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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

You are choosing between using STDIO-based communication and HTTP-based communication for an MCP server. The server will be invoked by a Claude Code session running locally.
Which communication pattern would you use?

A. HTTP polling against the MCP server, treating HTTP as a substitute for the standard MCP communication patterns.
B. STDIO and HTTP simultaneously for redundancy, with the team running two communication patterns at the same time across Claude Code sessions.
C. HTTP on the grounds that HTTP is preferable to STDIO in any context the application might encounter during normal operation.
D. STDIO because STDIO is well-suited to local process communication and avoids unnecessary network setup.

Question 2

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

Question 3

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. 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.
B. 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.
C. Suggest replacing the descriptions with example calls embedded in the tool definition, treating example calls as a complete substitute for the prose description.
D. Agree with the teammate because tool names are sufficient for the model to choose the right tool on every request the agent handles.

Question 4

Your enterprise has a contract with AWS that requires Claude API calls to flow through Amazon Bedrock rather than the direct Anthropic API. Your team is building a new Claude application and is unfamiliar with this constraint.
How would you build the application?

A. Build two parallel implementations of every call, one for the direct Anthropic API and one for Bedrock, and pick the faster one at runtime.
B. Build the application against the direct Anthropic API and ignore the contractual requirement to route Claude calls through Amazon Bedrock.
C. Configure the application to invoke Claude through the Bedrock-compatible API path while keeping the application's logic provider-agnostic.
D. Build the application against the direct Anthropic API now and migrate to Bedrock in a follow-up release once the team has more experience with the Bedrock API.

Question 5

Your Claude application is hitting context window limits when processing long customer service transcripts.
A junior developer suggests increasing the temperature parameter to fix the issue.
How would you respond?

A. Explain that temperature controls sampling randomness and is unrelated to context capacity, then address the context issue through summarization or chunking.
B. Increase the temperature parameter as the junior developer suggested and observe whether the context window issue resolves over the next several runs of the application in production.
C. Remove the system prompt entirely to make room for longer transcripts in each request, freeing up context window space the system prompt would otherwise consume.
D. Adjust the temperature parameter together with the max_tokens parameter, treating the combined adjustment as the team's mechanism for managing context window pressure during long-transcript processing.

Solutions: