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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. Use the output the model produces and leave schema enforcement to a later phase of production after the application is more complete.
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. Crash on any unexpected output and require manual recovery on affected requests the application handles during normal operation.
D. Apply defensive parsing to handle unexpected fields, missing values, and type mismatches that the downstream code might otherwise crash on.

Question 2

You are setting up Claude Code for a new project repository. Your team has shared coding standards, preferred libraries, and project-specific context that every developer working on the repository should have available when they use Claude Code.
How would you set this up?

A. Add the coding standards and project context to the repository's existing README file and direct developers to reference it when starting Claude Code sessions.
B. Initialize Claude Code in the repository and document the standards and project-specific context in a CLAUDE.md file at the repository root.
C. Configure Claude Code through environment variables that each developer sets on their own machine when they begin working in the repository.
D. Document the standards in a separate wiki page maintained outside the repository so the documentation stays decoupled from the source code.

Question 3

Your Claude application's error handling currently logs every API error with the same severity level. The team wants to differentiate between errors that should page an on-call engineer and errors that should be logged for later review. How would you structure the error handling?

A. Page on every error, on the grounds that paging guarantees that no error is missed by the team during normal operation across the application's lifecycle.
B. Log every error with the same severity, on the grounds that differentiating severity adds complexity that does not pay off in most application setups over time.
C. Disable logging for any error that does not page, treating non-paging errors as not worth recording for later review either.
D. Categorize errors by severity based on impact and recoverability, then route each category to the appropriate channel for paging or logging.

Question 4

You are implementing a custom tool for your Claude agent. The tool needs to interact with an external pricing service that returns product data.
Which of the following best practices would you apply as you develop this tool?

A. Define the tool with a clear schema, write a precise description for when to call it, and handle pricing service errors explicitly.
B. Implement the tool with no error handling and let the agent loop catch failures whenever the pricing service returns an error during operation.
C. Define the tool with a loose schema and let the model interpret the inputs flexibly on each call the agent makes.
D. Omit the tool description and let the model infer when to use the tool based on the tool's name and the rest of the prompt context.

Question 5

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. 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.
C. 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.
D. Remove all tools and rely on the agent's general capability instead, with the application losing the workflows that previously relied on tools.

Solutions: