rag-design-patterns
About
This Claude Skill automatically provides RAG system design patterns when building retrieval-augmented generation applications. It offers guidance on document chunking strategies, vector database selection, embedding management, and retrieval optimization techniques. Developers should use it when implementing RAG systems to ensure proper architecture and performance.
Quick Install
Claude Code
Recommendednpx skills add mattnigh/skills_collection -a claude-code/plugin add https://github.com/mattnigh/skills_collectiongit clone https://github.com/mattnigh/skills_collection.git ~/.claude/skills/rag-design-patternsCopy and paste this command in Claude Code to install this skill
GitHub Repository
Frequently asked questions
What is the rag-design-patterns skill?
rag-design-patterns is a Claude Skill by mattnigh. Skills package instructions and resources that Claude loads on demand, so Claude can perform rag-design-patterns-related tasks without extra prompting.
How do I install rag-design-patterns?
Use the install commands on this page: add rag-design-patterns to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does rag-design-patterns belong to?
rag-design-patterns is in the Other category, tagged automation, design, and data.
Is rag-design-patterns free to use?
Yes. rag-design-patterns is listed on AIMCP and free to install.
Related Skills
This Claude Skill automatically guides model and provider selection for LLM applications. It provides patterns for cost optimization, fallback strategies, and multi-model routing across providers like OpenAI and Anthropic. Use it when implementing model comparison, provider failover, or performance/cost trade-offs in your LLM system.
This Claude Skill automatically guides multi-agent system design by enforcing proper tool schema creation with Pydantic, managing agent states, and implementing robust error handling. It provides orchestration patterns for reliable tool-calling workflows and agent routing. Use it when building complex agent systems to ensure maintainable and structured interactions.
The ai-security skill automatically applies security protections for AI/LLM applications. It provides prompt injection detection, PII redaction, output filtering, and content moderation. Use this skill when building LLM applications that need built-in security guardrails.
This skill automatically guides model and provider selection for LLM applications. It provides patterns for cost optimization, fallback strategies, and multi-model routing across providers like OpenAI and Anthropic. Use it when implementing model comparison, provider failover, or cost-performance optimization in your LLM system.