📄 Query Google NotebookLM notebooks using Claude Code for accurate, citation-backed answers based on your documents.

📄 Connect Claude Code with NotebookLM for precise, document-based answers from your notebooks, enhancing accuracy and reducing misinformation.

The system takes a brief textual description, prompt, or statement from the user and analyzes it to determine if it correctly expresses a prophetic or visionary statement in the perfect tense. Using p

A new package is designed to analyze user inputs related to avoiding negative or unwelcome appearances on a Louis Rossmann video. It processes the text input to identify key factors or common pitfalls

Connect NotebookLM research with Claude to generate structured content from URLs, PDFs, and trending topics for multi-platform publishing.

🔍 Analyze and verify prophetic statements in the perfect tense with the `prophecyperfect` Python package for accurate textual insights.