AnkiNLM

v1.2 Changelog ✨ Better LaTeX compatibility — CSVs are now formatted to preserve LaTeX syntax (e.g., \sin(x), \frac{a}{b}, etc.) so your math renders correctly in Anki. 🧮 Optimized for math-heavy flashcards — When imported, cards can now display formulas and equations just like they appear in NotebookLM. 📄 Cleaner CSV output — Minor formatting refinements for improved readability and consistent field separation. Recommended setup To properly render mathematical formulas in Anki, you’ll need an add-on that interprets LaTeX syntax. After testing several options, we recommend “Better Markdown Anki” (ID 2100166052) — it provides the best rendering results and works seamlessly with the CSVs exported by AnkiNLM. Note: This add-on is not developed or maintained by the AnkiNLM team. You’re free to use any other add-on or template that supports LaTeX or MathJax rendering in Anki. --------------------------------------------------- AnkiNLM is a lightweight browser extension that helps you instantly transfer flashcards generated in Google NotebookLM into Anki. Once installed, it adds “Copy CSV” and “Download CSV” buttons at the bottom of the NotebookLM Studio flashcard footer, giving you a ready-to-import CSV file in one click. Stop manually rewriting cards. Start studying faster. 📚 How it works: 1. Open any NotebookLM Studio with generated flashcards 2. Scroll to the flashcard section footer 3. Click “Download CSV” or “Copy CSV” 4. Open Anki and import the CSV 5. Set Field 1 = Front and Field 2 = Back 6. Choose your deck and finish the import ✅ Features: * One-click CSV export * Copy or download support * 100% compatible with Anki field mapping * No setup required * Lightweight and privacy-friendly 🔒 Importing into Anki: Anki Desktop (Windows/Mac/Linux): 1. File > Import 2. Choose the CSV 3. Map Field 1 → Front, Field 2 → Back 4. Confirm import AnkiMobile (iOS) or AnkiDroid (Android): 1. Transfer or paste the CSV 2. Import via app or AnkiWeb sync AnkiWeb: 1. Open or create a deck 2. Click Add → Import File Perfect for: * NotebookLM users who rely on flashcards * Students looking for a faster study workflow * Anyone building an automatic NotebookLM → Anki pipeline 🚀