Skillzwave

rag-implementation

38 stars 2 forks Updated Dec 24, 2025
53.6

Build Retrieval-Augmented Generation (RAG) systems for AI 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.

Commands Marketplace
#retrieval#case#RAG#document#documents
Also in: pdf database api

Third-Party Skill: Review the code before installing. Skills execute in your AI assistant's environment and can access your files. Learn more about security

skilz install giuseppe-trisciuoglio_developer-kit/rag-implementation
skilz install giuseppe-trisciuoglio_developer-kit/rag-implementation --agent opencode
skilz install giuseppe-trisciuoglio_developer-kit/rag-implementation --agent codex
skilz install giuseppe-trisciuoglio_developer-kit/rag-implementation --agent gemini

First time? Install Skilz: pip install skilz

Works with 14 AI coding assistants

Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...

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Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/giuseppe-trisciuoglio/developer-kit
2. Copy the skill directory:
cp -r developer-kit/skills/ai/rag ~/.claude/skills/

Need detailed installation help? Check our platform-specific guides:

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Details

Repository
developer-kit
Stars
38
Forks
2
Type
Technical
Meta-Domain
productivity
Primary Domain
word
Sub-Domain
style format
Skill Size
42.2 KB
Files
8
Quality Score
53.6

AI-Detected Topics

Extracted using NLP analysis

retrieval case RAG document documents

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