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weaviate-collection-manager

Create, view, update, and delete Weaviate collection schemas and configurations.

39|5|Updated Nov 4, 2025
Search Tags:#database#schema#RAG#management#vectorizer#collection#weaviate
One-click install
npx skills add https://github.com/saskinosie/weaviate-claude-skills --skill weaviate-collection-manager
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: weaviate-collection-manager
Source: https://github.com/saskinosie/weaviate-claude-skills/tree/main/weaviate-collection-manager
Command: npx skills add https://github.com/saskinosie/weaviate-claude-skills --skill weaviate-collection-manager

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires weaviate-client.

What problem does it solves? Manually creating and managing Weaviate collection schemas can be complex and error-prone, especially when dealing with various vectorizers, generative modules, and data types. This Skill simplifies the entire process, allowing you to define, inspect, and modify your database structure with ease.

Core Features & Use Cases

  • Schema Creation: Define new collections with specific properties, vectorizers (e.g., OpenAI, CLIP), and generative modules (for RAG).
  • Collection Inspection: View detailed configurations, properties, and vectorizer settings of existing collections.
  • Multi-modal Support: Create collections optimized for text, images, or a combination, enabling advanced search capabilities.
  • Use Case: Set up a new collection for your product catalog, defining properties for name, description, image (for multi-modal search), and price, then enable RAG for advanced querying and summarization.

Quick Start

Create a new Weaviate collection called 'MyDocuments' with the text2vec-openai vectorizer and properties for 'title' and 'content'.

Frequently Asked Questions about weaviate-collection-manager

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a Weaviate collection with a custom schema?▼

Create a Weaviate collection by defining properties, selecting a vectorizer (such as OpenAI or CLIP), and configuring optional modules like generative configs for RAG. The Skill handles schema creation end-to-end on your local Docker-based Weaviate instance running at localhost:8080.

Can I set up multi-modal search with text and image vectorization in Weaviate?▼

Yes. Use CLIP or multi-modal vectorizers to create collections optimized for both text and image data. This enables combined search across multiple modalities within a single collection.

What do I need to manage Weaviate collections locally?▼

You need a Docker-based Weaviate instance running at localhost:8080, an active weaviate-connection, and the weaviate-client Python library installed in your environment.

How do I enable RAG features on a Weaviate collection?▼

Configure generative modules when creating or updating a collection schema. The Skill supports generative_config settings that enable retrieval-augmented generation on your collections.

Can I modify vectorizer settings after creating a Weaviate collection?▼

You can view existing collection configurations and properties, then update them by adjusting vectorizer settings and properties. The Skill supports schema inspection and modification workflows on local Weaviate deployments.

What are the limitations of managing schemas through Weaviate collections?▼

Schema management requires a running local Weaviate instance at a fixed endpoint and the weaviate-client library. Complex multi-step schema migrations and bulk operations depend on your collection design and vectorizer configuration choices.

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