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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect - Foundations Sample Questions:

Question 1

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, and Glob--and integrates with Model Context Protocol (MCP) servers.
An engineer who recently joined the team asks the agent to explain the authentication and authorization architecture before making security improvements. The codebase contains more than 800 files across multiple services.
What exploration strategy will most effectively build understanding while respecting context limits?

A. Read all CLAUDE.md and README files first, and then ask the engineer to identify the 10?5 most important authentication files.
B. Launch parallel subagents to explore every service simultaneously, and then synthesize their findings into an architectural overview.
C. Read all files containing auth, login, permission, or token in their filenames or contents.
D. Use Grep to locate authentication entry points, read those files, and then follow imports and function calls incrementally to map the authentication flow.

Question 2

A customer returns 4 hours after the 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 In testing, you observe that when resuming sessions with stale tool results, the agent often references the outdated data in responses (e.g., "I see your refund is still being processed") even after subsequent fresh tool calls return different information.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 but filter out previous tool_result messages before resuming, keeping only the human/assistant turns so the agent must re-fetch needed data.
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 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.
D. Resume with full history and configure the agent to automatically re-call all previously-used tools at session start to ensure data freshness.

Question 3

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.
Your CI pipeline performs security-focused code reviews on approximately 50 pull requests daily, currently costing $150 per day using the synchronous API. Reviews are non-blocking--developers merge after tests pass and address findings in follow-up commits. You are evaluating the Message Batches API for its 50% cost reduction.
What factor most determines whether batch processing is appropriate for this use case?

A. Whether your result-processing system can handle reviews arriving in a different order from the order in which they were submitted.
B. Whether review feedback arriving up to 24 hours after pull-request creation remains actionable.
C. Whether reducing per-review latency from 30?0 seconds to near-instant matters for your workflow.
D. Whether you can structure each review as a single request without multi-turn refinement.

Question 4

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.
An engineer's exploration subagent spent 30 minutes analyzing a legacy payment system, reading 47 files and documenting data flows. The session was interrupted when the engineer's connection dropped. While away, a teammate merged a PR that renamed two utility functions.
The engineer wants to continue the same exploration.
What's the most effective approach?

A. Resume the subagent from its previous transcript and inform it about the renamed functions.
B. Launch a fresh subagent and include the prior transcript in the initial prompt for context.
C. Resume the subagent from its previous transcript without mentioning the changes--the architecture understanding remains valid.
D. Launch a fresh subagent with a summary of prior findings.

Question 5

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

Solutions: