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Anthropic CCA-F Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Claude Code Configuration & Workflows | 20% | - Claude Code configuration
|
| Topic 2: Agentic Architecture & Orchestration | 27% | - Multi-agent orchestration
|
| Topic 3: Prompt Engineering & Structured Output | 20% | - Instruction design
|
| Topic 4: Context Management & Reliability | 15% | - System reliability
|
| Topic 5: Tool Design & MCP Integration | 18% | - Tool interface design
|
Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions:
1. An architect needs Claude to produce structured JSON that downstream software can parse automatically. Which prompting strategy is BEST?
A) Ask Claude to "respond normally."
B) Increase maximum output tokens only.
C) Use multiple unrelated examples.
D) Explicitly specify the required JSON schema and formatting rules.
2. Your expense reimbursement agent processes employee requests using a
process_reimbursement tool. Company policy requires that reimbursements above $500 must be approved by a manager before funds are disbursed. The agent handles hundreds of requests daily, and you need the threshold enforcement to be tamper-proof regardless of how the agent is prompted. Which design ensures the $500 approval threshold cannot be bypassed?
A) The process_reimbursement tool accepts an approved_by_manager: boolean parameter. The system prompt instructs the agent to only set this to true after confirming that a manager has approved the request. A nightly audit script reviews all reimbursements where approved_by_manager was set to true.
B) The process_reimbursement tool accepts amount and details, and internally enforces the threshold: amounts <$500 are auto-disbursed and the tool returns a success confirmation; amounts >$500 cause the tool to create a pending approval request and return a status indicating manager review is pending.
C) Provide two tools: auto_reimburse (hard-coded limit of $500) and request_manager_approval.
Include detailed system prompt instructions telling the agent to check the amount and call the appropriate tool. Add a PostToolUse hook that logs which tool was called for auditing.
D) Implement the threshold check in a PreToolUse hook that inspects the amount parameter before process_reimbursement executes. If the amount exceeds $500, the hook modifies the tool call to add a requires_approval: true flag, which the tool checks before disbursing.
3. After integrating a local MCP server providing code analysis tools (analyze_dependencies, find_dead_code, calculate _complexity), you verify the server is healthy and tools appear in the tools/list response. However, you observe that the agent consistently uses Grep to search for import statements instead of calling analyze_dependencies -even when users explicitly ask about "code dependencies." Examining tool definitions reveals:
MCP: analyze_ dependencies - "Analyzes dependency graph"
Built-in: Grep - "Search file contents for a pattern using regular
expressions. Returns matching lines with line numbers and surrounding
context."
What's the most effective approach to improve the agent's selection of MCP tools?
A) Split analyze_dependencies into granular tools ( list_imports, resolve_transitive_deps, detect_circular_deps) so each has a focused purpose less likely to overlap with Grep.
B) Remove Grep from available tools when the MCP server is connected to eliminate functional overlap.
C) Add routing instructions to the system prompt specifying that dependency-related questions should use MCP tools rather than Grep.
D) Expand MCP tool descriptions to detail capabilities and outputs - e.g., "Builds dependency graph showing direct imports, transitive dependencies, and cycles."
4. 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) Have the coordinator pre-classify each analysis request before passing instructions to the document analysis agent
C) Keep the single tool but add an analyze_type enum parameter requiring explicit selection between extraction, summarization, and verification modes
D) Split the generic tool into purpose-specific tools - extract_data_points, summarize_content, verify_claim_against_source - each with defined input/output contracts
5. Your multi-agent research pipeline crashed after processing12 of 28 documents. The web search agent had identified relevant sources, the document analyzer had partially completed extraction, and the synthesizer had begun pattern identification. You need to resume processing without repeating work or losing fidelity of prior findings. What state management approach best balances information fidelity with context efficiency when restoring agent state?
A) Have each agent persist a structured export to a known location. On resume, the coordinator loads the manifest and injects relevant state into agent prompts.
B) Index all agent outputs in a shared vector store. When resuming, each agent queries the store using semantic search to retrieve relevant prior findings.
C) Persist the coordinator's conversation log containing all task delegations and responses, providing this to agents when resuming.
D) Have each agent maintain its own persistent state file and reload it independently at the start of each session.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: B | Question # 3 Answer: D | Question # 4 Answer: D | Question # 5 Answer: A |
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