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Use case

Claude Code skills for AI agent builders

Build agents that route work correctly, fall back gracefully, and don’t get locked into one harness.

Quick answer

Agent builders use Loreto skills to route queries to the right store, define fallback behavior when retrieval is empty, and route work across the right AI harness.

Skills to start with

RAG

Agentic RAG Fallback

Designs a Retrieve-Check-Route fallback pattern for agentic (multi-tool) RAG systems so that when every retriever tool…

RAG

Agentic RAG Routing

Designs an agentic RAG architecture where an LLM agent acts as a dynamic router, semantically selecting the correct dom…

AI Harnesses

Detecting Harness Lockin

Identifies and quantifies the compounding switching cost of an AI coding agent harness commitment before it becomes inv…

RAG

RAG Pipeline Vector DB

Designs a traditional RAG pipeline organized around the Query-Retrieve-Augment-Generate (QRAG) flow and its single-LLM-…

RAG

RAG Pipeline Vector Store

Designs a baseline single-hop RAG pipeline that grounds LLM answers in private or domain-specific documents via vector…

RAG

RAG Query Routing

Designs and implements LLM-backed query routing across multiple domain-specific vector stores using the retriever-tool…

RAG

RAG Relevance Fallback

Designs a conditional fallback branch in a single-store RAG pipeline so that when retrieved documents are irrelevant or…

AI Harnesses

Routing Work Across AI Harnesses

Designs hybrid agent workflows that route tasks intelligently between AI coding agent harnesses based on task character…

Your workflow, as a skill

Loreto turns what you already know into a Claude Code skill your agent can run on demand.