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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect - Foundations Sample Questions:

Question 1

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

Question 2

The document analysis agent has a single analyze_documnet tool that takes a document and a free-text instruction parameter. During evaluation, requests like "extract the key financial metrics" often return narrative summaries, while "summarize the methodology" sometimes returns raw data tables. The synthesis agent reports that 35% of analysis results require re-requests with clarified instructions. What's the most effective way to improve reliability?

A. Enhance the tool description with detailed examples showing how different instruction phrasings should map to different output formats
B. Keep the single tool but add an analyze_type enum parameter requiring explicit selection between extraction, summarization, and verification modes
C. Split the generic tool into purpose-specific tools - extract_data_points, summarize_content, verify_claim_against_source - each with defined input/output contracts
D. Have the coordinator pre-classify each analysis request before passing instructions to the document analysis agent

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

Question 4

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.
You're implementing a caching layer for API responses to speed up the /products endpoint. You have a rough idea-Redis with a 5-minute TTL-but you're new to production caching and aren't sure what other considerations a robust implementation requires. What's the most effective way to start your iterative workflow?

A. Write a specification with your known requirements and "TBD" markers for uncertain areas, having Claude propose solutions for each TBD as it implements.
B. Start with a minimal request: "Add Redis caching to /products with 5-minute TTL." Add features and fix issues through follow-up prompts as problems surface during testing.
C. Use plan mode to analyze the current/products endpoint implementation, then provide your caching requirements once Claude explains how the existing code is structured.
D. Ask Claude to interview you about the caching requirements before implementing, surfacing considerations like invalidation strategies, cache layers, consistency guarantees, and failure modes.

Question 5

A financial services company plans to integrate Claude into an internal document analysis platform. The architects want to minimize exposure of confidential client information while maintaining high-quality responses. Which approach BEST aligns with Anthropic's recommended architecture?

A. Remove unnecessary sensitive information before sending prompts whenever possible.
B. Send every document without preprocessing to maximize context.
C. Replace Claude with a smaller local model regardless of task complexity.
D. Store every prompt permanently for auditing.

Solutions: