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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect - Foundations Sample Questions:

Question 1

You built an LLM-powered code-review tool that analyzes pull requests and returns structured findings. Each finding is a JSON object containing file_path, line_number, issue_category--such as security or style--and description. Developers can dismiss findings they consider unhelpful, and currently 35% of findings are dismissed. You want to analyze these dismissals to understand what the system is getting wrong and improve the prompts accordingly. What change to the output structure would best support this analysis?

A. Expand the description field with more detailed explanations of why each issue matters and how it should be fixed.
B. Add a model_confidence field from 0.0 to 1.0 and filter findings below a threshold calibrated against historical dismissal rates.
C. Add a detected_pattern field recording the specific code construct that triggered the finding, such as single-letter loop variable.
D. Remove the issue_category field and track dismissal rates only at the individual-finding level.

Question 2

The coordinator agent has AgentDefinition objects configured for all four specialized subagents, each with appropriate descriptions, prompts, and tool restrictions. During testing, you notice that the coordinator correctly reasons about when to delegate--it generates messages such as, "I'll ask the web-search agent to find sources on this topic"--but no subagent execution occurs. The coordinator then proceeds as if the delegation happened and continues with incomplete information. Logs show no errors. What is the most likely cause?

A. The coordinator's max_tokens setting is too low, causing the subagent invocation to be truncated before the agent-type parameter is specified.
B. The coordinator's allowedTools configuration does not include "Agent"--called "Task" in older SDK releases--so it cannot invoke the tool required to spawn subagents.
C. Subagent context isolation prevents task descriptions from reaching subagents unless explicit context forwarding is configured in ClaudeAgentOptions.
D. The AgentDefinition objects are configured correctly, but the coordinator's system prompt does not explicitly list the available subagent types.

Question 3

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. Structured JSON consumes significantly fewer tokens than natural language, substantially reducing API costs.
B. JSON schemas automatically validate that the underlying API returned correct data before the agent processes it.
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 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. Auto-approve routine posts and only require explicit confirmation for unusual patterns like posting to new accounts or large audiences
B. Add a mandatory waiting period before the confirm option becomes available
C. Require users to type a confirmation phrase instead of clicking a button
D. Include the complete post text, target account, scheduled time, and platform in the confirmation request

Question 5

You are using Claude Code to accelerate software development. Your team uses it for code generation, refactoring, debugging, and documentation. You need to integrate it into your development workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.
You've asked Claude Code to build a PDF report generation feature. The initial implementation queries the database correctly, but the output has formatting issues: table columns are too narrow causing content truncation, dates display without proper formatting, and page break handling is incorrect. You've noticed these issues interact--changing column widths affects how dates render, and page breaks depend on content height.
What's the most effective approach for iterating toward a working solution?

A. Provide all three issues in a single detailed message with exact specifications for each, allowing Claude to address them together in one update.
B. Show Claude an example of a correctly formatted report and ask it to match that output, rather than listing the specific technical issues.
C. Start fresh with a detailed prompt specifying all formatting requirements upfront.
D. Address the column width issue first with specific measurements, verify it works, then fix date formatting within the corrected columns, then adjust page breaks--testing after each change.

Solutions: