After the web search agent and document analysis agent complete their tasks, the coordinator invokes the synthesis agent. However, the synthesis agent responds that it cannot complete the task because no research findings were provided. What is the most likely cause of this issue?

• A. The synthesis agent's context window is not large enough to hold the combined outputs from both previous agents.
• B. The synthesis agent needs tools that can fetch results directly from the other agents' conversation histories.
• C. The coordinator did not include the outputs from the previous agents in the synthesis agent's prompt.
• D. The subagents need to share a single API connection to enable automatic context sharing between invocations.

An enterprise wants Claude responses to remain professional across every interaction. Where should tone instructions primarily reside?

• A. API key description
• B. System prompt
• C. User prompt only
• D. Retrieved documents

Your track_shipment(tracking_id) tool queries an external logistics API that sometimes fails - the API may be temporarily unavailable, the tracking ID may be malformed, or the shipment may not exist. Currently, your tool raises a Python exception when errors occur. Users report the agent gives unhelpful responses like "I'm having trouble with that request" instead of suggesting alternatives such as verifying the tracking number format or checking by order number. How should you handle errors in tool results?

• A. Return a generic error response (e.g., {"success": false, "error": "lookup_failed"}) for all failure cases to maintain a consistent schema and avoid exposing internal error details.
• B. Create dedicated error-recovery tools (retry_tracking_lookup, search_by_order_number) that the model can invoke after the primary tracking tool returns a failure indicator.
• C. Return structured error information as normal tool output including error type, recoverability status, and actionable context for the user.
• D. Implement retry logic with exponential backoff inside the tool implementation so transient errors are automatically handled and only return a result after all retry attempts are exhausted.

Your agent is handling a billing dispute. After calling get_customer and lookup_order, it identifies that the dispute involves a promotional pricing error requiring manager approval - beyond the agent's authorization level. How should the workflow handle this mid-process escalation?

• A. Call escalate_to_human passing only the customer's original message.
• B. Persist the complete conversation and tool response history to a database, then call escalate_to_human with a reference ID.
• C. Compile a structured handoff with customer details, order info, and the identified issue before calling escalate_to_human.
• D. Attempt the refund with process_refund anyway, escalating only if the system rejects the transaction.

You've configured the system so that all four subagents have access to the complete set of
18 tools. During testing, agents frequently call tools outside their specialization - the synthesis agent attempts web searches, and the report generator tries to analyze documents. What is the primary cause of this poor tool selection behavior?

• A. The tool definitions consume too much context window space, leaving insufficient room for task content.
• B. The coordinator cannot track which capabilities each subagent has, leading to misrouted tasks.
• C. Choosing from 18 tools instead of 4-5 relevant ones increases decision complexity beyond reliable selection thresholds.
• D. The agents' role descriptions in their system prompts conflict with having access to tools outside that role.