Anthropic CCDV-F Exam Questions : Claude Certified Developer-Foundations

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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

You are choosing a Claude model for a high-volume classification task. Each classification is straightforward, latency requirements are tight, and per-request cost matters at scale.
Which model would you choose?

A. Multiple Claude models in series, where each request runs through more than one model and the application combines the outputs into a final classification.
B. The largest, highest-capability Claude model, to maximize quality on every classification the application produces during normal operation across all requests.
C. A smaller, faster Claude model, because the task is straightforward and the workload prioritizes latency and per-request cost at scale.
D. A mid-tier Claude model selected by default, because mid-tier models balance quality and cost in a way the team can apply across most tasks.

Question 2

Your Claude application's content policy specifies categories of content it should not produce under any circumstance. The application currently has no mechanism to enforce this policy, and content matching these categories is appearing in the application's output.
How would you enforce the content policy?

A. Add deterministic output filtering that checks responses against the content policy before they reach users.
B. Enhance the system prompt to contain explicit instructions for the categories to avoid, complete with examples of each category. Treat the strengthened prompt as the primary enforcement mechanism for the application's content policy across all responses.
C. Move enforcement to users by asking them to report content policy violations after the violating content has already reached them in the application's responses.
D. Remove the content policy entirely and let any output reach users during normal operation, accepting whatever content the application produces in response to incoming traffic.

Question 3

Your team is preparing a new Claude application for production, and the product team has asked for a cost projection. The team needs to estimate the cost based on expected request volume, average input length, and average output length. How would you build the projection?

A. Build a cost model that combines expected request volume, average input tokens, average output tokens, the chosen model's pricing, and any caching benefits.
B. Build a cost model that combines expected request volume and average input tokens, treating output tokens as a small enough share of cost to leave out of the projection.
C. Build a cost model that uses the average per-request cost from a similar Claude application the team built last year, scaling that figure by expected request volume.
D. Build a cost model based on expected request volume and the chosen model's pricing, treating average input and output token counts as variables to be estimated post-launch.

Question 4

The product team has asked you to choose a Claude model for a new feature. The team has provided functional requirements but has not specified performance, cost, or quality targets. The team's product manager says, "Use whatever model gives us the best results." How would you respond?

A. Choose the largest, highest-capability Claude model, on the grounds that "best results" is most likely to mean highest quality.
B. Run every Claude model on a representative sample and pick whichever scores best on a generic benchmark.
C. Ask the product team to specify quality, latency, and cost targets, then select the model whose tradeoffs best fit those targets.
D. Choose a mid-tier model and ship the feature, because mid-tier models work for most use cases without specified targets.

Question 5

A teammate has asked you to explain why your Claude agent's tools include detailed descriptions in the tool definition, even when the tool name is already descriptive. The teammate suggests removing the descriptions to simplify the tool definitions.
How would you respond?

A. Agree with the teammate because tool names are sufficient for the model to choose the right tool on every request the agent handles.
B. Suggest replacing the descriptions with example calls embedded in the tool definition, treating example calls as a complete substitute for the prose description.
C. Suggest moving the descriptions out of the tool definition and into a separate documentation file the team maintains so the tool definitions stay short and the descriptions remain available.
D. Explain that the model uses the tool description to decide when to call the tool, and descriptions disambiguate cases where the tool name is not enough.

Solutions: