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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

Your Claude application produces good responses for typical inputs but struggles with edge cases. You have several labeled examples of edge-case inputs and the desired response for each. You want to use these examples to improve the model's handling of edge cases.
What is the best way to use these examples?

A. Add the labeled edge-case examples to the prompt as few-shot examples so the model can learn the pattern.
B. Tell users to avoid submitting the edge-case inputs to the application by adding warnings in the application's user interface.
C. Train a custom model on the edge-case examples and deploy that custom model in place of the team's current Claude integration.
D. Embed the examples in a database for the model to find during inference.

Question 2

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

Question 3

Your Claude application's token costs have grown faster than expected. The team has not been tracking token usage by feature, so the team cannot identify which features are driving cost. The team is debating how to respond.
How would you respond?

A. Add token usage tracking by feature to the application's logging so the team can identify which features drive cost before recommending changes.
B. Switch every feature to the smallest model to cut cost broadly across the application during normal operation.
C. Reduce token usage uniformly across all features by half, applying the cut evenly across the application during normal operation.
D. Tell the team that cost growth is unavoidable as the application scales and that no investigation will change the trajectory of the application's cost over the next several quarters.

Question 4

You are designing a Claude application that maintains user sessions across multi-turn conversations. The product team has asked how the application will handle session lifecycle: when sessions should expire, how state is reset, and how the application avoids carrying stale context into new conversations.
How would you design session lifecycle?

A. Define explicit session expiration rules, state reset triggers, and rules for starting fresh sessions so stale context does not leak into new conversations.
B. Define state reset triggers tied to specific application events but apply them across all sessions globally, with no per-session expiration rules.
C. Define explicit session expiration rules but rely on users to start new conversations when they want fresh context, with no automatic reset triggers in the application.
D. Define a single short session timeout that applies across all conversations and treat the timeout as the application's complete session lifecycle mechanism.

Question 5

You are extending a Claude agent with a capability that needs to be reusable across multiple teams in the organization, with each team able to invoke and use it independently.
How would you build the capability?

A. As a wrapper around an existing built-in tool that adds the missing functionality, on the grounds that built-in tools cover the reuse pattern when extended carefully.
B. As a Skill or MCP server because both are purpose-built for cross-team reuse independently by each consuming team.
C. As a shared library that each team imports into its own Claude application code, with each team responsible for keeping the library up to date in its integration.
D. As a custom tool embedded in this team's agent only, with other teams able to copy the implementation into their own agents when they need the capability.

Solutions: