Question

You are building a Mosaic AI agent that calls an external inventory API tool to answer customer stock-availability questions. During testing, the API intermittently returns timeouts and malformed responses, causing the agent to either crash or return the raw error text to the user. You need to make the agent robust while keeping responses helpful. Which approach best addresses this within the agent's tool-execution logic?

Accepted Answer

Wrap the tool call with retry-with-backoff logic and a fallback that returns a structured, user-friendly message the LLM can incorporate when the tool ultimately fails

Answer

Increase the foundation model's max_tokens so the LLM can absorb and rewrite the raw API error text before responding

Answer

Remove the inventory tool from the agent and instead embed all stock data into the system prompt so no external call is needed

Answer

Lower the model temperature to 0 so the agent stops producing inconsistent responses when the API fails