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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect – Foundations Sample Questions:

1. You are building a customer support resolution agent using the Claude Agent SDK. The agent handles high- ambiguity requests like returns, billing disputes, and account issues. It has access to your backend systems through custom Model Context Protocol (MCP) tools ( get_customer , lookup_order , process_refund , escalate_to_human ). Your target is 80%+ first-contact resolution while knowing when to escalate.
Your process_refund tool returns two types of errors: technical errors ("503 Service Unavailable",
"Connection timeout") that are transient (~5% of calls), and business errors ("Order exceeds 30-day return window", "Item already refunded") that are permanent (~12% of calls). Monitoring shows the agent wastes 3-
4 turns retrying business errors that can never succeed. Currently, both error types return only a plain text message to Claude.
What's the most effective way to reduce wasted retries while improving customer-facing response quality?

A) Return structured error responses with "retriable": false for business errors and a customer-friendly explanation for Claude to use.
B) Implement automatic retry logic at the tool layer for technical errors only, passing business errors to Claude without retries.
C) Add few-shot examples showing how to distinguish retriable from non-retriable errors by parsing error message text.
D) Add a check_refund_eligibility tool that must be called before process_refund to prevent business rule violations.

2. 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're tasked with adding real-time updates to the application. This could be implemented using WebSockets, Server-Sent Events, or polling, each with different complexity, browser support, and infrastructure requirements.
What's the most effective way to begin this task?

A) Start direct execution with WebSockets, then refactor if infrastructure issues arise.
B) Use direct execution to implement polling first, then evaluate whether to upgrade to WebSockets later.
C) Use direct execution with a prompt asking Claude to analyze all approaches and implement the one it determines is best.
D) Enter plan mode to explore the architecture, evaluate trade-offs, and present options for team approval before implementing.

3. 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.
Your agent has analyzed a complex service module-reading 23 source files, tracing request flows, and identifying error handling patterns. A developer wants to compare two testing strategies before committing to one: end-to-end tests with mocked external services vs. snapshot tests capturing expected outputs. They need to independently develop both approaches to evaluate trade-offs.
How should you manage the sessions?

A) Continue in the original session, developing end-to-end tests first, then snapshot tests sequentially.
B) Export the analysis session's key findings to a file, then create two new sessions that reference this file.
C) Resume the analysis session with fork_session enabled, creating a separate branch for each testing strategy.
D) Start two fresh sessions, having each re-read the relevant source files before beginning.

4. 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) Route extractions for review only when downstream systems report data quality issues or processing failures.
C) Randomly sample 5% of extractions for review.
D) Route extractions where the model indicates low confidence or where source documents contain ambiguous or contradictory information.

5. You are building a customer support resolution agent using the Claude Agent SDK. The agent handles high- ambiguity requests like returns, billing disputes, and account issues. It has access to your backend systems through custom Model Context Protocol (MCP) tools ( get_customer , lookup_order , process_refund , escalate_to_human ). Your target is 80%+ first-contact resolution while knowing when to escalate.
When the agent calls lookup_order and receives order details showing the item was purchased 45 days ago, how does the agentic loop determine whether to call process_refund or escalate_to_human next?

A) The agent executes the remaining steps in a tool sequence planned at the start of the request.
B) The orchestration layer automatically routes to the next tool based on the order's status field.
C) The agent follows a pre-configured decision tree mapping order attributes to specific tool calls.
D) The order details are added to the conversation and the model reasons about which action to take.

Solutions: