Anthropic CCA-F : Claude Certified Architect Foundations (CCA-F)

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Anthropic CCA-F Exam Syllabus Topics:

Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions:

1. 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 spent 25 minutes exploring a game engine's rendering subsystem -reading shader code, buffer management, and frame synchronization logic. An engineer now asks it to understand how the physics engine integrates with rendering for collision debug overlays. You notice recent responses reference "typical rendering patterns" rather than the specific VulkanPipeline and FrameGraph classes it discovered earlier.
What's the most effective approach?

A) Continue in the current context with more targeted prompts referencing the specific classes by name.
B) Spawn a sub-agent to explore physics independently, then manually synthesize its findings with the rendering knowledge accumulated in the main conversation.
C) Use /clear to reset context completely, then start fresh with physics exploration using file paths from the project's CLAUDE.md.
D) Summarize key rendering findings, then spawn a sub-agent for physics exploration with that summary in its initial context.

2. Your order management system requires tools for three distinct operations: issuing refunds (requires amount and reason), canceling orders (requires reason), and requesting reshipments (requires shipping address). Each operation shares an order_id parameter but has different additional requirements. You notice during testing that with your current unified tool design, the agent frequently omits required parameters or includes irrelevant ones. What design change will most effectively improve parameter accuracy?

A) Split into three separate tools (issue_refund, cancel_order, request_reshipment), each defining only the parameters required for that specific operation.
B) Keep one unified tool with all parameters marked optional, but add detailed few-shot examples in the system prompt showing correct parameter combinations for each operation type.
C) Keep one unified tool but add JSON Schema if-then-else conditionals to enforce that parameters like amount are required only when the operation type is "refund".
D) Keep one unified tool with a nested operation_details object parameter whose internal structure varies by operation type, documented in the tool description.

3. During a billing dispute resolution, your agent successfully retrieves customer info via get_customer and order details via lookup_order, but when attempting to call process_refund, the tool returns a timeout error. The agent has enough information to explain the charges and verify refund eligibility, but cannot actually process the refund due to the backend failure. What approach best balances first-contact resolution with appropriate error handling?

A) Confirm the refund will be processed and close the conversation, since the system has all necessary information to complete it automatically
B) Escalate immediately to a human agent since the refund action cannot be completed
C) Explain the billing confirm refund eligibility, acknowledge the system issue preventing immediate processing, and offer escalation or retry later
D) Implement automatic retries with exponential backoff for process_refund, keeping the conversation open until the refund is successfully processed

4. 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" rather than trying alternative approaches when pre-specified searches fail, (2) research quality drops for emerging topics that don't match expected patterns, and (3) the subagent rarely surfaces valuable tangential sources.
What's the most effective way to improve subagent adaptability?

A) Add explicit fallback directives to the detailed instructions: "If specified searches yield fewer than N results, attempt alternative query formulations before reporting failure."
B) Specify research goals and quality criteria (coverage breadth, source diversity, recency) rather than procedural steps, letting the subagent determine its search strategy.
C) Implement a topic classification step where the coordinator categorizes requests as "well-defined" or "exploratory" and uses different instruction styles for each category.
D) Remove procedural details entirely, delegating with simple goals like "research X thoroughly" and relying on the subagent's general capabilities.

5. A retail organization observes that Claude occasionally gives different wording when summarizing identical customer reviews. The summaries remain accurate. What is the MOST likely explanation?

A) Retrieval failed.
B) The API returned cached responses.
C) Large language models are probabilistic.
D) Claude is malfunctioning.

Solutions: