Implements high-performance vector search and RAG patterns using the Weaviate TypeScript v3 client.
This skill provides specialized patterns for integrating Weaviate, a leading open-source vector database, into Claude Code workflows. It focuses on the latest TypeScript v3 client, covering essential operations from gRPC connection management and collection configuration to advanced hybrid search and Retrieval Augmented Generation (RAG). By enforcing best practices like proper client cleanup, multi-tenant isolation, and optimized query timeouts, it enables developers to build scalable, AI-native applications that leverage built-in vectorization and semantic search with minimal boilerplate.
Key Features
015 GitHub stars
02Multi-tenant collection management and data isolation lifecycle
03Type-safe collection configuration and vectorizer module setup
04Advanced search patterns including nearText, nearVector, BM25, and Hybrid search
05Native RAG (Generative Search) implementation with singlePrompt and groupedTask
06High-performance batch imports with automated error handling
Use Cases
01Building semantic search engines that combine keyword and vector relevance
02Managing isolated vector data for multi-user SaaS applications
03Implementing Retrieval Augmented Generation (RAG) for AI agents and chatbots
