Anthropic CCA-F 試験概要:

Anthropic CCA-F 試験シラバストピック:

Anthropic Claude Certified Architect Foundations (CCA-F) 認定 CCA-F 試験問題：

問題 #1
An enterprise wants Claude responses to remain professional across every interaction. Where should tone instructions primarily reside?

A. API key description
B. User prompt only
C. System prompt
D. Retrieved documents

問題 #2
A customer writes: "I've been going back and forth on this return for days. I just want to speak to someone who can actually help me." The agent has confirmed via lookup_order that the return is straightforward - within policy and eligible for immediate processing. What should the agent do?

A. Acknowledge frustration, inform them this is resolvable now, and offer to complete it or escalate
B. Ask what specifically hasn't worked in previous attempts before deciding whether to escalate or resolve automatically
C. Call escalate_to_human immediately to honor the customer's request
D. Process the refund via process_refund to resolve the underlying issue, then inform them it's complete

問題 #3
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. The tool definitions consume too much context window space, leaving insufficient room for task content.
B. Choosing from 18 tools instead of 4-5 relevant ones increases decision complexity beyond reliable selection thresholds.
C. The coordinator cannot track which capabilities each subagent has, leading to misrouted tasks.
D. The agents' role descriptions in their system prompts conflict with having access to tools outside that role.

問題 #4
Your agent uses three tools: get_property_details(property_id) returns data including street address, get_price_history(property_id) returns historical pricing, and get_neighborhood_info(address) returns area statistics. You observe that get_neighborhood_info always requires get_property_details first just to extract the address, even when users specify the property by ID. This creates unnecessary latency and failure coupling - if the first call fails, the neighborhood request also fails. What tool design change best addresses this?

A. Add retry logic and timeout handling to get_property_details.
B. Create a lookup_address(property_id) helper tool for retrieving addresses.
C. Consolidate into a single get_property_with_neighborhood(property_id) tool returning both datasets.
D. Change get_neighborhood_info to accept property_id, resolving the address internally.

問題 #5
Production reviews reveal inconsistent handling of uncertainty in final reports. Sometimes conflicting subagent findings are synthesized into a single confident statement (losing nuance), while other times reports over-hedge with excessive qualifications (becoming unhelpful). When the web search agent returns "industry analysts estimate $50B market size (methodology varies)" and the document analysis agent returns "peer-reviewed study estimates $35B (±$7B, 95% CI)," the coordinator either picks one arbitrarily or produces vague statements like "the market may be
$35B-$50B depending on factors." What systematic approach best addresses this?

A. Configure subagents to only report findings meeting a high-confidence threshold, filtering uncertain information before it reaches the coordinator.
B. Implement a confidence calibration layer that normalizes subagent uncertainty expressions to standardized probability scores (0.0-1.0), then weight-average findings by their calibrated confidence.
C. Add a verification subagent that cross-references findings across sources, only passing claims to synthesis that are corroborated by at least two independent sources.
D. Instruct the synthesis agent to structure reports with explicit sections distinguishing well- established findings from contested ones, preserving original source characterizations and methodological context.

解説：