How would you build or rewrite a retrieval query for RAG?

Transforms conversational requests into bounded search inputs while preserving user intent, constraints, and traceability.

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TL;DR

I turn the user's request into a standalone search query that preserves the subject, constraints, and important conversation references. I remove conversational filler but do not invent facts or access filters. For complex questions, I may issue several focused queries and merge their results rather than forcing every concept into one embedding.

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Practice focus

Query understanding, conversation context, decomposition, and protection against invented filters.

Answer first

Answer path

Core answer first, then checkpoints toward a stronger answer.

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Core answer
Start here. This is the direct spoken answer to practice first.
Overview
The best generation prompt cannot recover evidence that an ambiguous retrieval query never found.
I turn the user's request into a standalone search query that preserves the subject, constraints, and important conversation references. I remove conversational filler but do not invent facts or access filters. For complex questions, I may issue several focused queries and merge their results rather than forcing every concept into one embedding.
Checkpoint
Stronger answer
Optional upgrade with examples, trade-offs, and sharper phrasing.
If the user asks whether that policy still applies in Germany, the rewriter needs the policy named earlier plus the country and current-time constraint. I log the original and rewritten query with sensitive values protected, then evaluate whether rewriting improves retrieval on representative conversations. A poor rewrite can narrow away the correct evidence, so the original query remains available as another retrieval signal.

Review signals

Use these to catch weak phrasing, shallow reasoning, and risky claims.

Common mistakesCandidateCommon mistakesMistakes that weaken the answer or signal shallow understanding.Open details

Details

Embedding the entire chat transcript as the search query.
Allowing a model to invent unrestricted metadata filters.
Replacing the original query without evaluation.

How would you build or rewrite a retrieval query for RAG?

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Overview

Review signals

Follow-up prompts

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