CCA-F 試験問題を無料オンラインアクセス

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

A company is building its first production Claude application. Which principle should guide the initial deployment?

• A.Start with a simple design and iteratively evaluate improvements.
• B.Optimize only for response speed.
• C.Disable monitoring to reduce costs.
• D.Maximize prompt complexity immediately.

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.
A developer asks the agent to investigate why a specific API endpoint intermittently returns 500 errors. The codebase has 200+ files and the developer doesn't know which components are involved. The agent must trace the error through routing, middleware, business logic, and database layers. What task decomposition approach would be most effective?

• A.Define a fixed sequence of investigation steps upfront - grep for error patterns, then read error handlers, then check database queries, then examine middleware - executing each step regardless of intermediate findings.
• B.Have the agent first create a comprehensive plan mapping all code paths through the endpoint before beginning any file exploration or code reading.
• C.Run parallel worker agents that simultaneously investigate all four layers, then synthesize their findings to identify where the error originates.
• D.Have the agent dynamically generate investigation subtasks based on what it discovers at each step, adapting its exploration plan as new information about the error path emerges.

A company wants Claude to summarize thousands of support tickets efficiently. Which design scales BEST?

• A.Increase temperature.
• B.Process tickets individually and combine summaries.
• C.Send all tickets in one request.
• D.Remove system prompts.

Users report that final reports sometimes lack depth on specific subtopics. Investigation shows that the document analysis agent frequently identifies gaps - for instance, noting "the retrieved sources discuss API authentication but lack details on token refresh patterns" - but under the current strict pipeline, this insight isn't actionable since search has already completed. What's the most effective architectural change?

• A.Add a research planning agent before the search phase that decomposes topics into specific sub- questions.
• B.Have the coordinator review analysis output for gap indicators and re-invoke search with gap- informed queries when gaps are detected.
• C.Have the synthesis agent attach confidence scores to each section and flag areas with insufficient coverage for manual review.
• D.Have the analysis agent report specific gaps to the coordinator, which triggers targeted searches and re-invokes analysis until sufficient.