Make the structure legible
Prefer table, collection, and field names that describe the data rather than internal shorthand. Keep related values consistent: dates should use a predictable representation, status fields should have a known set of values, and identifiers should have a clear purpose. A readable structure reduces ambiguity when a request refers to a business concept.
Avoid placing unrelated concepts in one overloaded field when you expect the agent to filter or compare records. If a field contains multiple meanings, document how they are represented or separate them into clearer fields before relying on automated questions.
Give the query its business context
In the request, explain what terms such as active, qualified, or overdue mean in your organization. A schema can show that a field exists, but it cannot infer every policy behind its values. Include the date range, grouping, and result format when those choices matter to the answer.
Review a sample result before using it to make a decision. Check that the selected fields and filters match the question, especially when similar columns or collections exist. If the result is off, refine the definitions or the request instead of assuming that the database structure explains the business rule by itself.