Anthropic CCAR-F : Claude Certified Architect - Foundations

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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect - Foundations Sample Questions:

Question 1

Your get_portfolio_value tool returns the total value of a user's investment portfolio. You're deciding between returning a structured JSON object with explicit fields versus returning the information as a formatted text string. What is the primary advantage of using structured output with defined fields?

A. JSON schemas automatically validate that the underlying API returned correct data before the agent processes it.
B. Structured JSON consumes significantly fewer tokens than natural language, substantially reducing API costs.
C. Structured JSON is processed deterministically by the model, significantly improving accuracy when extracting values.
D. The agent can reliably extract specific values without parsing free-form text, reducing errors in subsequent operations.

Question 2

You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JavaScript Object Notation (JSON) schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.
Your extraction pipeline validates outputs against JSON schemas, but you need to implement human review given limited reviewer capacity (they can handle approximately 5% of total extraction volume).
What's the most effective basis for selecting which extractions to route for human review?

A. Route extractions containing specific high-priority entity types (e.g., financial figures, dates) for human review, regardless of extraction confidence.
B. Randomly sample 5% of extractions for review.
C. Route extractions for review only when downstream systems report data quality issues or processing failures.
D. Route extractions where the model indicates low confidence or where source documents contain ambiguous or contradictory information.

Question 3

A developer wants Claude to explain every reasoning step internally before answering. Why might this request be inappropriate?

A. Internal reasoning should not be relied upon as an application feature.
B. JSON cannot contain reasoning.
C. Temperature prevents explanations.
D. Claude requires GPU acceleration.

Question 4

What is the PRIMARY purpose of few-shot prompting?

A. Increase model size.
B. Demonstrate desired output patterns.
C. Reduce token costs.
D. Encrypt prompts.

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, and Glob--and integrates with Model Context Protocol (MCP) servers.
You are building a security-scanning workflow.
When engineers need to locate every occurrence of a dangerous function such as eval() across a large codebase, which tool should the agent use for content searching?

A. Use Grep to search for the regular-expression pattern eval\( across all files in the codebase.
B. Use Bash to run ls -R | grep eval and search the recursively listed filenames.
C. Use Glob with a pattern such as **/eval* to locate files, and then read each matching file.
D. Read the project's main entry file and follow import statements to trace where eval() might be used.

Solutions: