notebooklm-learner-pack

Name: notebooklm-learner-pack
Availability: InStock
Author: drmultivac

Generate topic-grounded NotebookLM Learner Packs as self-contained HTML files.

22|10|Updated Apr 15, 2026

Search Tags:#html #grounding #prompts #notebooklm #brand-voice #prompt-library #learner-pack

Ready to run

npx skills add https://github.com/DrMultivac/notebooklm-learner-pack --skill notebooklm-learner-pack

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: notebooklm-learner-pack
Source: https://github.com/DrMultivac/notebooklm-learner-pack/tree/main
Command: npx skills add https://github.com/DrMultivac/notebooklm-learner-pack --skill notebooklm-learner-pack

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The NotebookLM Learner Pack skill automatically converts topic and source context into a branded, copy-paste-ready prompt library, enabling rapid creation of explainer assets and knowledge checks.

Core Features & Use Cases

Grounded prompts: 29 prompts across 5 asset types (infographics, slide decks, audio, video storyboards, knowledge tests) built from topic and source material.
Brand voice immersion: supports Techy Surgeon, Duke Health, RevelAi Modern Enterprise, and custom brands to match your audience.
Dual-filter rendering: single HTML output with live audience-lens toggling and asset-type filtering for targeted prompts.
Reusable prompts: prompts are fully grounded and constructed to reference actual constructs, actors, and metrics from the provided corpus.

Quick Start

Provide the topic and brand (and optional source materials) to generate a self-contained HTML Learner Pack ready to paste into NotebookLM.

Frequently Asked Questions about notebooklm-learner-pack

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate a NotebookLM prompt pack from source material?▼

To generate a NotebookLM prompt pack, provide your topic, brand, and optional source materials to produce a self-contained HTML file with 29 grounded prompts across 5 asset types and 6 audience lenses. The output is ready to paste directly into NotebookLM.

What is a dual-filter rendering UI for a prompt library?▼

A dual-filter rendering UI is a single HTML interface that features live audience-lens toggling and asset-type filtering. It allows users to interactively narrow down the 29 generated prompts to find targeted assets for specific audiences.

Can I customize the brand voice for NotebookLM explainer assets?▼

Yes, you can customize the brand voice for NotebookLM explainer assets. The generator supports Techy Surgeon, Duke Health, RevelAi Modern Enterprise, and custom brands to ensure prompt outputs match your specific audience.

What types of explainer assets can I create with grounded NotebookLM prompts?▼

You can create five types of explainer assets with grounded NotebookLM prompts: infographics, slide decks, audio, video storyboards, and knowledge tests. All 29 prompts reference actual constructs and metrics from your provided corpus.

Do I need external source documents to build a topic-grounded prompt library?▼

No, external source documents are optional. You can build a topic-grounded prompt library by providing just the topic and brand, though adding source materials ensures the generated prompts reference actual constructs, actors, and metrics.

How many audience lenses are included in a NotebookLM Learner Pack?▼

A NotebookLM Learner Pack includes 6 audience lenses. These lenses work alongside the 29 prompts and 5 asset types, allowing you to filter the generated HTML output for highly targeted explainer assets and knowledge checks.