Anthropic Claude Certified Architect - Foundations : CCAR-F

Your send_notification tool calls third-party messaging APIs. When these services time out during delivery, you cannot determine whether the message was actually sent. Currently, the tool returns is_error: true with a generic "Notification failed" message for all timeouts. Production monitoring reveals agents automatically retry these failures, frequently causing users to receive duplicate notifications. How should you modify the error response?

• A. Return is_error: true with a message encouraging retry: "Delivery service temporarily unavailable.
  Please retry the notification."
• B. Return is_error: true with the original message content echoed back.
• C. Return is_error: true with a structured field retry_safe: true for timeouts, distinguishing them from permanent failures that should not be retried.
• D. Return is_error: true with a message communicating uncertainty: "Timeout - status unknown.
  Message may have been sent. Avoid retry."

You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with Model Context Protocol (MCP) servers.
An engineer used the agent yesterday to analyze a legacy authentication module, identifying two distinct refactoring approaches: extracting a microservice versus refactoring in-place. Today, they want to explore both approaches in depth - having the agent propose specific code changes for each - before deciding which to implement. What's the most effective way to structure this exploration?

• A. Resume yesterday's session and explore both approaches sequentially within the same conversation thread.
• B. Use fork_session to create two branches from yesterday's analysis, exploring one approach in each fork.
• C. Start two fresh sessions, manually providing a summary of yesterday's analysis findings to establish context.
• D. Resume yesterday's session to explore the first approach, then start a new session for the second, manually recreating the original context.

You're implementing the escalation logic for when the agent should call escalate_to_human. Your team proposes four different approaches for triggering escalation. Which approach will most reliably identify cases that genuinely require human intervention?

• A. Implement sentiment analysis that monitors for frustration indicators (negative language, repeated questions, exclamation marks) and trigger escalation when the frustration score exceeds a configured threshold.
• B. Instruct the agent to escalate when the customer requests a human, when the issue requires policy exceptions, or when the agent cannot make meaningful progress.
• C. Build a rules engine that maps specific issue types, customer segments, and product categories to escalation decisions, removing the need for model judgment calls.
• D. Configure the agent to escalate after three consecutive tool calls that fail to resolve the customer's stated issue, ensuring a reasonable attempt before involving a human.

The agent verifies customer identity through a multi-step process before resetting passwords.
During testing, you notice that after the customer answers the third verification question, the agent asks them to provide their name again, as if the earlier exchange never happened. What's the most likely cause of this behavior?

• A. The prompt lacks instructions telling Claude to remember information across multiple exchanges.
• B. Claude's memory retention is limited to two conversational turns by default, requiring explicit configuration to extend it.
• C. The conversation history isn't being passed in subsequent API requests.
• D. The verification tool is clearing the agent's internal state after each successful validation step.

Your update_user_profile tool accepts a user_id (required) and an optional fields_to_update object. In testing, Claude frequently omits user_id or passes incorrectly structured data. What is most critical for helping Claude understand what parameter values to provide?

• A. Verbose parameter names encoding format hints, such as user_id_string_uuid_format
• B. Clear parameter descriptions explaining expected format, such as "user_id: UUID of the user to update (required)"
• C. Strict JSON Schema type constraints marking user_id as required and defining fields_to_update as an object type
• D. Detailed error responses explaining why invalid parameter values were rejected