This project provides an end-to-end automated content creation pipeline, integrating deep research capabilities with AI-powered content synthesis and multi-platform publishing. It targets users seeking to streamline workflows from trending topic discovery and source analysis to generating diverse content formats like articles, social posts, podcasts, and presentations. The primary benefit is a fully automated, AI-assisted content lifecycle, reducing manual effort and accelerating output.

How It Works

The system orchestrates a four-phase workflow: collection, research, generation, and publishing. It leverages notebooklm-py (v0.3.4, pure async Python) to interact with NotebookLM, creating notebooks from various sources (URLs, PDFs, trending topics). Deep research queries are executed against these notebooks, extracting structured insights. These findings then feed into Claude for polished content generation across multiple formats. An additional phase supports generating diverse artifacts, including audio, video, slides, reports, quizzes, and flashcards, facilitating comprehensive content production.

Quick Start & Requirements

Installation is streamlined via uvx (recommended, zero install: uvx notebooklm-skill --help), pip (pip install notebooklm-skill), or from source. Authentication is simplified through a one-time, browser-based Google login, eliminating the need for API keys or OAuth setup; sessions are stored locally. Key commands include notebooklm-skill create, ask, and podcast. Python 3.10+ is required. Full setup details are available in docs/SETUP.md.

Highlighted Details

• Extensive Artifact Generation: Supports 9 downloadable artifact types: audio (M4A podcast), video (MP4), slides (PDF/PPTX), report (Markdown), quiz (JSON/Markdown/HTML), flashcards (JSON/Markdown/HTML), mind map (JSON), data table (CSV), and study guide (Markdown).
• Dual Interface Options: Functions as a Claude Code Skill for seamless integration within Claude workflows or as a standalone MCP Server, compatible with clients like Cursor and Gemini CLI.
• Simplified Authentication: Utilizes browser-based Google login, removing complex API key management and OAuth configurations.
• Integrated Topic Discovery: Features optional integrations with trend-pulse for automated trending topic discovery and threads-viral-agent for publishing research-backed social posts.

Maintenance & Community

The provided README does not detail specific contributors, sponsorships, roadmap updates, or community channels (e.g., Discord, Slack). Contribution guidelines are present, outlining standard fork-and-pull-request workflows for development.

Licensing & Compatibility

The project is released under the permissive MIT License. This license generally allows for broad compatibility, including commercial use and integration within closed-source applications without significant restrictions.

Limitations & Caveats

The 'infographic' artifact generation is noted with a "⚠️ no download" indicator, suggesting potential limitations in direct exportability. Authentication sessions, while persistent for weeks, may require re-authentication if errors occur.