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You are building a customer support resolution agent using the Claude Agent SDK.

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You are building a customer support resolution agent using the Claude Agent SDK. The agent handles high-ambiguity requests like returns, billing disputes, and account issues. It has access to your backend systems through custom Model Context Protocol (MCP) tools ( get_customer , lookup_order , process_refund , escalate_to_human ). Your target is 80%+ first-contact resolution while knowing when to escalate.

During a billing dispute resolution, your agent successfully retrieves customer info via get_customer and order details via lookup_order , but when attempting to call process_refund , the tool returns a timeout error. The agent has enough information to explain the charges and verify refund eligibility, but cannot actually process the refund due to the backend failure.

What approach best balances first-contact resolution with appropriate error handling?

A.

Implement automatic retries with exponential backoff for process_refund , keeping the conversation open until the refund is successfully processed.

B.

Confirm the refund will be processed and close the conversation, since the system has all necessary information to complete it automatically.

C.

Explain the billing, confirm refund eligibility, acknowledge the system issue preventing immediate processing, and offer escalation or retry later.

D.

Escalate immediately to a human agent since the refund action cannot be completed.

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