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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect – Foundations Sample Questions:

1. 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 need to add a date validation check ensuring event dates are in the future. This requires adding a conditional statement to one existing function in a single file.
What is the most appropriate approach?

A) Use direct execution to make the change.
B) Enter plan mode first to create a detailed implementation strategy before making the change.
C) Enter plan mode to analyze how the validation might impact other parts of the reservation flow.
D) Start with extended thinking mode enabled to ensure thorough reasoning about the validation logic.

2. 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.
A customer raises three separate issues during one session: a refund inquiry (turns 1-15), a subscription question (turns 16-30), and a payment method update (turns 31-45). At turn 48, the customer asks "What happened with my refund?" The conversation is approaching context limits.
What strategy best maintains the agent's ability to address all issues throughout the session?

A) Summarize earlier turns into a narrative description, preserving full message history only for the active issue.
B) Implement sliding window context that retains the most recent 30 turns.
C) Rely on MCP tools to re-fetch relevant information on demand when the customer references earlier issues.
D) Extract and persist structured issue data (order IDs, amounts, statuses) into a separate context layer.

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.
You've configured your Claude agent with three MCP servers: one for git operations, one for Jira ticket management, and one for documentation search.
When a user asks the agent to "create a branch for JIRA-123 and add documentation links to the ticket," how does the agent access tools across these servers?

A) The agent queries each server sequentially to determine which handles each tool, routing calls based on tool name prefixes.
B) The agent automatically selects the most relevant server based on the request and loads only that server' s tools.
C) Tools from all configured MCP servers are discovered at connection time and available simultaneously to the agent.
D) You must specify which MCP server to use for each turn, and the agent can only access one server's tools at a time.

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 system implements automatic retries when validation fails. On each retry, the specific validation error is appended to the prompt. This retry-with-error-feedback approach resolves most failures within 2-3 attempts.
For which failure pattern would additional retries be LEAST effective?

A) The model extracts citation counts as locale-formatted strings ("1,234") when the schema requires integers.
B) The model extracts dates as ISO 8601 datetime strings ("2023-03-15T00:00:00Z") when the schema requires only the date portion (YYYY-MM-DD).
C) The model extracts keywords as a nested object organized by category when the schema requires a flat array of strings.
D) The model extracts "et al." for co-authors when the full list exists only in an external document not in the input.

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.
Your agent is handling a billing dispute. After calling get_customer and lookup_order , it identifies that the dispute involves a promotional pricing error requiring manager approval-beyond the agent's authorization level.
How should the workflow handle this mid-process escalation?

A) Call escalate_to_human , passing only the customer's original message.
B) Attempt the refund with process_refund anyway, escalating only if the system rejects the transaction.
C) Compile a structured handoff with customer details, order info, and the identified issue before calling escalate_to_human .
D) Persist the complete conversation and tool response history to a database, then call escalate_to_human with a reference ID.

Solutions: