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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

Your Claude application uses structured output that is consumed by downstream code. The team wants to handle malformed or unexpected output gracefully so it does not crash downstream systems.
The best choice for handling this issue would be to...

A. Crash on any unexpected output and require manual recovery on affected requests the application handles during normal operation.
B. Silently drop any output that does not match expectations so downstream systems do not see the malformed output the application receives from the model.
C. Apply defensive parsing to handle unexpected fields, missing values, and type mismatches that the downstream code might otherwise crash on.
D. Use the output the model produces and leave schema enforcement to a later phase of production after the application is more complete.

Question 2

Your Claude agent has too many tools, and many of them have overlapping functionality. The agent often picks an inappropriate tool when several could plausibly handle a request.
How would you address the tool selection problem?

A. Restructure the tool set by consolidating overlapping tools, removing unused tools, and clarifying tool descriptions so each tool has a distinct purpose.
B. Remove all tools and rely on the agent's general capability instead, with the application losing the workflows that previously relied on tools.
C. Add more tools to cover every variation of the requests the agent handles, on the grounds that more tools give the agent more accurate options to choose from.
D. Add detailed examples to each tool's description so the agent can match incoming requests to the right tool by example, treating the examples as the team's selection mechanism.

Question 3

You are starting a new Claude application and have a small set of well-labeled examples that demonstrate the desired output format. You want to use these examples to guide Claude's behavior.
How would you guide the application's behavior?

A. Train a custom model on the labeled examples before deployment so that the application does not need to include the examples in any prompt during operation.
B. Use multi-shot prompting by including the labeled examples in the prompt so Claude can match the desired output format on each request.
C. Embed the examples in a database and retrieve them at runtime as reference material for the team.
D. Use zero-shot prompting and rely on the model's general capability to produce the desired output format consistently across all incoming requests.

Question 4

You are designing an agent that handles a multi-step research task. You want the agent to break the task into smaller pieces, hand each piece to a focused subagent, and consolidate the results.
The agent pattern you would apply is...

A. A single tool-use loop that includes every tool the agent might need across all subtasks.
B. A memory pattern that stores the entire research history in advance, before any subtask begins execution.
C. A context-window pruning pattern that drops each subtask's content after the agent moves on.
D. An orchestrator and subagent pattern with specialized subagents assigned to each subtask.

Question 5

A Claude application is occasionally refusing to answer questions that should be in scope, including questions the application has answered correctly in the past. You want to investigate.
What is the first step of your investigation?

A. Identify which questions have been refused and compare them against previously answered questions to determine what changed between the successful and refused interactions.
B. Assess whether the refusals cluster around specific input patterns, question types, or time periods by analyzing the distribution of refused requests in the logs.
C. Examine traces of the refused requests to identify what triggers the refusal, whether input patterns, system prompt content, or other context.
D. Test whether removing or adjusting those instructions resolves the behavior.

Solutions: