So? What alternative do you suggest? Let the LLM get it wrong forever? Remove the tool? Automatically try to patch the syntax?
Almost no "solutions" in engineering/programming comes for free, one way or another, it's all a balancing act between different solutions with different tradeoffs. In this case, another request/response seems preferable to the other tradeoffs.
The counter intuitive pattern I see emerging is if you can cleanly determine intent, of the call you fix the call and prepend informative text to the tool call response indicating the mistake made and how to fix in the future then followed by the actual tool call. In this case you can validate fields and rather than throw a hard error determine if it's an extra field that isn't needed. If so you correct the call and prepend a corrective response in the tool call. This saves turns, it instructs the model in context so less likely to happen later and helps models that aren't so good at recovering from bad tool calls and staying on their longer horizon agentic task (most non openai and anthropic models)