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google-gemini-file-search

Enable document Q&A and semantic search across 100+ file formats using Google Gemini File Search.

961|99|Updated Oct 20, 2025
Search Tags:#semantic search#knowledge base#RAG#file upload#Google Gemini#document search#document Q&A
One-click install
npx skills add https://github.com/jezweb/claude-skills --skill google-gemini-file-search
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: google-gemini-file-search
Source: https://github.com/jezweb/claude-skills/tree/main/skills/google-gemini-file-search
Command: npx skills add https://github.com/jezweb/claude-skills --skill google-gemini-file-search

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @google/genai, and includes scripts (resource) and references (resource) and templates (resource) components.

What problem does it solve?

This Skill eliminates the complexity of building document search systems by providing fully managed RAG with automatic chunking, embeddings, and citations.

Core Features & Use Cases

  • Semantic Search: Upload 100+ file formats and query with natural language understanding.
  • Managed Infrastructure: No vector databases or custom embedding code required.
  • Use Case: Imagine you have customer support manuals, legal contracts, and technical documentation scattered across multiple formats. Use this Skill to create a unified searchable knowledge base with automatic source citations.

Quick Start

Create a file search store named "support-docs" and upload the PDF file "user-manual.pdf" for semantic search.

Frequently Asked Questions about google-gemini-file-search

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

FAQPage Schema
How do I build a searchable knowledge base from multiple document formats?▼

Semantic search across 100+ file formats like PDFs, Word, and Excel uses Google Gemini File Search to automatically chunk documents, generate embeddings, and index content without vector databases. Upload your files to create a unified knowledge base queryable by natural language.

Can I use Google Gemini for document Q&A without managing embeddings myself?▼

Yes. Google Gemini File Search provides fully managed RAG—automatic chunking, embeddings, and citations are built in. You upload documents and query them directly; no custom embedding code or infrastructure setup required.

What file formats does Gemini File Search support for semantic search?▼

Gemini File Search handles 100+ formats including PDFs, Microsoft Word, Excel spreadsheets, and code files. All are automatically chunked and indexed for natural language queries with source citations.

How do I configure document chunking and metadata filtering for large knowledge bases?▼

Configure chunking with maxTokensPerChunk and overlap parameters to control index granularity. Add up to 20 key-value pair metadata filters to organize and retrieve documents by custom attributes within your knowledge base.

What's the pricing model for indexing documents with Gemini File Search?▼

Indexing uses one-time pricing at $0.15 per 1 million tokens. There's no per-query cost; you pay once when the file store is created and documents are indexed.

How do I handle updates to documents already in my searchable knowledge base?▼

Documents in Gemini File Search are immutable. To update indexed content, delete the existing document and re-upload the new version to refresh your knowledge base.

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