RAG Search

RAG Search extends your AI assistant with the ability to backend retrieval skill for structured search of occupational health standards and documents, returning relevant text with source and clause details. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly — and it will take care of the task end-to-end, using RAG Search as its underlying capability.

RAG Search works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) — an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install RAG Search once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.

Getting started with RAG Search takes about two minutes. Place the skill at `~/.claude/skills/rag-search/` (personal, all projects) or `.claude/skills/rag-search/` (project-specific), then restart your AI client. From that point, typing `/rag-search` in any conversation activates it, or the AI will use it on its own when it detects a relevant request.

RAG Search has been installed 2,692 times, making it one of the more actively used skills in the Data & Analytics category. The install rate suggests it solves a real, recurring need rather than a niche edge case. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.