With tools like this, you basically assume the LLM doesn't know, and teach it to always defer to a tool, so its response is basically summarization over the tool output.
That's right. If you want to ask questions about "general public knowledge", a plain LLM will know anyway and would not need tools. However, for many use cases you need data from your private CRM / a SQL db / a private wiki / or your obversability platform. Agents allow to "query" those tools/APIs to get the needed information so that they can answer the question. It's a matter of composition in your architecture. The "monolith LLM" works well for a certain spectrum of tasks, but at some point you want to decouple responsibilities into individual services / tools. Simplifies debugging, explainability, maintenance ...