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Anthropic CCA-F Exam Syllabus Topics:

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

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Anthropic Claude Certified Architect Foundations (CCA-F) 認定 CCA-F 試験問題 (Q68-Q73):

質問 # 68
You are designing a prompt to extract structured data from unstructured documents. You decide to use tool_use with a strict JSON schem a. What specific guarantee does this approach provide?

A. It guarantees both structural compliance and the semantic correctness of the extracted data.
B. It eliminates the need for validation-retry loops.
C. It guarantees the model will not hallucinate missing information.
D. It eliminates JSON syntax errors and guarantees structural compliance, but does not prevent semantic errors.

正解：D

解説：
Using tool_use with JSON schemas guarantees structural compliance (all required fields present, valid types, syntax correct) but does NOT guarantee semantic correctness (the actual values may still be inaccurate or hallucinated). You still need semantic validation rules.

質問 # 69
The synthesis agent receives summarized findings from the web search and document analysis agents, then passes a consolidated summary to the report generator. During testing, you discover the generated reports make factual claims without proper citations - the report generator cannot attribute statements to their original sources because that metadata was lost during the summarization steps. What's the most effective approach to ensure proper source attribution in the final reports?

A. Have each agent output structured data separating content summaries from source metadata (URLs, document names, page numbers).
B. Instruct the synthesis agent to embed source references inline within its summary text using a consistent citation format.
C. Skip summarization and pass full raw outputs from web search and document analysis directly to the report generator.
D. Have the report generator query the web search agent to re-locate sources for claims in the final report.

正解：A

解説：
Structured outputs that keep summaries separate from source metadata preserve attribution throughout the agent workflow. This allows the synthesis and report generation stages to carry forward URLs, document names, page numbers, and other citation details without losing the link between claims and their original sources.

質問 # 70
When configuring a project-level Jira Model Context Protocol (MCP) server for a development team, what is the required method for securely managing authentication credentials?

A. Hardcode the API tokens directly in the .mcp.json file to ensure all team members can access the integration.
B. Store the credentials in an encrypted secrets .json file referenced by the CLAUDE .md configuration.
C. Configure the server in the user-scoped ~/ . claude. json file so credentials remain local to each developer.
D. Define the server in the project-scoped .mcp.json file using environment variable expansion like ${JIRA_TOKEN}.

正解：D

解説：
Project-level MCP configurations that are shared via version control must use the .mcp.json file. To prevent leaking credentials, environment variable expansion syntax (e.g., ${JIRA TOKEN}) is required so the secrets remain in the local environment and out of the codebase.

質問 # 71
When orchestrating complex workflows using the Claude Agent SDK, in which scenario is dynamic adaptive decomposition preferred over fixed sequential prompt chaining?

A. When executing open-ended investigation tasks where intermediate discoveries dictate the next required steps.
B. When performing predictable, multi-aspect code reviews where the sequence of analysis is entirely static.
C. When validating a strictly structured JSON extraction against predefined business rules.
D. When executing a daily technical debt audit across a predefined list of target directories.

正解：A

解説：
Dynamic adaptive decomposition is the optimal strategy for unpredictable, open-ended tasks (like investigations) where the agent must decide its next steps based on intermediate findings. Prompt chaining (fixed sequential pipelines) is better suited for predictable, linear workflows with static sequences.

質問 # 72
Which of the following statements correctly describe the behavior of session management commands in Claude Code? Choose 2 correct answers.

A. Option C
B. Option B
C. Option A
D. Option D

正解：C、D

解説：

質問 # 73
......

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