weaviate

Ask questions and get generated answers with sources (Query Agent ask mode)

List all collections in Weaviate or get the schema of an individual collection

Create example data

Explore a Weaviate collection's data, including property metrics and sample objects

Fetch and filter objects from Weaviate collections

Query Weaviate using natural language (Query Agent search mode)

Interactive onboarding guide — set up Weaviate Cloud, configure credentials, load data, and learn every command

Search a Weaviate collection using hybrid, semantic, or keyword search

Use this skill when the user wants to build AI applications with Weaviate. It contains a high-level index of architectural patterns, 'one-shot' blueprints, and best practices for common use cases. Currently, it includes references for building a Query Agent Chatbot, Data Explorer, Multimodal PDF RAG (Document Search), Basic RAG, Advanced RAG, Basic Agent, Agentic RAG, and optional guidance on how to build a frontend for each of them.

Search, query, and manage Weaviate vector database collections. Use for semantic search, hybrid search, keyword search, natural language queries with AI-generated answers, collection management, data exploration, filtered fetching, data imports from CSV/JSON/JSONL files, create example data and collection creation.