Anthropic Claude Certified Architect - Foundations : CCAR-F

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Anthropic CCAR-F Prüfungsthemen:

Anthropic Claude Certified Architect - Foundations CCAR-F Prüfungsfragen mit Lösungen

1. You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline.
The system runs automated code reviews, generates test cases, and provides feedback on pull requests. You need to design prompts that provide actionable feedback and minimize false positives.
During initial testing of the automated review pipeline, you notice that reviews on large pull requests containing more than 50 changed files sometimes take over 20 minutes and cost $8-$12 per run because of extensive agentic loops. Claude reads files, runs analysis tools, and iterates many times. Your team needs each invocation to abort once it reaches both a fixed iteration count and a fixed dollar amount, enforced by Claude Code itself rather than by the surrounding job runner.
Which configuration change directly enforces both per-invocation caps?

A) Set timeout-minutes: 5 on the GitHub Actions job step and monitor per-run costs through the Anthropic Console usage dashboard.
B) Switch the --model flag to a smaller, less expensive model so each iteration uses fewer tokens and has a lower per-call cost.
C) Set --permission-mode dontAsk to automatically deny tool-permission requests not included in the explicitly allowed set.
D) Add --max-turns 10 --max-budget-usd 2.00 to the claude -p invocation to cap iterations and spending.

2. 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.
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) Compile a structured handoff with customer details, order info, and the identified issue before calling escalate_to_human .
B) Attempt the refund with process_refund anyway, escalating only if the system rejects the transaction.
C) Persist the complete conversation and tool response history to a database, then call escalate_to_human with a reference ID.
D) Call escalate_to_human , passing only the customer's original message.

3. 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.
You've configured your Claude agent with three MCP servers: one for git operations, one for Jira ticket management, and one for documentation search.
When a user asks the agent to "create a branch for JIRA-123 and add documentation links to the ticket," how does the agent access tools across these servers?

A) You must specify which MCP server to use for each turn, and the agent can only access one server's tools at a time.
B) The agent automatically selects the most relevant server based on the request and loads only that server' s tools.
C) The agent queries each server sequentially to determine which handles each tool, routing calls based on tool name prefixes.
D) Tools from all configured MCP servers are discovered at connection time and available simultaneously to the agent.

4. Your pipeline reviews every pull request using a single API call with a static prompt containing the diff and the full text of each changed file; unchanged files are not included. Reviews are posted asynchronously and do not block pull-request creation. Developers report that reviews consistently miss bugs involving cross-file interactions-for example, a pull request renames a function's parameters, but the review does not flag callers in other files that still use the old parameter names. Post-release analysis shows that cross-file bugs account for 35% of production incidents from reviewed pull requests. What is the most effective change to your review design?

A) Add chain-of-thought instructions asking the model to list all external references in the diff and then reason step by step about how each change might affect callers in other files.
B) Use static analysis to build a dependency graph of changed code, and then expand the prompt to include every file within two dependency hops of any changed file.
C) Redesign the review as a turn-limited agentic task in which the model can read files and search the codebase through tools, following references to verify cross-file findings.
D) Run parallel review passes for each changed file with its direct dependents included, and then aggregate and deduplicate the findings through a final summarization call.

5. Your multi-agent research pipeline crashed after processing 12 of 28 documents. The web-search agent had identified relevant sources, the document analyzer had partially completed extraction, and the synthesizer had begun identifying patterns. You need to resume processing without repeating work or losing fidelity in the prior findings. What state-management approach best balances information fidelity with context efficiency when restoring agent state?

A) Persist the coordinator's conversation log containing all task delegations and responses, and provide this log to the agents when resuming.
B) Index all agent outputs in a shared vector store. When resuming, have each agent query 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 beginning of each session.
D) Have each agent persist a structured export to a known location. On resumption, the coordinator loads the manifest and injects relevant state into agent prompts.

Fragen und Antworten: