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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Prompt Engineering & Structured Output	20%	- Tool-augmented prompting 1. Validation and retry loops 2. Tool-use driven reasoning patterns - Instruction design 1. Deterministic output formatting (e.g., JSON) 2. Few-shot prompting strategies
Agentic Architecture & Orchestration	27%	- Agentic loops & lifecycle design 1. Stop reason handling and control flow 2. Tool use loop execution (request → tool_use → result → next step) - Multi-agent orchestration 1. Coordinator / sub-agent patterns 2. Parallel task decomposition
Tool Design & MCP Integration	18%	- Tool interface design 1. Clear tool descriptions and boundaries 2. Structured tool input/output schemas - Model Context Protocol (MCP) 1. MCP server integration patterns 2. Tool selection and routing strategies
Context Management & Reliability	15%	- System reliability 1. Escalation strategies (fail vs retry vs human) 2. Error propagation handling - Context window optimization 1. "Lost in the middle" mitigation strategies 2. Managing long conversation degradation
Claude Code Configuration & Workflows	20%	- Claude Code configuration 1. Project-level vs user-level configuration 2. CLAUDE.md hierarchy and scoping - CI/CD and workflow integration 1. Command vs plan mode usage 2. Automated pipeline integration

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q88-Q93):

NEW QUESTION # 88
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. Process the refund via process_refund to resolve the underlying issue, then inform them it's complete
B. Call escalate_to_human immediately to honor the customer's request
C. Ask what specifically hasn't worked in previous attempts before deciding whether to escalate or resolve automatically
D. Acknowledge frustration, inform them this is resolvable now, and offer to complete it or escalate

Answer: D

Explanation:
The agent should address the customer's frustration while making clear that the issue can be resolved immediately. Offering to complete the refund or escalate respects the user's preference and maintains control over resolution without unnecessary delays or forced escalation.

NEW QUESTION # 89
An agentic loop is the core execution pattern for Claude-based agents. When building an agent, how should the loop reliably determine when to terminate and return a final response to the user?

A. Check the stop_reason field of the API response and exit the loop when it equals end_turn.
B. Parse the assistant's natural language text output to check for keywords like 'task complete' or 'l am done'.
C. Set a hard maximum iteration cap of 10 loops to prevent infinite execution and terminate when reached.
D. Monitor the token count of the conversation and stop when it approaches the context window limit.

Answer: A

Explanation:
The stop_reason field is the only reliable signal for controlling the agentic loop. 'tool_use' indicates the loop must continue to execute tools, while 'end_turn' indicates Claude has finished reasoning and the loop should exit. Parsing natural language or setting arbitrary iteration caps are heavily tested anti-patterns.

NEW QUESTION # 90
A custom subagent named security-reviewer is defined in . claude/agents/. How does this subagent gain access to a project's deployed skills?

A. The subagent must execute the /load_skills command upon initialization.
B. Built-in explorer agents cascade all available workspace skills to newly spawned subagents.
C. Skills must be explicitly listed in the skills field of the custom subagent's markdown definition.
D. Subagents automatically inherit all skills currently loaded by the main coordinator agent.

Answer: C

Explanation:
Subagents start with a clean context and do not automatically inherit skills from the parent or main conversation. To grant a custom subagent access to skills, they must be explicitly listed in the 'skills' field of the subagent's configuration frontmatter.

NEW QUESTION # 91
What is the primary architectural advantage of using glob-pattern rules in a . claude/rules/ file rather than placing a CLAUDE. md file in a subdirectory?

A. Glob patterns allow conventions to apply to files by type regardless of their directory location, which is essential for conventions that span multiple directories.
B. Glob patterns disable Claude's semantic inference, forcing it to use exact keyword matching for all prompts.
C. Glob patterns bypass the Model Context Protocol (MCP) server requirements for fetching dynamic rules.
D. Glob patterns automatically apply the rules to the global system-level /etc/c1aude/CLAUDE .md configuration.

Answer: A

Explanation:
The advantage of glob-pattern rules over directory-level CLAUDE.md files is that they can apply conventions to files spread across the codebase by type regardless of directory location (e.g., test files located next to components). Subdirectory CLAUDE.md files only apply to that specific directory and its children.

NEW QUESTION # 92
When processing a batch of 10,000 documents via the Message Batches API, 45 requests fail due to context window limits. What is the recommended failure handling strategy?

A. Resubmit the entire batch of 10,000 requests to guarantee correct ordering.
B. Resubmit only the failed documents (identified by their custom_id) after modifying them, such as chunking oversized documents.
C. Ignore the failures, as the API inherently guarantees a 99% success SLA.
D. Switch immediately to the synchronous API to retry the failed documents.

Answer: B

Explanation:
Batch failures should be handled by identifying the specific failed requests using their custom_id, modifying them appropriately (e.g., chunking oversized documents to fit context limits), and resubmitting only those failed items.

NEW QUESTION # 93
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