RAG
Retrieval-augmented generation. Ground answers in your documents and knowledge base.
Details
RAG skill lets your agent retrieve relevant chunks from a vector store and use them in answers. For custom knowledge and internal docs.
When to use
Use when the agent must answer from your private docs or knowledge base. Requires vector store; good for internal Q&A and support.
How RAG fits into your OpenClaw setup
AI/ML skills change what your assistant fundamentally is, rather than just what it can do. They add learning loops, memory, and self-improvement on top of the base model. RAG operates at this layer, which is why it is worth installing deliberately and early — capabilities that compound over time deliver more the longer they run.
How it works in practice
After installation, RAG mostly works in the background. You will notice its effect in the assistant's behaviour over weeks rather than in any single reply: fewer repeated mistakes, better recall of how you like things done, and responses that fit your context more precisely. Periodically reviewing what the assistant has learned keeps the loop honest.
Installing RAG
Installation follows the standard ClawHub flow. From your OpenClaw directory, run the install command below, then restart your assistant so the new capability registers. If the skill needs credentials or API access, its README will say so — set those up before the first use.
When the assistant comes back online, give it one easy request that only this skill can handle. If it responds correctly, you are done. If not, you have caught the problem while the install is still fresh in your mind — far better than discovering it mid-task next week.
clawhub install ragGetting the most out of it
Think of RAG as one instrument in an ensemble. OpenClaw's real strength is composition — the assistant combining several skills in a single task because the request demanded it. When you browse the catalogue, look for the skills that complete your workflows, not just the ones that sound impressive in isolation.
Setting this up well takes judgment as much as effort — which skills, in what configuration, integrated with which of your tools. That is the work we do for clients: full OpenClaw setup, skills like RAG tuned to your workflow, and custom development where nothing off the shelf fits.