📄 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.

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

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

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