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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect - Foundations Sample Questions:

Question 1

When implementing your lookup_order MCP tool, the backend sometimes returns errors (e.g.,
"Order not found" or temporary database failures). What is the correct pattern for communicating these errors back to the agent?

A. Log the error server-side and return an empty result to avoid confusing the model
B. Return the error message in the tool result content with the isError flag set to true
C. Return a success response with a "status" field indicating the error type
D. Throw an exception from the tool handler so the agent framework can catch and log it

Question 2

You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. The system runs automated code reviews, generates test cases, and provides feedback on pull requests. You need to design prompts that provide actionable feedback and minimize false positives.
Your automated code review is missing genuine bugs in pull requests. Investigation reveals that your review prompt includes the instruction: "Only flag critical issues that would definitely cause production failures. Ignore minor concerns and anything you are uncertain about." Developers confirm that some missed bugs are genuine logic errors that the model investigated but chose not to report. The team requires the review output to remain structured, with each finding tagged with metadata, and actionable.
Which prompt change both removes the cause of the suppressed findings and preserves structured, tagged output for downstream filtering?

A. Remove all severity-related instructions from the prompt and let the model use its default judgment about what to report.
B. Instruct the model to report all findings with confidence and severity tags, deferring filtering to a downstream step.
C. Add a second review pass that rereads the diff using the same prompt, looking for anything the first pass may have missed.
D. Enable extended thinking and instruct the model to reason step by step about every code change before producing its review.

Question 3

The web search agent has gathered several relevant sources for a research topic. The document analysis agent now needs to examine these sources. How does information typically flow between these two specialized subagents?

A. The web search agent directly invokes the document analysis agent, passing the discovered sources as parameters.
B. The agents communicate through an event-driven message queue, with the document analysis agent subscribing to web search completion events.
C. The coordinator agent receives the web search agent's output and includes relevant findings in the prompt when invoking the document analysis agent.
D. Both agents access a shared memory store where the web search agent writes findings and the document analysis agent reads them.

Question 4

A chatbot frequently receives greetings, policy questions, and technical support requests. Which architecture improves maintainability?

A. Maximum temperature.
B. Disable retrieval.
C. Prompt routing based on request type.
D. One prompt for every scenario.

Question 5

You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with Model Context Protocol (MCP) servers.
An engineer asks your agent to add comprehensive tests to a legacy codebase with 200 files and minimal existing test coverage. The engineer hasn't specified which modules to prioritize.
How should the agent decompose this open-ended task?

A. Use Glob and Grep to map codebase structure, identify heavily-coupled modules, create a prioritized plan for high-impact areas, and revise as dependencies are discovered.
B. Systematically read all 200 files to create a complete function inventory before writing any tests, ensuring the testing plan accounts for every function before beginning.
C. Create a fixed testing schedule upfront based on directory structure, allocating equal effort to each top-level directory regardless of code complexity or business importance.
D. Start writing tests for the first module alphabetically, using test failures and imports to discover related files organically.

Solutions: