agentic-rag

Iteratively refine queries with semantic search to retrieve comprehensive information.

Updated Jun 16, 2026

Search Tags:#context #semantic search #rag #search #iterative #query-rewriting

Ready to run

npx skills add https://github.com/breakingcircuits1337/agent-skills --skill agentic-rag-breakingcircuits1337

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: agentic-rag
Source: https://github.com/breakingcircuits1337/agent-skills/tree/main/agentic-rag
Command: npx skills add https://github.com/breakingcircuits1337/agent-skills --skill agentic-rag-breakingcircuits1337

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Agentic RAG solves the challenge of retrieving comprehensive and relevant information from complex requests by iteratively refining queries.

Core Features & Use Cases

Iterative Query Refinement: Enhances initial searches to uncover deeper context.
Relevant Information Retrieval: Delivers the most pertinent information for complex requests.
Use Case: When faced with a multifaceted research question, Agentic RAG helps to refine the search and provide a comprehensive answer.

Quick Start

Activate the agentic-rag skill with the query: "Find all relevant context for AI research."

Frequently Asked Questions about agentic-rag

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

FAQPage Schema

How does iterative query refinement improve semantic search results?▼

Iterative query refinement improves semantic search by rewriting initial queries to uncover deeper, hidden context, ensuring comprehensive information retrieval for complex requests. It systematically enhances the search parameters to find pertinent data.

How do I retrieve comprehensive context for multifaceted research questions?▼

To retrieve comprehensive context for multifaceted research questions, use an agentic approach that applies iterative query rewriting. This method systematically refines search terms to extract all relevant information from your available data sources.

What is the best way to find hidden context in complex search requests?▼

The best way to find hidden context in complex search requests is using iterative query refinement combined with semantic search. This approach systematically rewrites and enhances queries to reveal deeper, pertinent information not immediately obvious.

Do I need natural language processing libraries to use iterative query rewriting?▼

Yes, you need natural language processing and semantic search libraries to utilize iterative query rewriting. These libraries provide the necessary computational foundation to parse, understand, and systematically refine complex search queries.

When should I use agentic retrieval for complex information requests?▼

You should use agentic retrieval for complex information requests when a basic search fails to deliver comprehensive results. It is specifically designed for multifaceted research questions that require iterative query refinement to uncover hidden context.