CCA-F日本語参考 & CCA-F技術試験

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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Agentic Architecture & Orchestration	27%	- Agent design patterns 1. Hub-and-spoke multi-agent systems 2. Agent loops and control flow - Anthropic Agent SDK usage 1. Task spawning and tool management 2. Session state and context handling
Tool Design & MCP Integration	18%	- Model Context Protocol (MCP) 1. Tools, resources, and prompts integration 2. MCP server and client setup - Tool definition and best practices 1. Error handling and validation 2. Tool descriptions and selection logic
Prompt Engineering & Structured Output	20%	- Advanced prompting techniques 1. Few-shot and chain-of-thought prompting 2. System prompts and role framing - Structured data generation 1. JSON schema enforcement 2. Output validation and reliability
Claude Code Configuration & Workflows	20%	- Configuration files and structure 1. Custom commands and workflows 2. CLAUDE.md and rules system - CI/CD and development integration 1. Pipeline automation and review 2. Plan mode vs direct execution
Context Management & Responsible AI	15%	- Context window optimization 1. Token management and truncation strategies 2. Context retention and summarization - Safety and compliance 1. Constitutional AI principles 2. Refusal handling and risk mitigation

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CCA-F技術試験 & CCA-F試験参考書

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Anthropic Claude Certified Architect Foundations (CCA-F) 認定 CCA-F 試験問題 (Q41-Q46):

質問 # 41
You are building a multi-agent research system using the Claude Agent SDK. A coordinator agent delegates to specialized subagents: one searches the web, one analyzes documents, one synthesizes findings, and one generates reports. The system researches topics and produces comprehensive, cited reports.
When researching "renewable energy adoption," the web search agent returns recent statistics (2024: 35% adoption) while the document analysis agent extracts data from internal reports (2021: 18% adoption). The synthesis agent incorrectly flags these as contradictory sources rather than recognizing the data shows growth over time. What change would best enable the synthesis agent to correctly interpret such temporal differences?

A. Configure the web search agent to only return results from the past 6 months.
B. Instruct the synthesis agent to always treat the most recent data as authoritative and place older findings in a separate historical appendix.
C. Add a conflict resolution agent that automatically discards older data when newer data exists for the same metric.
D. Require subagents to include publication or data collection dates in their structured outputs.

正解：D

解説：
Temporal metadata lets the synthesis agent distinguish measurements from different time periods and interpret 18% in 2021 and 35% in 2024 as a trend rather than a contradiction.

質問 # 42
You are using Claude Code to accelerate software development. Your team uses it for code generation, refactoring, debugging, and documentation. You need to integrate it into your development workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.
You're implementing a new payment processing module that must follow your project's established patterns for database transactions, error handling, and audit logging. You've identified three existing modules that exemplify these patterns: db_utils.py, error_handlers.py, and audit_logger.py. This is a one-off integration task - these patterns are well-documented in your team wiki and don't need additional project-level documentation. What's the most effective approach?

A. Describe the patterns from the three modules in natural language in your prompt, explaining the transaction handling approach, error format, and logging conventions Claude should follow.
B. Ask Claude to explore your codebase to find and understand the transaction, error handling, and logging patterns before generating the new module.
C. Use @ references to include the three modules directly in your prompt, giving Claude concrete code examples of the patterns to follow.
D. Add documentation of each pattern to your CLAUDE.md file, establishing them as project conventions that Claude will apply automatically.

正解：C

解説：
This is a one-off task, so directly attaching the relevant files gives Claude concrete, authoritative examples without permanently expanding CLAUDE.md. Claude Code supports @ references specifically for bringing files or directories into the current task's context.

質問 # 43
A developer at quicktechie.com wants to configure Claude Code to always use their preferred Vim keybindings, without enforcing this standard on the rest of their team. Where must this configuration be placed?

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

正解：C

解説：
Personal preferences (like editor settings or Vim keybindings) must go in the user-level configuration located at ~/.claude/CLAUDE.md. Placing them in the project-level .claude/CLAUDE.md would share them via version control and force them onto the entire team, which is an anti-pattern.

質問 # 44
Your application has test files spread throughout the codebase next to the components they test. You want Claude to automatically apply specific testing conventions whenever it generates or edits a test file. Which configuration method is most maintainable and deterministic?

A. Define an MCP server resource to fetch testing standards dynamically.
B. Place a separate CLAUDE. md file in every subdirectory that contains test files.
C. Create a rule file in. claude/rules/testing.md With YAML frontmatter specifying paths: [ . test. tsx"].
D. Consolidate all testing conventions in the root CLAUDE .md and rely on Claude's inference to apply them.

正解：C

解説：
Using .claude/rules/ files with glob patterns in the paths field allows conventions to be automatically and conditionally applied based on file paths. This ensures the rules load deterministically whenever matching files are edited, without overloading the context window for unrelated tasks.

質問 # 45
A developer is using a multi-agent system to analyze a massive legacy codebase. The coordinator agent is running out of context window space because the search tool returns verbose file contents and exploration noise. What is the best pattern to mitigate this context degradation?

A. Delegate the verbose file-by-file exploration to a subagent, which then returns only a synthesized summary of its findings back to the coordinator's context.
B. Force the coordinator agent to use the Bash tool to run grep manually instead of reading files.
C. Switch from dynamic adaptive decomposition to static prompt chaining to force a linear review path.
D. Share the full coordinator conversation history with all subagents to ensure maximum context propagation.

正解：A

解説：
Subagent delegation is a core mitigation for context degradation. By delegating verbose exploration tasks to subagents, the subagent's isolated context absorbs the exploration noise, and only the clean, synthesized results are returned to the coordinator.

質問 # 46
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