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rag-implementation

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28.2kSmitheryGeneralby wshobson

Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.

Install & Usage

1
Create the skills directory
mkdir -p .claude/skills
2
Download the skill file
mkdir -p .claude/skills && curl -o .claude/skills/rag-implementation.md https://raw.githubusercontent.com/wshobson/agents/main/plugins/llm-application-dev/skills/rag-implementation/SKILL.md
3
Invoke in Claude Code
/rag-implementation
View source on GitHub
documentationai-&-ml

Frequently Asked Questions

What is rag-implementation?

Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.

How to install rag-implementation?

To install rag-implementation, create the .claude/skills directory in your project, then run the curl command to download the skill file. Once installed, invoke it in Claude Code with /rag-implementation.

What is rag-implementation best for?

rag-implementation is a community categorized under General. It is designed for: documentation, ai-&-ml. Created by wshobson.