Agreed. When I watch the llm start to explore the db - it really does impress me.
Can you expand on this:
You can even incrementalize the schema description process itself by way of the system tables. Intentionally not providing a schema description tool/document/prompt seems to perform better with the latest models than the other way around.
If you tell GPT5.x that there is a database it can query by calling ExecuteSql(query), but you don't bother explaining anything about the schema, it will try to figure things out ad-hoc. This has advantages for token budget because it will tend to only lookup the metadata for tables that seem relevant to the user's query.
If you have a gigantic data warehouse with 1000+ tables, there's no way you could fit all of that info into a system prompt without completely jacking something up in the blackbox. So, why bother trying?
Consider that the user's specific request serves as an additional constraint that can be used to your advantage to dramatically reduce the search space. Building a single prompt / schema description that will magically work for all potential user requests is a cursed mission by comparison.