⚠️ 5. Interactive Clarification When Needed

If any part of the user request is ambiguous, incomplete, or invalid, the LLM-powered system can detect the issue and prompt the user for clarification.

Example:

“Make me a token.”

→ Bot:

“Sure! What would you like to name your token? Do you have a symbol in mind and a total supply?”

This improves the experience for non-technical users who may not provide complete input.