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Anthropic CCA-F Exam Syllabus Topics:

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

1. The synthesis agent receives summarized findings from the web search and document analysis agents, then passes a consolidated summary to the report generator. During testing, you discover the generated reports make factual claims without proper citations - the report generator cannot attribute statements to their original sources because that metadata was lost during the summarization steps. What's the most effective approach to ensure proper source attribution in the final reports?

A) Instruct the synthesis agent to embed source references inline within its summary text using a consistent citation format.
B) Skip summarization and pass full raw outputs from web search and document analysis directly to the report generator.
C) Have each agent output structured data separating content summaries from source metadata (URLs, document names, page numbers).
D) Have the report generator query the web search agent to re-locate sources for claims in the final report.

2. Your agent has called lookup_order multiple times while investigating a customer's return requests. Each response includes 40+ fields (items, shipping details, payment info, status history). Tool outputs now represent the majority of the conversation's context. The customer mentions two more orders they want to discuss. What's the most effective approach before making additional lookups?

A) Have the model generate a natural language summary of each order's key details, replacing structured responses with prose descriptions
B) Extract only the return-relevant fields (items, purchase date, return window, status) from each existing order response, removing verbose details
C) Proceed with additional lookups without modifying the existing tool output context
D) Move all tool responses to a vector database with semantic indexing, retrieving relevant portions as the conversation continues

3. 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) 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.
C) 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.
D) Subagent context isolation means task descriptions from the coordinator don't automatically reach subagents; you need to configure explicit context forwarding in ClaudeAgentOptions.

4. A company wants Claude to summarize thousands of support tickets efficiently. Which design scales BEST?

A) Remove system prompts.
B) Increase temperature.
C) Send all tickets in one request.
D) Process tickets individually and combine summaries.

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

Solutions: