Anthropic CCA-F - Claude Certified Architect - Foundations Exam
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Total 46 questions
Question #1 (Topic: Exam A)
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. Have the report generator query the web search agent to re-locate sources for claims in the final report.
B. Have each agent output structured data separating content summaries from source metadata (URLs, document names, page numbers).
C. Skip summarization and pass full raw outputs from web search and document analysis directly to the report generator.
D. Instruct the synthesis agent to embed source references inline within its summary text using a consistent citation format.
Answer: B
Question #2 (Topic: Exam A)
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 the full accumulated context from all prior agents.
B. Pass the synthesis draft along with a structured source index that maps key claims to their source URLs and relevant excerpts.
C. Pass only the synthesis draft and have a separate post-processing pipeline match claims to sources and insert citations after the report is generated.
D. Pass a condensed summary of all prior stages that preserves the main findings and attributes them to sources by name only.
Answer: B
Question #3 (Topic: Exam A)
Your multi-agent research pipeline crashed after processing12 of 28 documents. The web search agent had identified relevant sources, the document analyzer had partially completed extraction, and the synthesizer had begun pattern identification. You need to resume processing without repeating work or losing fidelity of prior findings. What state management approach best balances information fidelity with context efficiency when restoring agent state?
A. Have each agent persist a structured export to a known location. On resume, the coordinator loads the manifest and injects relevant state into agent prompts.
B. Index all agent outputs in a shared vector store. When resuming, each agent queries the store using semantic search to retrieve relevant prior findings.
C. Have each agent maintain its own persistent state file and reload it independently at the start of each session.
D. Persist the coordinator’s conversation log containing all task delegations and responses, providing this to agents when resuming.
Answer: A
Question #4 (Topic: Exam A)
You’ve configured the system so that all four subagents have access to the complete set of 18 tools. During testing, agents frequently call tools outside their specialization – the synthesis agent attempts web searches, and the report generator tries to analyze documents. What is the primary cause of this poor tool selection behavior?
A. Choosing from 18 tools instead of 4-5 relevant ones increases decision complexity beyond reliable selection thresholds.
B. The tool definitions consume too much context window space, leaving insufficient room for task content.
C. The agents’ role descriptions in their system prompts conflict with having access to tools outside that role.
D. The coordinator cannot track which capabilities each subagent has, leading to misrouted tasks.
Answer: A
Question #5 (Topic: Exam A)
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. Implement a topic classification step where the coordinator categorizes requests as “well-defined” or “exploratory” and uses different instruction styles for each category.
B. Add explicit fallback directives to the detailed instructions: “If specified searches yield fewer than N results, attempt alternative query formulations before reporting failure.”
C. Remove procedural details entirely, delegating with simple goals like “research X thoroughly” and relying on the subagent’s general capabilities.
D. Specify research goals and quality criteria (coverage breadth, source diversity, recency) rather than procedural steps, letting the subagent determine its search strategy.
Answer: D
