Claude Code skills for RAG engineers
Ship reliable retrieval-augmented generation faster with battle-tested skills for routing, fallbacks, and debugging.
RAG engineers use Loreto skills to route queries to the right vector store, define fallback behavior when retrieval returns nothing, and diagnose why a pipeline answers wrong — all packaged as Claude Code skills.
Skills to start with
Agentic RAG Fallback
Designs a Retrieve-Check-Route fallback pattern for agentic (multi-tool) RAG systems so that when every retriever tool…
Agentic RAG Routing
Designs an agentic RAG architecture where an LLM agent acts as a dynamic router, semantically selecting the correct dom…
RAG Pipeline Vector DB
Designs a traditional RAG pipeline organized around the Query-Retrieve-Augment-Generate (QRAG) flow and its single-LLM-…
RAG Pipeline Vector Store
Designs a baseline single-hop RAG pipeline that grounds LLM answers in private or domain-specific documents via vector…
RAG Query Routing
Designs and implements LLM-backed query routing across multiple domain-specific vector stores using the retriever-tool…
RAG Relevance Fallback
Designs a conditional fallback branch in a single-store RAG pipeline so that when retrieved documents are irrelevant or…
Your workflow, as a skill
Loreto turns what you already know into a Claude Code skill your agent can run on demand.