Notebooklm Research

NotebookLM Research

Use youtube_notebooklm when the user wants market research, trend mapping, competitor scans, or synthesis from YouTube sources through NotebookLM.

Primary Action

Use youtube_to_notebook_workflow for end-to-end execution:

1. Search YouTube
2. Create NotebookLM notebook
3. Add videos as sources
4. Ask NotebookLM for analysis
5. Optionally generate/download infographic

First-run check:

• Call setup_status first. If setupRequired: true, run the returned

next_steps commands before continuing.

Fast Start

{
  "action": "youtube_to_notebook_workflow",
  "query": "Claude Code skills marketing",
  "count": 10,
  "months": 6,
  "question": "What are the strongest recurring GTM patterns and differentiators across these videos?",
  "generate_infographic": true,
  "infographic_prompt": "Create a handwritten blueprint style infographic with GTM patterns, risks, and opportunities.",
  "infographic_orientation": "portrait",
  "infographic_detail": "detailed"
}

Granular Actions

• youtube_search
• setup_status
• notebook_create
• notebook_add_sources
• notebook_ask
• notebook_generate_infographic

Use granular actions if the user wants custom sequencing or to reuse an existing notebook.

Prerequisites

Install dependencies once:

pip install yt-dlp
pip install "notebooklm-py[browser]"
playwright install chromium
notebooklm login

If commands fail, report missing prerequisites and suggest the exact install/login command.

Operating Notes

• Default recency filter is last 6 months (months: 6).
• Set no_date_filter: true to include all upload dates.
• Keep wait_for_sources: true for reliable downstream analysis.
• For stakeholder-ready output, enable generate_infographic and keep the prompt specific.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: ArgentAIOS
• Source: ArgentAIOS/agent-skills
• License: MIT

Install and usage instructions live in the source repository linked above.