NotebookLM Lesson Planner

Create comprehensive lesson plans for Google NotebookLM with validated sources and customized audio overview prompts.

What This Skill Does

This skill helps you create NotebookLM notebooks by:

1. Finding high-quality sources - Identifying 10-20 online resources that are publicly accessible, LLM-readable, and substantive
2. Validating sources - Ensuring all URLs are active, accessible, and not behind paywalls or crawler blocks
3. Generating tailored prompts - Creating specific prompts for each learning area that guide NotebookLM's audio overview generation
4. Structuring content - Organizing lessons to avoid redundancy and ensure comprehensive coverage

When to Use This Skill

Use this skill when the user wants to:

• Create a NotebookLM notebook on a specific topic
• Generate a learning curriculum with multiple focused audio overviews
• Build educational content with curated sources
• Process multiple topics in batch (e.g., 100+ lesson plans)

Workflow Overview

The process varies based on whether you're creating a single lesson or processing a batch:

Single Lesson Mode:

1. Gather requirements from user
2. Find and validate sources
3. Generate prompts for each learning area
4. Provide complete lesson plan

Batch Mode:

1. Process JSON specification file
2. For each lesson: find sources, validate, generate prompts
3. Output complete lesson plans for all topics

Single Lesson Mode

Step 1: Gather Requirements

Ask the user for:

1. Main topic - The overall subject (e.g., "Firewall Configuration")
2. Learning areas - Specific subtopics to cover (e.g., "ACLs", "NAT", "VPN", "Logging")
3. Listener context - Information about the learner:
   • What they already know
   • Expertise level (beginner, intermediate, advanced)
   • What they want to learn
   • Why they're learning this (use case, goal)
4. Target source count - How many sources to find (recommend 15, range 10-20)

Step 2: Find Sources

Use web_search to find sources that:

• Cover the main topic and learning areas
• Are publicly accessible (no paywall, no login)
• Are high-quality and substantive
• Provide appropriate depth for listener's level

Search strategy:

1. Start with comprehensive sources covering multiple learning areas
2. Find specialized sources for each specific learning area
3. Ensure diversity in source types (tutorials, documentation, analysis)
4. Aim for 10-20 total sources

See references/source_finding.md for detailed strategies on:

• Source quality criteria
• Search techniques
• Source type evaluation
• Coverage matrix planning

Step 3: Validate Sources

After finding sources, validate them using the validation script:

scripts/validate_sources.py url1 url2 url3 ... --verbose

The script checks:

• URL is active (200 status)
• No paywall detected
• Content is substantive (>500 chars)
• No obvious crawler blocking

If sources fail validation:

• Remove invalid sources
• Find replacements using web_search
• Re-validate until all sources pass

Step 4: Generate Prompts

For each learning area, create a tailored prompt for NotebookLM's audio overview generator.

Read prompt templates first:

view references/prompt_templates.md

Each prompt must include:

1. Topic/Learning Area - What specific area this overview covers
2. Listener Profile - Who the listener is, what they know, their expertise level
3. Coverage Scope - What this overview should cover in detail
4. Previous Coverage - What was covered in the last episode (for continuity)
5. Upcoming Topics - What will be covered in future episodes (to avoid going into detail)
6. Exclusions - Critical! What NOT to cover in detail (handled by other overviews)
7. Approach and Goals - Tone, depth, teaching style, and learning objectives
8. Length Suggestion - Duration target: [15 min] for standard, [22 min] for longer episodes
9. Additional Context - Any other relevant information

Exclusion and continuity strategy:

• Overview 1: No previous coverage, upcoming: areas 2, 3, 4
• Overview 2: Previous: area 1, upcoming: areas 3, 4
• Overview 3: Previous: areas 1-2, upcoming: area 4
• Overview 4: Previous: areas 1-3, no upcoming topics

This ensures each overview is focused, non-redundant, and builds on prior knowledge.

Case Study Requirement: One audio overview in every lesson MUST be a real-life case study focusing on real companies and their experiences. This overview should analyze actual implementation stories, challenges faced, and lessons learned from real organizations.

Step 5: Generate Quiz Prompts

For each lesson, create 4 quiz prompts based on the audio overviews. Each quiz prompt should:

1. Reference the audio overview - Which overview this quiz is based on
2. Specify length - short, default, or long
3. Specify difficulty - medium or hard
4. Guide quiz content - What topics/concepts to focus on

Quiz distribution:

• Quiz 1: Based on Overview 1 (difficulty: medium, length: default)
• Quiz 2: Based on Overview 2 (difficulty: medium, length: short)
• Quiz 3: Based on Overview 3 (difficulty: hard, length: default)
• Quiz 4: Based on Overview 4 or case study (difficulty: hard, length: long)

Step 6: Deliver Lesson Plan

Provide the user with:

1. Complete source list - All validated URLs with brief descriptions
2. Coverage summary - Which sources cover which learning areas
3. Audio Overview Prompts - One prompt per learning area, numbered and ready to use (including length suggestions)
4. Quiz Prompts - Four quiz prompts with length and difficulty specified
5. Instructions - How to use the lesson plan with NotebookLM:
   • Add all sources to NotebookLM notebook
   • For each audio overview, copy the corresponding prompt
   • Generate audio overviews in sequence
   • Generate quizzes using the quiz prompts

Output format:

# NotebookLM Lesson Plan: [Topic]

## Sources (15)

1. [Source 1 Title] - [URL]
   Coverage: [Learning areas covered]

2. [Source 2 Title] - [URL]
   Coverage: [Learning areas covered]

...

