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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

You are designing an agent that processes vendor invoices. The work involves a small number of well- understood steps, but occasionally an invoice arrives in an unexpected format that requires the system to decide between rerouting, requesting clarification, or flagging for human review.
The most appropriate architecture for this system is...

A. A fully autonomous agent that handles every invoice from start to finish across all formats.
B. A manager agent that delegates each step of standard invoice processing to a dedicated subagent, with a separate subagent handling each unexpected format.
C. A workflow for the standard path with an agent invoked at the decision point for unexpected formats.
D. A single large prompt that processes every incoming invoice, both standard and unexpected, in one model call.

Question 2

You are building a Claude application that needs to maintain a persistent connection to a service that streams real-time updates. The team is unsure what communication pattern to use.
Which communication pattern would you use?

A. Repeated short-lived HTTP polling requests, where the application opens a new HTTP connection each time it checks for updates.
B. A WebSocket, because WebSockets are designed for bidirectional, persistent, real-time communication between the client and the streaming service.
C. File-based communication where the service writes new updates to disk and the application polls the file system for changes.
D. A single long HTTP request the server holds open indefinitely, with no standard WebSocket framing on the connection.

Question 3

Your team is integrating Claude into an existing REST API service. The service handles concurrent requests, and you are deciding how to structure the Claude API calls within the existing async codebase.
How would you structure the Claude calls?

A. Run Claude API calls in a separate thread pool isolated from the rest of the service so the main event loop is not affected.
B. Use the Claude SDK's async client and structure Claude calls as awaitable operations alongside the rest of the service's async code.
C. Make synchronous Claude API calls and block the async event loop until each call completes before processing the next request.
D. Replace the existing async REST service with a synchronous service to match the call style of synchronous Claude SDK clients.

Question 4

Your Claude application uses tool calling to fetch patient data and generate summary reports. The flow occasionally fails because the model returns a tool_use block that references arguments not present in the schema, and your application code does not handle this case gracefully.
How would you address this?

A. Log invalid tool_use blocks when they occur and allow the tool dispatch to proceed, relying on the tool's own error handling to surface failures back to the application.
B. Stop using tool calling entirely and replace tools with prompted text generation that asks the model to describe what it would do.
C. Retry the same request repeatedly until the model returns a valid tool_use block that matches the schema as expected.
D. Validate the tool_use block's arguments against the tool schema before dispatching the tool and handle invalid arguments as a recognized error path.

Question 5

Your Claude application is producing inconsistent outputs for similar inputs, even when using the same model and prompt. You want to debug the issue systematically.
Your debugging approach would...

A. Lower the model's temperature and re-run the inconsistent inputs to determine whether the parameter change reduces output variability across runs.
B. Retry every request that produces an unexpected output and log the results to identify whether repeated calls converge on a consistent response pattern.
C. Assume inconsistent outputs reflect normal LLM non-determinism and document the variability as an accepted characteristic of the application's behavior.
D. Capture full traces of input, system prompt, user messages, model output, and parameters, then analyze the differences between consistent and inconsistent runs.

Solutions: