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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Agentic Architecture & Orchestration	27%	- System orchestration patterns 1. Task decomposition strategies 2. Hub-and-spoke agent systems - Agentic loop design and execution lifecycle 1. Multi-agent coordination and delegation patterns 2. Tool use decision flow (tool_use vs end_turn)
Topic 2: Claude Code Workflows & Configuration	20%	- Claude Code operational patterns 1. Plan mode vs execution mode 2. CI/CD and workflow integration
Topic 3: Tool Design & MCP Integration	18%	- Model Context Protocol (MCP) 1. Tool schema design 2. MCP client/server integration patterns
Topic 4: Context Management & Reliability	15%	- Long-context optimization 1. Context window management 2. Reliability and retry strategies
Topic 5: Prompt Engineering & Structured Output	20%	- Reliable structured generation 1. Schema-guided outputs 2. Prompt patterns for agents

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q89-Q94):

NEW QUESTION # 89
Why is it heavily recommended to use Agent SDK hooks rather than prompt instructions to enforce critical business rules in a application?

A. Hooks inherently consume zero tokens from the context window.
B. Hooks automatically implement strict JSON schema validation for all tool_use calls.
C. Prompt instructions cannot be modified without restarting the entire MCP server architecture.
D. Hooks provide deterministic guarantees, whereas prompt instructions rely on probabilistic compliance and carry a non-zero failure rate.

Answer: D

Explanation:
The core distinction is that hooks run as programmatic code, providing deterministic, 100% reliable enforcement for business policies. Prompts rely on the LLM's probabilistic pattern matching, meaning the model can and occasionally will ignore critical instructions.

NEW QUESTION # 90
The web search agent has gathered several relevant sources for a research topic. The document analysis agent now needs to examine these sources. How does information typically flow between these two specialized subagents?

A. The coordinator agent receives the web search agent's output and includes relevant findings in the prompt when invoking the document analysis agent.
B. The agents communicate through an event-driven message queue, with the document analysis agent subscribing to web search completion events.
C. Both agents access a shared memory store where the web search agent writes findings and the document analysis agent reads them.
D. The web search agent directly invokes the document analysis agent, passing the discovered sources as parameters.

Answer: A

Explanation:
In a coordinated multi-agent pipeline, the coordinator mediates information flow. It collects outputs from the web search agent and includes the relevant findings in the prompt when invoking the document analysis agent, ensuring proper sequencing and context without tightly coupling the subagents.

NEW QUESTION # 91
What configuration is strictly required for a coordinator agent to be able to spawn subagents?

A. The tool_choice parameter must be set to 'auto'.
B. The agent must be executed in plan mode rather than direct execution.
C. A PreToolUse hook must be registered to manage process limits.
D. The coordinator's allowedTools array must explicitly include the Task tool.

Answer: D

Explanation:
The Task tool is the mechanism used for spawning subagents. For a coordinator to invoke subagents, its allowedTools configuration must explicitly include 'Task'.

NEW QUESTION # 92
When designing a human review workflow with limited reviewer capacity, which of the following items should be prioritized for human review? (Choose 2 correct answers)

A. Randomly selected extractions from documents categorized as having 99% historical accuracy.
B. Extractions involving ambiguous or contradictory source documents.
C. Extractions where the model reports low field-level confidence.
D. Documents where the tool_choice was set to "auto".

Answer: B,C

Explanation:
When reviewer capacity is limited, human review should be prioritized and routed toward items with low model confidence and tasks involving ambiguous, contradictory, or borderline source material where human judgment is strictly required.

NEW QUESTION # 93
An agent queries multiple external APIs that return dates in drastically different formats (e.g., Unix timestamps vs ISO 8601). What is the architecturally correct way to normalize this data before the agent processes it?

A. Implement a PostToolUse hook that intercepts the heterogeneous tool results and transforms them into a standardized format before appending to context.
B. Provide few-shot examples in the system prompt showing the agent successfully translating Unix timestamps.
C. Set the tool_choice parameter to strictly enforce ISO 8601 schema outputs.
D. Use a PreToolUse hook to dynamically modify the prompt, instructing the agent to convert all dates to ISO 8601.

Answer: A

Explanation:
PostToolUse hooks are specifically designed to intercept tool results after they execute but before they are passed back to the model. This makes them ideal for normalizing heterogeneous data formats (like standardizing dates or status codes) so the agent processes consistent data.

NEW QUESTION # 94
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