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Anthropic CCA-F Exam Syllabus Topics:

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

1. After the web search agent finds 25 sources (120K tokens of raw content), the document analysis agent extracts key insights (15K tokens), and the synthesis agent produces a coherent narrative draft (3K tokens), the coordinator must pass context to the report generation agent for the final output with proper source citations. What context-passing strategy provides the best balance of completeness and efficiency?

A) Pass only the synthesis draft and have a separate post-processing pipeline match claims to sources and insert citations after the report is generated.
B) Pass the synthesis draft along with a structured source index that maps key claims to their source URLs and relevant excerpts.
C) Pass a condensed summary of all prior stages that preserves the main findings and attributes them to sources by name only.
D) Pass the full accumulated context from all prior agents.

2. 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) Attempt the refund with process_refund anyway, escalating only if the system rejects the transaction.
B) Call escalate_to_human passing only the customer's original message.
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.

3. Which prompt revision is MOST likely to improve output quality?

A) Include objective, context, constraints, and expected format.
B) "Summarize this."
C) Use only uppercase letters.
D) "Help me."

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) Remove procedural details entirely, delegating with simple goals like "research X thoroughly" and relying on the subagent's general capabilities.
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) Specify research goals and quality criteria (coverage breadth, source diversity, recency) rather than procedural steps, letting the subagent determine its search strategy.

5. What is the PRIMARY purpose of few-shot prompting?

A) Encrypt prompts.
B) Increase model size.
C) Demonstrate desired output patterns.
D) Reduce token costs.

Solutions: