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Anthropic CCA-F Exam Syllabus Topics:

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

1. The document analysis agent has a single analyze_documnet tool that takes a document and a free-text instruction parameter. During evaluation, requests like "extract the key financial metrics" often return narrative summaries, while "summarize the methodology" sometimes returns raw data tables. The synthesis agent reports that 35% of analysis results require re-requests with clarified instructions. What's the most effective way to improve reliability?

A) Keep the single tool but add an analyze_type enum parameter requiring explicit selection between extraction, summarization, and verification modes
B) Have the coordinator pre-classify each analysis request before passing instructions to the document analysis agent
C) Split the generic tool into purpose-specific tools - extract_data_points, summarize_content, verify_claim_against_source - each with defined input/output contracts
D) Enhance the tool description with detailed examples showing how different instruction phrasings should map to different output formats

2. A developer wants Claude to consistently answer as an experienced cybersecurity analyst regardless of the user question. Which prompt component should contain this instruction?

A) System prompt
B) Assistant response
C) Retrieved document
D) User message

3. Users report that final reports sometimes lack depth on specific subtopics. Investigation shows that the document analysis agent frequently identifies gaps - for instance, noting "the retrieved sources discuss API authentication but lack details on token refresh patterns" - but under the current strict pipeline, this insight isn't actionable since search has already completed. What's the most effective architectural change?

A) Have the analysis agent report specific gaps to the coordinator, which triggers targeted searches and re-invokes analysis until sufficient.
B) Have the coordinator review analysis output for gap indicators and re-invoke search with gap- informed queries when gaps are detected.
C) Add a research planning agent before the search phase that decomposes topics into specific sub- questions.
D) Have the synthesis agent attach confidence scores to each section and flag areas with insufficient coverage for manual review.

4. 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) Implement automatic retry logic at the tool level for technical errors only, passing business errors to Claude without retries.
B) Return structured error responses with retriable: false for business errors and a customer-friendly explanation for Claude to use.
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.

5. The coordinator agent has AgentDefinitions configured for all four specialized subagents, each with appropriate descriptions, prompts, and tool restrictions. During testing, you notice the coordinator correctly reasons about when to delegate - it generates messages like "I'll ask the web search agent to find sources on this topic" - but no subagent execution ever 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 AgentDefinitions are configured correctly, but the coordinator's system prompt doesn't explicitly list the available subagent types, preventing the model from knowing they can be invoked.
B) Subagent context isolation means task descriptions from the coordinator don't automatically reach subagents; you need to configure explicit context forwarding in ClaudeAgentOptions.
C) The coordinator's allowedTools configuration doesn't include "Task", so while it can reason about delegation, it cannot invoke the tool required to spawn subagents.
D) The coordinator's max_tokens setting is too low, causing the Task tool invocation to be truncated before the subagent type parameter can be specified.

Solutions: