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.
Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security
Installation for Agentic Skill
View all platforms →skilz install Microck/ordinary-claude-skills/rag-implementation skilz install Microck/ordinary-claude-skills/rag-implementation --agent opencode skilz install Microck/ordinary-claude-skills/rag-implementation --agent codex skilz install Microck/ordinary-claude-skills/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...
Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/Microck/ordinary-claude-skills cp -r ordinary-claude-skills/skills_categorized/llm-ai/rag-implementation ~/.claude/skills/ Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Repository
- ordinary-claude-skills
- Type
- Non-Technical
- Meta-Domain
- general
- Primary Domain
- general
- Sub-Domain
- cd rag generation
- Market Score
- 20.5
Browse Category
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