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rag-implementationby Seth HobsonDevelopmentGitHub stars: 41.8k

RAG Implementation skill: what it does and how to install it

Builds Retrieval-Augmented Generation systems with vector databases, semantic search and grounded answers for knowledge-based LLM applications.

Summary generated from the skill's documentation.

Install

$ npx skills add wshobson/agents --skill rag-implementation

Run it in a terminal. If your agent is already running, start a new session so it picks the skill up.

About this skill

What it does. Guides the design of RAG applications that ingest external knowledge, embed and retrieve documents, optionally rerank results, and generate grounded answers. It covers dense, sparse, hybrid, multi-query and HyDE retrieval, with a LangGraph example using LangChain, Anthropic, Voyage AI and Pinecone.

When to use it. For document Q&A, semantic search, documentation assistants, research tools and chatbots that need domain-specific or current information with fewer hallucinations.

History

Repo stars

41.8k+1.5k since 5 Oct 2026

Stars are counted for the whole repository, which holds 76 skills.

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Repo stars by day
DateRepo stars
26 Oct 202641,741
25 Oct 202641,668
24 Oct 202641,623
23 Oct 202641,590
22 Oct 202641,533
21 Oct 202641,400
20 Oct 202641,212
19 Oct 202641,081
18 Oct 202640,990
17 Oct 202640,943
16 Oct 202640,891
15 Oct 202640,824
14 Oct 202640,663
13 Oct 202640,579
12 Oct 202640,457
11 Oct 202640,368
10 Oct 202640,319
9 Oct 202640,307
8 Oct 202640,296
7 Oct 202640,267
6 Oct 202640,238
5 Oct 202640,212

Installs

14k

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Installs via skills.sh

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