weaviate

name	weaviate
description	Search, query, inspect, create, and import data into Weaviate vector database collections using official scripts and references.
category	databases
risk	critical
source	community
source_repo	weaviate/agent-skills
source_type	official
date_added	2026-06-29
author	Weaviate
tags	["weaviate","vector-database","semantic-search","hybrid-search","data-import"]
tools	["python","weaviate"]
license	BSD-3-Clause
license_source	https://github.com/weaviate/agent-skills/blob/main/LICENSE

Weaviate Database Operations

This skill provides comprehensive access to Weaviate vector databases including search operations, natural language queries, schema inspection, data exploration, filtered fetching, collection creation, and data imports.

When to Use This Skill

• Use when the user needs to inspect Weaviate collections, schemas, or data distribution.
• Use when running semantic, hybrid, keyword, filtered, or Query Agent searches against Weaviate.
• Use when importing CSV, JSON, JSONL, or PDF data into a Weaviate collection.
• Use when creating example data or a collection for a Weaviate-backed workflow.

Weaviate Cloud Instance

If the user does not have an instance yet, direct them to the cloud console to register and create a free sandbox. Create a Weaviate instance via Weaviate Cloud.

Environment Variables

Required:

• WEAVIATE_URL - Your Weaviate Cloud cluster URL
• WEAVIATE_API_KEY - Your Weaviate API key

External Provider Keys (auto-detected): Set only the keys your collections use, refer to Environment Requirements for more information.

Script Index

Search & Query

• Query Agent - Ask Mode: Use when the user wants a direct answer to a question based on collection data. The Query Agent synthesizes information from one or more collections and returns a structured response with source citations (collection name and object ID).
• Query Agent - Search Mode: Use when the user wants to explore or browse raw objects across one or more collections. Unlike ask mode, this returns the actual data objects rather than a synthesized answer.
• Hybrid Search: Default choice for most searches. Provides a good balance of semantic understanding and exact keyword matching. Use this when you are unsure which search type to pick.
• Semantic Search: Use for finding regardless of exact wording. Best when the intent matters more than specific keywords.