Question

You are building a Mosaic AI agent that has access to three registered Unity Catalog functions: `get_order_status`, `lookup_product_inventory`, and `search_return_policy`. During testing, you notice the LLM frequently calls `search_return_policy` even when users ask about where their package is. The tool bindings and endpoint work correctly, and each function executes without error when called directly. What is the most effective change to improve the agent's tool selection accuracy?

Accepted Answer

Write clear, distinct docstrings and parameter descriptions for each function so the LLM can accurately match user intent to the correct tool

Answer

Reduce the temperature of the foundation model endpoint to 0 to make tool calls deterministic

Answer

Increase the agent's maximum iteration limit so it has more chances to call the right tool

Answer

Switch the endpoint from a pay-per-token model to provisioned throughput for more consistent responses