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RAG Query Optimizer
Optimize this query for RAG (Retrieval-Augmented Generation) retrieval: Original query: "[query]" Documentation/knowledge base topic: [to…
Opening lines · ~61 words in full
Optimize this query for RAG (Retrieval-Augmented Generation) retrieval: Original query: "[query]" Documentation/knowledge base topic: [topic] …
Free with an account
“RAG Query Optimizer” is free — register to read and copy it
This prompt (~61 words) is part of the free set. A free account opens it and keeps what you save. No card.
How to use it
- Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
- Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
- Not sure what it produces? Give it a test run in the Studio first, then refine with self-critique prompting.
Techniques in this prompt
RAG
A rag technique used to shape and strengthen the model's response.
Works with
Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.
New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.