A chatbot frequently receives greetings, policy questions, and technical support requests. Which architecture improves maintainability?

• A. Disable retrieval.
• B. One prompt for every scenario.
• C. Maximum temperature.
• D. Prompt routing based on request type.

解説: (Fast2test メンバーにのみ表示されます)

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.
Your team frequently migrates React components to Vue. You've written a step-by-step workflow for Claude Code to follow during each migration, and you want every developer on the team to invoke it by typing /migrate-component. The workflow should stay in sync as the team iterates on it. Where should you place the skill file?

• A. In ~/.claude/skills/migrate-component/SKILL.md on each developer's machine
• B. As a detailed instruction block in the project's root CLAUDE.md file
• C. In the project's.claude/settings.json using a skillOverrides entry to register and define the workflow
• D. In .claude/skills/migrate-component/SKILL.md at the project root, committed to version control

解説: (Fast2test メンバーにのみ表示されます)

A customer raises three separate issues during one session: a refund inquiry (turns 1-15), a subscription question (turns 16-30), and a payment method update (turns 31-45). At turn 48, the customer asks "What happened with my refund?" The conversation is approaching context limits.
What strategy best maintains the agent's ability to address all issues throughout the session?

• A. Summarize earlier turns into a narrative description, preserving full message history only for the active issue.
• B. Extract and persist structured issue data (order IDs, amounts, statuses) into a separate context layer.
• C. Rely on MCP tools to re-fetch relevant information on demand when the customer references earlier issues.
• D. Implement sliding window context that retains the most recent 30 turns.

解説: (Fast2test メンバーにのみ表示されます)

The synthesis agent completes its initial pass but flags that three key research questions remain unanswered because the web search and document analysis agents didn't find relevant information on those specific subtopics. The coordinator currently proceeds directly to report generation, producing reports with incomplete coverage. What change would most effectively improve research completeness?

• A. Give the synthesis agent direct access to web search tools so it can autonomously fill knowledge gaps without returning control to the coordinator.
• B. Have the report generation agent note which research questions couldn't be answered, so users understand the limitations of the final output.
• C. Have the coordinator evaluate synthesis output for gaps, then re-delegate to web search and document analysis with targeted queries before invoking synthesis again.
• D. Increase the initial breadth of queries sent to web search and document analysis to reduce the probability of missing relevant information.

解説: (Fast2test メンバーにのみ表示されます)

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.

解説: (Fast2test メンバーにのみ表示されます)