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Anthropic CCA-F Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Claude Code Workflows & Configuration | 20% | - Claude Code operational patterns
|
| Topic 2: Agentic Architecture & Orchestration | 27% | - Agentic loop design and execution lifecycle
|
| Topic 3: Tool Design & MCP Integration | 18% | - Model Context Protocol (MCP)
|
| Topic 4: Prompt Engineering & Structured Output | 20% | - Reliable structured generation
|
| Topic 5: Context Management & Reliability | 15% | - Long-context optimization
|
Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions:
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 asks your agent to identify untested code paths in a legacy payment processing module spanning 45 files. After reading the first 8 source files, the agent's responses are becoming noticeably less accurate - it's forgetting previously discussed code patterns and hasn't yet located all test files or traced critical payment flows. What's the most effective approach to complete this investigation?
- A. Switch to using Grep to search for specific function names instead of reading full files, reducing the content loaded into context for remaining exploration.
- B. Document all current findings in a summary report, clear context completely, then use that report as the sole reference for continuing the investigation.
- C. Clear context with /clear, then selectively re-read only the most critical files discovered so far, writing key findings to a scratchpad file that persists between context resets.
- D. Spawn subagents to investigate specific questions (e.g., "find all test files for payment processing," "trace refund flow dependencies") while the main agent coordinates findings and preserves high-level understanding.
Correct Answer: D 🗳️
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An organization wants predictable outputs for automated invoice classification. Which API parameter should generally be LOWER?
- A. Context window
- B. Prompt length
- C. Max tokens
- D. Temperature
Correct Answer: D 🗳️
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A healthcare company processes long clinical reports. Some exceed Claude's practical context requirements. What is the BEST architectural approach?
- A. Chunk documents before processing.
- B. Ignore the excess text.
- C. Increase temperature.
- D. Randomly remove paragraphs.
Correct Answer: A 🗳️
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Your agent is handling a billing dispute. After calling get_customer and lookup_order, it identifies that the dispute involves a promotional pricing error requiring manager approval - beyond the agent's authorization level. How should the workflow handle this mid-process escalation?
- A. Attempt the refund with process_refund anyway, escalating only if the system rejects the transaction.
- B. Persist the complete conversation and tool response history to a database, then call escalate_to_human with a reference ID.
- C. Compile a structured handoff with customer details, order info, and the identified issue before calling escalate_to_human.
- D. Call escalate_to_human passing only the customer's original message.
Correct Answer: C 🗳️
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A retail organization observes that Claude occasionally gives different wording when summarizing identical customer reviews. The summaries remain accurate. What is the MOST likely explanation?
- A. Retrieval failed.
- B. Claude is malfunctioning.
- C. Large language models are probabilistic.
- D. The API returned cached responses.
Correct Answer: C 🗳️
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