## Audio Overview Prompts

### Overview 1: [Learning Area 1] [~15 min]

[Full prompt text including: coverage, previous coverage, upcoming topics, approach and goals]

### Overview 2: [Learning Area 2] [~15 min]

[Full prompt text]

### Overview 3: [Case Study] [~22 min]

[Full prompt text - real-life case study of real companies]

...

## Quiz Prompts

### Quiz 1: [Topic] (Based on Overview 1)
**Length**: default | **Difficulty**: medium

[Full quiz prompt text]

### Quiz 2: [Topic] (Based on Overview 2)
**Length**: short | **Difficulty**: medium

[Full quiz prompt text]

...

## Usage Instructions

1. Create a new notebook in Google NotebookLM
2. Add all 15 sources to the notebook
3. For each audio overview:
   - Click "Generate Audio Overview"
   - Copy and paste the corresponding prompt above
   - Generate the overview
4. For each quiz:
   - Click "Generate Quiz"
   - Copy and paste the corresponding quiz prompt
   - Generate the quiz
5. Listen to overviews in sequence (1→2→3→...)

Batch Mode

For processing multiple topics from a JSON file.

Step 1: Understand Batch Specification

The user provides a JSON file with this structure:

{
  "lessons": [
    {
      "topic": "Sandwich Making",
      "learning_areas": ["bread", "proteins", "cheeses", "vegetables"],
      "listener_context": {
        "knows": ["basic cooking"],
        "wants_to_learn": ["gourmet techniques"],
        "skill_level": "intermediate"
      },
      "target_sources": 15
    },
    {
      "topic": "Firewall Configuration",
      "learning_areas": ["ACLs", "NAT", "VPN"],
      ...
    }
  ]
}

Step 2: Process Each Lesson

For each lesson in the batch:

1. Follow the Single Lesson Mode workflow
2. Find sources (may need multiple web_search calls)
3. Validate sources
4. Generate prompts
5. Save lesson plan to individual JSON file

Important for batch processing:

• Process lessons sequentially (don't try to parallelize)
• Be efficient with web_search (combine queries when possible)
• Validate sources in batches using the script
• Save progress incrementally (one lesson at a time)

Step 3: Output Structure

Create a directory structure:

output/
├── lesson_001_sandwich_making.json
├── lesson_002_firewall_configuration.json
├── lesson_003_database_optimization.json
...
└── batch_summary.md

Each JSON file contains:

{
  "topic": "Sandwich Making",
  "learning_areas": ["bread", "proteins", "cheeses", "vegetables"],
  "listener_context": {...},
  "sources": [
    {
      "url": "https://example.com/sandwich-guide",
      "title": "Complete Sandwich Making Guide",
      "coverage": ["bread", "proteins", "cheeses", "vegetables"]
    },
    ...
  ],
  "prompts": [
    {
      "area": "bread",
      "prompt": "Topic: Bread Selection for Sandwiches\n\n..."
    },
    ...
  ]
}

The batch_summary.md provides an overview of all lessons created.

Quality Guidelines

Source Quality

• Minimum 10 sources, maximum 20
• All sources must pass validation
• Each learning area covered by at least 3 sources
• Mix of comprehensive and specialized sources
• Appropriate depth for listener's expertise level

Prompt Quality

• Each prompt 200-350 words (optimal with new requirements)
• Clear previous coverage and upcoming topics sections
• Clear exclusions to avoid overlap
• Listener context consistent across all prompts
• Specific coverage guidance
• Appropriate tone and depth for audience
• Length suggestion included ([15 min] or [22 min])
• Approach and goals clearly stated
• At least one case study overview per lesson

Quiz Quality

• 4 quizzes per lesson minimum
• Each quiz mapped to a specific audio overview
• Mix of difficulty levels (medium and hard)
• Mix of lengths (short, default, long)
• Clear guidance on topics to test
• Questions should reinforce key concepts from the audio overviews

Coverage Balance

• No learning area should dominate (unless intentional)
• No learning area should be under-represented
• Sources should provide diverse perspectives
• Both breadth and depth appropriate for topic scope

Tips and Best Practices

Finding sources:

• Start broad, then get specific
• Use multiple search queries per learning area
• Look for official documentation first
• Check publication date for time-sensitive topics
• Verify accessibility before adding to list

Writing prompts:

• Be explicit about exclusions
• Reference other overviews by number
• Provide specific examples of what to cover
• Match technical depth to listener's level
• Include practical context (why they're learning this)

Validating sources:

• Always run validate_sources.py before finalizing
• Manually spot-check 3-5 sources
• If >20% fail validation, reconsider search strategy
• Replace failed sources before generating prompts

Batch processing:

• Process 10-20 lessons at a time
• Check one complete lesson before processing all
• Save progress frequently
• Use consistent listener_context format across batch

Common Issues

Sources failing validation:

• Check for paywall indicators in URL or title
• Try alternative sources on the same topic
• Ensure using HTTPS not HTTP
• Verify site isn't down temporarily

Overlapping prompts:

• Review exclusion sections
• Ensure each area has clear boundaries
• Consider if learning areas need restructuring
• Make exclusions more specific

Coverage gaps:

• Add more specialized sources
• Use more specific search queries
• Look for sources that bridge multiple areas
• Consider if learning areas are too granular

Batch processing slow:

• Combine search queries where possible
• Validate sources in batches
• Process during off-peak hours
• Consider breaking into smaller batches

Files and Scripts

Scripts:

• validate_sources.py - Validate URLs for NotebookLM compatibility

References:

• prompt_templates.md - Templates and examples for creating prompts
• source_finding.md - Strategies for finding high-quality sources

Usage examples in references files.