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Anthropic CCA-F Exam Syllabus Topics:

Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions:

1. 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

2. A customer sends: "This is frustrating. I've explained my issue twice and nothing is being resolved. I want to talk to a real person NOW." The agent has not yet called any tools to investigate their account. What should the agent do?

A) Briefly explain what the agent can help with and offer to resolve the issue quickly, escalating only if the customer repeats their request.
B) Immediately call escalate_to_human with the conversation history.
C) Acknowledge the frustration and ask one targeted question to understand the specific issue before escalating.
D) First call get_customer and lookup_order to gather account context, then escalate to a human agent.

3. The synthesis agent completes its initial pass but flags that three key research questions remain unanswered because the web search and document analysis agents didn't find relevant information on those specific subtopics. The coordinator currently proceeds directly to report generation, producing reports with incomplete coverage. What change would most effectively improve research completeness?

A) Increase the initial breadth of queries sent to web search and document analysis to reduce the probability of missing relevant information.
B) Have the report generation agent note which research questions couldn't be answered, so users understand the limitations of the final output.
C) Have the coordinator evaluate synthesis output for gaps, then re-delegate to web search and document analysis with targeted queries before invoking synthesis again.
D) Give the synthesis agent direct access to web search tools so it can autonomously fill knowledge gaps without returning control to the coordinator.

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.
Your code review assistant needs to analyze pull requests and provide feedback on three aspects: code style compliance, potential security issues, and documentation completeness.
Each aspect requires reading files, running analysis tools, and generating a report section. The review process follows the same three-step workflow for every PR. Which task decomposition pattern is most appropriate for this workflow?

A) Orchestrator-workers - have a central LLM analyze each PR to dynamically determine which checks are needed, then delegate to specialized worker LLMs for each identified subtask.
B) Routing - classify each PR by type (feature, bugfix, refactor) first, then route to different review prompts optimized for that category.
C) Prompt chaining - break the review into sequential steps where each aspect (style, security, documentation) is analyzed separately, with outputs combined in a final synthesis step.
D) Single comprehensive prompt - include all instructions in one prompt and let the model handle all three aspects simultaneously.

5. A chatbot frequently receives greetings, policy questions, and technical support requests. Which architecture improves maintainability?

A) One prompt for every scenario.
B) Prompt routing based on request type.
C) Disable retrieval.
D) Maximum temperature.

Solutions: