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Anthropic CCAR-F Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Prompt Engineering & Structured Output | 20% | - Prompt design
|
| Context Management & Reliability | 15% | - Context handling
|
| Agentic Architecture & Orchestration | 27% | - Agentic architecture patterns
|
| Tool Design & MCP Integration | 18% | - Tool integration
|
| Claude Code Configuration & Workflows | 20% | - Claude Code
|
Anthropic Claude Certified Architect - Foundations Sample Questions:
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.
Monitoring shows 12% of extractions fail Pydantic validation with specific errors like "expected float for quantity, got `2 to 3'". Retrying these requests without modification produces identical failures.
What's the most effective approach to recover from these validation failures?
- A. Pre-process source documents to standardize problematic formats before sending them for extraction.
- B. Set temperature to 0 to eliminate output variability and ensure consistent formatting.
- C. Implement a secondary pipeline using a larger model tier to reprocess documents that fail validation.
- D. Send a follow-up request including the validation error, asking the model to correct its output.
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Your control_device tool manages smart home devices through external APIs. When a device doesn't respond within the timeout period, the tool returns an error. Production logs show that the agent simply tells users "the device is not responding" without offering helpful next steps. Which error response structure would best enable the agent to provide useful follow-up?
- A. Set is_error: true with a structured technical error containing the device ID, timeout duration, and raw API response code for debugging purposes.
- B. Set is_error: false with an optimistic message indicating the command was dispatched successfully but device acknowledgment is still pending.
- C. Set is_error: true with a message explaining the likely cause and suggesting troubleshooting steps the agent can offer the user.
- D. Set is_error: true with a brief "Device offline" message and provide a separate tool the agent can call to retrieve context-specific troubleshooting suggestions.
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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 orchestration layer automatically routes to the next tool based on the order's status field.
- B. The agent follows a pre-configured decision tree mapping order attributes to specific tool calls.
- C. The order details are added to the conversation and the model reasons about which action to take.
- D. The agent executes the remaining steps in a tool sequence planned at the start of the request.
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An application frequently repeats the same background instructions in every API request. What is a potential downside?
- A. Increased hallucinations only.
- B. Lower reliability.
- C. Higher token usage and cost.
- D. Reduced model capability.
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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.
An engineer who recently joined the team asks the agent to explain the authentication and authorization architecture before making security improvements. The codebase contains more than 800 files across multiple services.
What exploration strategy will most effectively build understanding while respecting context limits?
- A. Read all CLAUDE.md and README files first, and then ask the engineer to identify the 10?5 most important authentication files.
- B. Use Grep to locate authentication entry points, read those files, and then follow imports and function calls incrementally to map the authentication flow.
- C. Read all files containing auth, login, permission, or token in their filenames or contents.
- D. Launch parallel subagents to explore every service simultaneously, and then synthesize their findings into an architectural overview.
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