rag-architect
Use when the user asks to design RAG pipelines, optimize retrieval strategies, choose embedding models, implement vector search, or build knowledge retrieval systems.
npx skills add majiayu000/claude-skill-registry --skill rag-architect-alirezarezvani-claude-skills --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 Architect - POWERFUL ## Overview The RAG (Retrieval-Augmented Generation) Architect skill provides comprehensive tools and knowledge for designing, implementing, and optimizing production-grade RAG pipelines. This skill covers the entire RAG ecosystem from document chunking strategies to evaluation frameworks, enabling you to build scalable, efficient, and accurate retrieval systems. ## Core Competencies ### 1. Document Processing & Chunking Strategies #### Fixed-Size Chunking - **Character-based chunking**: Simple splitting by character count (e.g., 512, 1024, 2048 chars) - **Token-based chunking**: Splitting by token count to respect model limits - **Overlap strategies**: 10-20% overlap to maintain context continuity - **Pros**: Predictable chunk sizes, simple implementation, consistent processing time - **Cons**: May break semantic units, context boundaries ignored - **Best for**: Uniform documents, when consistent chunk sizes are critical #### Sentence-Based Chunking - **Sentence boundary detection**: Using NLTK, spaCy, or regex patterns - **Sentence grouping**: Combining sentences until size threshold is reached - **Paragraph preservation**: Avoiding mid-paragraph splits
- Overview
- Core Competencies
- 1. Document Processing & Chunking Strategies
- 2. Embedding Model Selection
- 3. Vector Database Selection
- 4. Retrieval Strategies
- 5. Query Transformation Techniques
- 6. Context Window Optimization
- 7. Evaluation Frameworks
- 8. Production Patterns
- 9. Cost Optimization
- 10. Guardrails & Safety
- Implementation Best Practices
- Development Workflow
What does the rag-architect skill do?
Use when the user asks to design RAG pipelines, optimize retrieval strategies, choose embedding models, implement vector search, or build knowledge retrieval systems.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill rag-architect-alirezarezvani-claude-skills --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.