Anthropic CCA-F 시험 개요:

Anthropic CCA-F 시험 요강 주제:

최신 Claude Certified Architect CCA-F 무료샘플문제

1. An architect needs Claude to produce structured JSON that downstream software can parse automatically. Which prompting strategy is BEST?

A) Ask Claude to "respond normally."
B) Use multiple unrelated examples.
C) Explicitly specify the required JSON schema and formatting rules.
D) Increase maximum output tokens only.

2. You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with Model Context Protocol (MCP) servers.
A developer asks the agent to investigate why a specific API endpoint intermittently returns 500 errors. The codebase has 200+ files and the developer doesn't know which components are involved. The agent must trace the error through routing, middleware, business logic, and database layers. What task decomposition approach would be most effective?

A) Have the agent first create a comprehensive plan mapping all code paths through the endpoint before beginning any file exploration or code reading.
B) Define a fixed sequence of investigation steps upfront - grep for error patterns, then read error handlers, then check database queries, then examine middleware - executing each step regardless of intermediate findings.
C) Run parallel worker agents that simultaneously investigate all four layers, then synthesize their findings to identify where the error originates.
D) Have the agent dynamically generate investigation subtasks based on what it discovers at each step, adapting its exploration plan as new information about the error path emerges.

3. You are building a multi-agent research system using the Claude Agent SDK. A coordinator agent delegates to specialized subagents: one searches the web, one analyzes documents, one synthesizes findings, and one generates reports. The system researches topics and produces comprehensive, cited reports.
A user is expanding the research system beyond its single web search agent by adding specialized data sources. They add a financial API agent that returns structured JSON with revenue, margins, and growth rates; a news monitoring agent that returns prose summaries of recent developments; and a patent analysis agent that returns structured lists of technology areas. The synthesis agent combines these into executive briefings. Currently, it converts everything to bullet points, causing financial comparisons to lose tabular clarity and news summaries to lose narrative flow. What change would most improve briefing quality?

A) Update the synthesis agent to render each content type appropriately - financial data as tables, news as prose
B) Standardize all subagent outputs to JSON with fields for claim, evidence, source, and confidence
C) Standardize all subagent outputs to prose summaries with inline citations
D) Add a format conversion layer between subagents and synthesis that transforms all outputs to a common intermediate representation

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

5. 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) Process the refund via process_refund to resolve the underlying issue, then inform them it's complete
D) Call escalate_to_human immediately to honor the customer's request

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