cursor-codebase-indexing

# Cursor Codebase Indexing Set up and optimize Cursor's codebase indexing system. Indexing creates embeddings of your code, enabling `@Codebase` semantic search and improving AI context awareness across Chat, Composer, and Agent mode. ## How Indexing Works ``` Your Code Files │ ▼ Syntax Chunking ─── splits files into meaningful code blocks │ ▼ Embedding Generation ─── converts chunks to vector representations │ ▼ Vector Storage (Turbopuffer) ─── cloud-hosted nearest-neighbor search │ ▼ @Codebase Query ─── your question → embedding → similarity search → relevant chunks ``` ### Key Architecture Details - **Merkle tree** for change detection: only modified files are re-indexed (every 10 minutes) - **No plaintext storage**: code is not stored server-side; only embeddings and obfuscated metadata - **Privacy Mode compatible**: with Privacy Mode on, embeddings are computed without retaining source code - Indexing runs in the background; small projects complete in seconds, large projects (50K+ files) may take hours initially ## Initial Setup 1. Open your project in Cursor 2. Indexing starts automatically on first open 3. Check status: look at the bottom status bar for "Indexing..." indicator 4. View indexed files: `Cursor Settings` > `Features` > `Codebase Indexing` > `View included files` ### Verify Indexing Status The status bar shows: - **"Indexing..."** with progress indicator -- initial indexing in progress - **"In...