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最新的 Claude Certified Architect CCAR-F 免費考試真題:

1. You are building a customer support resolution agent using the Claude Agent SDK. The agent handles high- ambiguity requests like returns, billing disputes, and account issues. It has access to your backend systems through custom Model Context Protocol (MCP) tools ( get_customer , lookup_order , process_refund , escalate_to_human ). Your target is 80%+ first-contact resolution while knowing when to escalate.
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.

2. You are using Claude Code to accelerate software development. Your team uses it for code generation, refactoring, debugging, and documentation. You need to integrate it into your development workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.
Your team's CLAUDE.md includes a rule: "Use 4-space indentation and always run Prettier formatting." Despite this, code reviews reveal that roughly 30% of files Claude Code generates use inconsistent formatting-sometimes 2-space indentation, sometimes missing trailing commas. Adding emphasis ("IMPORTANT: You MUST use Prettier formatting") reduces violations to about 15%, but doesn't eliminate them.
What is the most effective way to ensure all generated code is consistently formatted?

A) Split the formatting rules into path-scoped .claude/rules/ files that load when Claude works on matching file types.
B) Add a Stop hook with a prompt-based check that evaluates whether generated code follows formatting standards and prompts Claude to fix violations.
C) Extract the formatting rules into a dedicated skill that Claude loads automatically when generating code, with more detailed examples of correct formatting.
D) Configure a PostToolUse hook with an Edit|Write matcher that automatically runs Prettier on each file Claude modifies.

3. You are building a customer support resolution agent using the Claude Agent SDK. The agent handles high- ambiguity requests like returns, billing disputes, and account issues. It has access to your backend systems through custom Model Context Protocol (MCP) tools (get_customer, lookup_order, process_refund, escalate_to_human). Your target is 80%+ first-contact resolution while knowing when to escalate.
A customer returns 4 hours after their initial session about the same billing dispute. The previous 32-turn session contains lookup_order results showing "Status: PENDING, Expected resolution: 24-48 hours." In testing, you observe that when resuming sessions with stale tool results, the agent often references the outdated data in responses (e.g., "I see your refund is still being processed") even after subsequent fresh tool calls return different information.
What approach most reliably handles returning customers?

A) Resume with full history and add a system prompt instruction telling the agent to always prefer the most recent tool results when multiple calls to the same tool exist in context.
B) Start a new session, inject a structured summary of the previous interaction (issue type, actions taken, resolution status), then make fresh tool calls before engaging.
C) Resume with full history and configure the agent to automatically re-call all previously used tools at session start to ensure data freshness.
D) Resume with full history but filter out previous tool_result messages before resuming, keeping only the human/assistant turns so the agent must re-fetch needed data.

4. You are building a customer support resolution agent using the Claude Agent SDK. The agent handles high- ambiguity requests like returns, billing disputes, and account issues. It has access to your backend systems through custom Model Context Protocol (MCP) tools ( get_customer , lookup_order , process_refund , escalate_to_human ). Your target is 80%+ first-contact resolution while knowing when to escalate.
A customer contacts the agent about a warranty claim on a power drill. Resolving this requires multiple sequential tool calls: get_customer to look up their account, lookup_order to find the purchase details, and then either process_refund or escalate_to_human depending on warranty eligibility. You're implementing the agentic loop that orchestrates these steps using the Claude API.
What is the primary mechanism your application uses to determine whether to continue the loop or stop?

A) You track the number of tool calls made and exit the loop once a preconfigured maximum is reached.
B) You check whether Claude's response contains a text content block-if text is present, the agent has produced its final answer and the loop should exit.
C) You manually set the tool_choice parameter to "none" after the final expected tool call to force Claude to stop requesting tools.
D) You check the stop_reason field in each API response-the loop continues while it equals "tool_use" and exits when it changes to "end_turn" or another terminal value.

5. You are using Claude Code to accelerate software development. Your team uses it for code generation, refactoring, debugging, and documentation. You need to integrate it into your development workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.
Your team has connected a custom MCP server that provides DevOps workflow templates. The server exposes several MCP prompts (such as deploy_checklist and incident_response ) in addition to tools.
How do these MCP prompts become accessible within Claude Code?

A) They appear as slash commands (e.g., /mcp__servername__deploy_checklist ) that you can invoke, with arguments passed after the command name.
B) They are surfaced as @ -mentionable resources alongside files, fetched and attached to your message when referenced.
C) They are added to Claude Code's tool registry alongside the server's tools, invoked automatically by the model when relevant to the task.
D) They are automatically prepended to every conversation as additional system-level context, influencing Claude's behavior throughout the session.

問題與答案：