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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect - Foundations Sample Questions:

Question 1

Your test-generation process produces unit tests for new code, but reviews show that 55% are low-value: trivial assertions that verify only that functions do not throw exceptions, tests that duplicate existing coverage, or tests that ignore your team's fixture conventions. How should you reduce the rate of low-value tests being generated in the first place?

A. Implement two-phase generation in which a second Claude call scores every test against quality criteria and filters out low-scoring tests before presenting them to developers.
B. Add post-generation coverage analysis that automatically filters out every generated test that does not increase line coverage beyond the existing test suite.
C. Document your testing standards in CLAUDE.md, including valuable-test criteria, available fixtures and their intended uses, and examples distinguishing meaningful behavioural tests from trivial assertions.
D. Restrict test generation to directories where historical quality metrics show higher acceptance rates, disabling it in areas where generated tests consistently require substantial editing.

Question 2

You are building a multi-agent research system using the Claude Agent SDK. A coordinator agent delegates to specialized subagents: one searches the web, one analyzes documents, one synthesizes findings, and one generates reports. The system researches topics and produces comprehensive, cited reports.
Production reviews reveal inconsistent handling of uncertainty in final reports. Sometimes conflicting subagent findings are synthesized into a single confident statement, losing important nuance, while other reports use excessive qualifications and become unhelpful. The web-search agent returns, "Industry analysts estimate a $50 billion market size, although methodologies vary." The document- analysis agent returns, "A peer-reviewed study estimates $35 billion, with a ?7 billion 95% confidence interval." The coordinator either selects one estimate arbitrarily or produces a vague $35?50 billion range.
What systematic approach best addresses this?

A. Add a verification subagent that passes claims to synthesis only when they are corroborated by at least two independent sources.
B. Configure subagents to report only findings meeting a high-confidence threshold, filtering uncertain information before it reaches the coordinator.
C. Implement a confidence-calibration layer that normalizes subagent uncertainty expressions to probability scores between 0.0 and 1.0, and then calculate a confidence-weighted average.
D. Instruct the synthesis agent to distinguish well-established findings from contested findings explicitly, preserving each source's original uncertainty, methodology, and supporting evidence.

Question 3

The coordinator provides detailed step-by-step instructions to the web-search subagent, specifying exact search queries, source priorities, and date filters. Production monitoring reveals three issues:
(1) the subagent reports "insufficient results" instead of trying
alternative approaches when the specified searches fail,
(2) research quality drops for emerging topics that do not match
expected patterns, and
(3) the subagent rarely surfaces valuable tangential sources.
What is the most effective way to improve subagent adaptability?

A. Specify research objectives and quality criteria--such as coverage breadth, source diversity, and recency--rather than prescribing procedural steps, allowing the subagent to determine its search strategy.
B. Classify each topic as either "well-defined" or "exploratory" and use a different instruction style for each category.
C. Add fallback directives requiring alternative query formulations whenever the specified searches produce fewer than a predetermined number of results.
D. Remove procedural details entirely and delegate using simple goals such as "research this topic thoroughly," relying on the subagent's general capabilities.

Question 4

Your post_content tool requires user confirmation before publishing. The current workflow displays "Ready to post to social media. Confirm?" and analytics show users approve 98% of requests within 2 seconds. Post-mortems reveal incidents where posts went to wrong accounts, were scheduled for wrong times, or contained errors - all confirmed by users without catching the mistakes. How should you redesign the confirmation workflow?

A. Require users to type a confirmation phrase instead of clicking a button
B. Include the complete post text, target account, scheduled time, and platform in the confirmation request
C. Add a mandatory waiting period before the confirm option becomes available
D. Auto-approve routine posts and only require explicit confirmation for unusual patterns like posting to new accounts or large audiences

Question 5

Your MCP server includes archive_file(file_id) and delete_file(file_id) tools. Production logs show the agent calls delete_file when users ask to "remove old backups," but company policy requires archiving backup files. Both tools currently have minimal descriptions: "Archives a file" and
"Deletes a file." Which change most directly improves tool selection for this scenario?

A. Add a confirmation step that requires users to type "CONFIRM DELETE" before delete_file executes.
B. Implement server-side validation that rejects delete_file calls for files tagged as backups, returning an error message suggesting archive_file.
C. Expand tool descriptions to clarify use cases, adding guidance like "Do not use for backup files" to delete_file.
D. Add few-shot examples to the system prompt demonstrating that requests involving "backup" or
"old" should use archive_file.

Solutions: