How does GitHub Copilot in SSMS 22 handle database context collection before generating a response?

Hello,

I am trying to better understand the internal workflow of GitHub Copilot in SSMS 22, especially for database-specific questions.

From the product descriptions, it seems that Copilot can use the context of the currently connected database, such as schema, tables, columns, and possibly other metadata, when answering questions or generating T-SQL.

However, I could not find clear official documentation about the actual sequence of operations.

My main questions are:

1. Before generating a response, does Copilot first collect database context/metadata from the active connection and then send that context to the LLM as grounding information?
2. Or does it first use the LLM to interpret the user’s request, decide what information is needed, and then retrieve database metadata before generating the final answer?
3. In some explanations, I have seen the phrase "Core SQL Copilot Infrastructure", but I cannot find any official documentation for that term.
   • Is this an official component name?
   • If so, what does it specifically refer to in the SSMS Copilot architecture?
4. When Copilot answers schema-related or data-related questions, what information is retrieved automatically from the connected database, and is any SQL executed as part of that process?
5. Is there any official architectural documentation that explains:
   • context collection,
   • prompt grounding,
   • LLM invocation order,
   • and whether query execution can occur before the final response is generated?

I am asking because I want to understand the feature from both an architecture and data governance/security perspective.

Any clarification from the product team or documentation links would be greatly appreciated.

Thank you.