試験CCAR-F トピック1 問題47 スレッド
Anthropic CCAR-Fのリアル試験問題集
問題 #: 47
トピック #: 1
問題 #: 47
トピック #: 1
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.
Your code review assistant needs to analyze pull requests and provide feedback on three aspects: code style compliance, potential security issues, and documentation completeness. Each aspect requires reading files, running analysis tools, and generating a report section. The review process follows the same three-step workflow for every PR.
Which task decomposition pattern is most appropriate for this workflow?
Your code review assistant needs to analyze pull requests and provide feedback on three aspects: code style compliance, potential security issues, and documentation completeness. Each aspect requires reading files, running analysis tools, and generating a report section. The review process follows the same three-step workflow for every PR.
Which task decomposition pattern is most appropriate for this workflow?
おすすめの解答：C 解答を投票する
Prompt chaining is appropriate because the workflow consists of predictable, fixed subtasks that apply to every pull request. The system can run a focused style-compliance analysis, then a security analysis, then a documentation review, and finally synthesize the three results into a consistent report.
Anthropic defines prompt chaining as decomposing a task into a sequence of steps in which each call handles a smaller component. It is recommended when a task can be cleanly divided into fixed subtasks, trading additional latency for better focus and accuracy. Intermediate checks can also be inserted between stages to confirm that each report section meets its requirements. ( https://www.anthropic.com/engineering/building- effective-agents ) Option A concentrates all considerations into one call, making it easier for one aspect to receive inadequate attention. Option B is unnecessary because orchestrator-workers is intended for complex work where the required subtasks cannot be predicted in advance. Here, the three review dimensions are already known and remain constant. Option D solves a different problem: routing is appropriate when inputs belong to distinct categories that require different downstream processes.
Although the three analyses could potentially be parallelized for lower latency, the option that accurately represents the stated repeatable decomposition is prompt chaining with final synthesis.
Official references/topics: Prompt Chaining, Fixed Subtasks, Intermediate Validation, Workflow Selection.
Anthropic defines prompt chaining as decomposing a task into a sequence of steps in which each call handles a smaller component. It is recommended when a task can be cleanly divided into fixed subtasks, trading additional latency for better focus and accuracy. Intermediate checks can also be inserted between stages to confirm that each report section meets its requirements. ( https://www.anthropic.com/engineering/building- effective-agents ) Option A concentrates all considerations into one call, making it easier for one aspect to receive inadequate attention. Option B is unnecessary because orchestrator-workers is intended for complex work where the required subtasks cannot be predicted in advance. Here, the three review dimensions are already known and remain constant. Option D solves a different problem: routing is appropriate when inputs belong to distinct categories that require different downstream processes.
Although the three analyses could potentially be parallelized for lower latency, the option that accurately represents the stated repeatable decomposition is prompt chaining with final synthesis.
Official references/topics: Prompt Chaining, Fixed Subtasks, Intermediate Validation, Workflow Selection.
Kawase 2026-10-07 07:45:30
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