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rag_search

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Semantic search over your RAG vector store.

Data & Analytics#context#embeddings#rag#search#retrieval#vector#semantic
AuthorMichaelYagi
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This skill enables fast semantic search over a RAG vector database to locate relevant chunks and contextual information, reducing manual digging through documents.

Core Features & Use Cases

  • Semantic retrieval: search across a vector store to fetch semantically related chunks.
  • Contextual grounding: gather supporting context for answers from multiple sources.
  • Use Case: when you need to locate documents mentioning a topic across a large corpus and present concise results.

Quick Start

Example: Use rag_search_tool to query for a topic, such as "latest onboarding guidelines" and review the retrieved results.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: rag_search
Download link: https://github.com/MichaelYagi/mcp_a2a/archive/main.zip#rag-search

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
View Source Repository

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