CCA-F 試験問題を無料オンラインアクセス

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.
An engineer used the agent yesterday to analyze a legacy authentication module, identifying two distinct refactoring approaches: extracting a microservice versus refactoring in-place. Today, they want to explore both approaches in depth - having the agent propose specific code changes for each - before deciding which to implement. What's the most effective way to structure this exploration?

• A.Resume yesterday's session to explore the first approach, then start a new session for the second, manually recreating the original context.
• B.Resume yesterday's session and explore both approaches sequentially within the same conversation thread.
• C.Use fork_session to create two branches from yesterday's analysis, exploring one approach in each fork.
• D.Start two fresh sessions, manually providing a summary of yesterday's analysis findings to establish context.

Your get_portfolio_value tool returns the total value of a user's investment portfolio. You're deciding between returning a structured JSON object with explicit fields versus returning the information as a formatted text string. What is the primary advantage of using structured output with defined fields?

• A.Structured JSON consumes significantly fewer tokens than natural language, substantially reducing API costs.
• B.Structured JSON is processed deterministically by the model, significantly improving accuracy when extracting values.
• C.The agent can reliably extract specific values without parsing free-form text, reducing errors in subsequent operations.
• D.JSON schemas automatically validate that the underlying API returned correct data before the agent processes it.

A customer returns 4 hours after the initial session about the same billing dispute. The previous
32-turn session contains lookup_order results showing "Status: PENDING, Expected resolution:
24-48 hours." In testing, you observe that when resuming sessions with stale tool results, the agent often references the outdated data in responses (e.g., "I see your refund is still being processed") even after subsequent fresh tool calls return different information. What approach most reliably handles returning customers?

• A.Resume with full history and configure the agent to automatically re-call all previously-used tools at session start to ensure data freshness.
• B.Start a new session, inject a structured summary of the previous interaction (issue type, actions taken, resolution status), then make fresh tool calls before engaging.
• C.Resume with full history but filter out previous tool_result messages before resuming, keeping only the human/assistant turns so the agent must re-fetch needed data.
• D.Resume with full history and add a system prompt instruction telling the agent to always prefer the most recent tool results when multiple calls to the same tool exist in context.

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 need to add a date validation check ensuring event dates are in the future. This requires adding a conditional statement to one existing function in a single file. What is the most appropriate approach?

• A.Start with extended thinking mode enabled to ensure thorough reasoning about the validation logic.
• B.Enter plan mode to analyze how the validation might impact other parts of the reservation flow.
• C.Enter plan mode first to create a detailed implementation strategy before making the change.
• D.Use direct execution to make the change.

Your update_user_profile tool accepts a user_id (required) and an optional fields_to_update object. In testing, Claude frequently omits user_id or passes incorrectly structured data. What is most critical for helping Claude understand what parameter values to provide?

• A.Verbose parameter names encoding format hints, such as user_id_string_uuid_format
• B.Detailed error responses explaining why invalid parameter values were rejected
• C.Clear parameter descriptions explaining expected format, such as "user_id: UUID of the user to update (required)"
• D.Strict JSON Schema type constraints marking user_id as required and defining fields_to_update as an object type