RAG Retrieval for Claude Code FAQs

Question 1

What are the hardware requirements for local RAG?

Accepted Answer

The skill requires at least 2GB of RAM to handle vector operations and local search efficiently within the Claude Code environment.

Question 2

Does this skill send my documents to the cloud for indexing?

Accepted Answer

No, document indexing and vector storage happen entirely on your local machine using ChromaDB, though the final answer generation uses Claude Haiku via the Anthropic API.

Question 3

Does this skill increase my Claude API token usage?

Accepted Answer

The retrieval bridge itself is designed for zero token use; tokens are only consumed when Claude Haiku generates the final synthesized answer based on the retrieved text.

Question 4

What is the benefit of hybrid search mode?

Accepted Answer

Hybrid mode combines vector similarity for conceptual matching with keyword matching for specific technical terms, ensuring higher accuracy for technical documentation.

Question 5

How do I add new documents to the RAG knowledge base?

Accepted Answer

You can index new content by running the provided indexing script pointing to your document folder, which populates the local vector database.

RAG Retrieval for Claude Code

Key Features

Use Cases

RAG Retrieval for Claude Code

Key Features

Use Cases