For WeChat, use the 'Copy Link' feature or export as text. 2. **Run the Prompt:** Paste the prompt template into your AI tool (e.g., Claude, ChatGPT) and replace [CONTENT_SOURCE], [CONTENT_LINK_OR_FILE_PATH], and any other placeholders. For large PDFs, summarize the key sections first to avoid token limits. 3. **Review and Refine:** Check the output for accuracy. Adjust the podcast script for tone (e.g., conversational vs. formal) and edit the PPT outline to match your branding. Use NotebookLM’s built-in tools to import the mind map and quiz directly. 4. **Integrate into NotebookLM:** Upload the podcast script as a 'Script' document, the PPT outline as a 'Presentation' document, the mind map as a 'Mind Map' document, and the quiz as a 'Quiz' document. Tag them with relevant topics for easy retrieval. 5. **Share and Iterate:** Share the NotebookLM package with your team. Use the quiz to test understanding and the mind map for brainstorming sessions. Gather feedback and refine the content for future use.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/joeseesun/anything-to-notebooklm

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Convert [CONTENT_SOURCE: URL/PDF/Markdown/WeChat] into a structured NotebookLM-ready format. First, extract key insights and actionable takeaways. Then, generate: 1) A 5-10 minute podcast script with timestamps for each segment, 2) A 10-slide PPT outline with speaker notes, 3) A mind map in Markdown format, and 4) A 10-question multiple-choice quiz with explanations. Prioritize clarity and practical application. Source: [CONTENT_LINK_OR_FILE_PATH].

Example Output

### **NotebookLM Content Package: "AI-Powered Customer Support Automation"**

**Podcast Script (5:30 min)**
*[0:00-0:45] Introduction:* Welcome to the future of customer support! Today, we’re diving into how AI is transforming support teams from reactive to proactive. We’ll cover three key areas: automation tools, training strategies, and measuring success.

*[0:46-2:10] Key Insight 1: Automation Tools:* Tools like Zendesk’s Answer Bot and Intercom’s Fin handle 60% of Tier 1 inquiries, freeing agents for complex issues. Example: Acme Corp reduced response time by 40% using these tools.

*[2:11-3:30] Key Insight 2: Training Strategies:* AI-generated training modules adapt to agent performance. At Globex Inc., new hires mastered workflows 30% faster with AI-driven simulations.

*[3:31-4:50] Key Insight 3: Measuring Success:* Track metrics like first-contact resolution (FCR) and customer satisfaction (CSAT). A 10% FCR improvement correlates with a 15% boost in CSAT.

*[4:51-5:30] Conclusion:* Start small—pilot one automation tool, train 5 agents, and track FCR for 30 days. The ROI is real.

**PPT Outline (10 Slides)**
1. **Title Slide:** AI in Customer Support: A Game-Changer
2. **Agenda:** Tools, Training, Metrics
3. **The Problem:** 70% of support tickets are repetitive
4. **Solution:** AI Automation Tools (Zendesk, Intercom)
5. **Case Study:** Acme Corp’s 40% faster response time
6. **Training Strategies:** AI-driven simulations
7. **Case Study:** Globex Inc.’s 30% faster onboarding
8. **Measuring Success:** FCR and CSAT metrics
9. **Action Plan:** 30-day pilot program
10. **Q&A:** Key takeaways

**Mind Map (Markdown)**
```
AI Customer Support
├── Automation Tools
│   ├── Zendesk Answer Bot
│   ├── Intercom Fin
│   └── ROI: 40% faster response
├── Training Strategies
│   ├── AI simulations
│   └── ROI: 30% faster onboarding
└── Success Metrics
    ├── FCR (First-Contact Resolution)
    └── CSAT (Customer Satisfaction)
```

**Quiz (10 Questions)**
1. **What percentage of Tier 1 inquiries can AI tools handle?**
   - A) 30% (B) 60% (C) 80% (D) 90%
   **Answer:** B) 60% (Source: Zendesk 2023 Report)

2. **Which company reduced response time by 40% using AI?**
   - A) Globex Inc. (B) Acme Corp (C) TechNova (D) None
   **Answer:** B) Acme Corp

3. **What’s the primary benefit of AI-driven training?**
   - A) Lower costs (B) Faster onboarding (C) Fewer agents (D) None
   **Answer:** B) Faster onboarding

4. **Which metric directly correlates with higher CSAT?**
   - A) Average handle time (B) First-contact resolution (C) Agent count (D) None
   **Answer:** B) First-contact resolution

5. **What’s the recommended pilot duration?**
   - A) 7 days (B) 14 days (C) 30 days (D) 90 days
   **Answer:** C) 30 days

... (5 more questions with explanations)