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Anthropic CCA-F Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Context Management & Responsible AI | 15% | - Context window optimization
|
| Topic 2: Agentic Architecture & Orchestration | 27% | - Anthropic Agent SDK usage
|
| Topic 3: Tool Design & MCP Integration | 18% | - Model Context Protocol (MCP)
|
| Topic 4: Claude Code Configuration & Workflows | 20% | - CI/CD and development integration
|
| Topic 5: Prompt Engineering & Structured Output | 20% | - Advanced prompting techniques
|
Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions:
1. An organization wants predictable outputs for automated invoice classification. Which API parameter should generally be LOWER?
A) Max tokens
B) Context window
C) Prompt length
D) Temperature
2. A customer writes: "I've been going back and forth on this return for days. I just want to speak to someone who can actually help me." The agent has confirmed via lookup_order that the return is straightforward - within policy and eligible for immediate processing. What should the agent do?
A) Acknowledge frustration, inform them this is resolvable now, and offer to complete it or escalate
B) Ask what specifically hasn't worked in previous attempts before deciding whether to escalate or resolve automatically
C) Process the refund via process_refund to resolve the underlying issue, then inform them it's complete
D) Call escalate_to_human immediately to honor the customer's request
3. 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 In testing, you observe that when resuming sessions with stale tool results, the agent often references the outdated data in responses (e.g., "I see your refund is still being processed") even after subsequent fresh tool calls return different information.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) 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.
C) 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.
D) Resume with full history and configure the agent to automatically re-call all previously-used tools at session start to ensure data freshness.
4. After the web search agent finds 25 sources (120K tokens of raw content), the document analysis agent extracts key insights (15K tokens), and the synthesis agent produces a coherent narrative draft (3K tokens), the coordinator must pass context to the report generation agent for the final output with proper source citations. What context-passing strategy provides the best balance of completeness and efficiency?
A) Pass a condensed summary of all prior stages that preserves the main findings and attributes them to sources by name only.
B) Pass the synthesis draft along with a structured source index that maps key claims to their source URLs and relevant excerpts.
C) Pass only the synthesis draft and have a separate post-processing pipeline match claims to sources and insert citations after the report is generated.
D) Pass the full accumulated context from all prior agents.
5. An architect needs Claude to produce structured JSON that downstream software can parse automatically. Which prompting strategy is BEST?
A) Explicitly specify the required JSON schema and formatting rules.
B) Use multiple unrelated examples.
C) Increase maximum output tokens only.
D) Ask Claude to "respond normally."
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A | Question # 3 Answer: C | Question # 4 Answer: B | Question # 5 Answer: A |



