rag-architecture
Retrieval-Augmented Generation (RAG) system design patterns, chunking strategies, embedding models, retrieval techniques, and context assembly. Use when designing RAG pipelines, improving retrieval quality, or building knowledge-grounded LLM applications.
npx skills add majiayu000/claude-skill-registry --skill rag-architecture --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# RAG Architecture ## When to Use This Skill Use this skill when: - Designing RAG pipelines for LLM applications - Choosing chunking and embedding strategies - Optimizing retrieval quality and relevance - Building knowledge-grounded AI systems - Implementing hybrid search (dense + sparse) - Designing multi-stage retrieval pipelines **Keywords:** RAG, retrieval-augmented generation, embeddings, chunking, vector search, semantic search, context window, grounding, knowledge base, hybrid search, reranking, BM25, dense retrieval ## RAG Architecture Overview ```text ┌─────────────────────────────────────────────────────────────────────┐ │ RAG Pipeline │ ├─────────────────────────────────────────────────────────────────────┤ │ │ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────────────┐ │ │ │ Ingestion │ │ Indexing │ │ Vector Store │ │ │ │ Pipeline │───▶│ Pipeline │───▶│ (Embeddings) │ │ │ └──────────────┘ └──────────────┘ └──────────────────────┘ │ │ │ │ │ │ │ Documents Chunks + Indexed │ │ Embeddings Vectors │ │ │ │ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────────────┐ │ │ │ Query │ │ Retrieval │ │ Context Assembly │ │ │ │ Processing │───▶│ Engine │───▶│ + Generation │ │ │ └───
- When to Use This Skill
- RAG Architecture Overview
- Document Ingestion Pipeline
- Document Processing Steps
- Chunking Strategies
- Strategy Comparison
- Chunking Decision Tree
- Chunk Overlap
- Chunk Size Trade-offs
- Embedding Models
- Model Comparison
- Embedding Selection
- Embedding Optimization
- Retrieval Strategies
What does the rag-architecture skill do?
Retrieval-Augmented Generation (RAG) system design patterns, chunking strategies, embedding models, retrieval techniques, and context assembly. Use when designing RAG pipelines, improving retrieval quality, or building knowledge-grounded LLM applications.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill rag-architecture --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.