You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JSON schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.
Your extraction system processes two document types: standard monthly reports, which are archived after processing, and urgent exception reports, which must trigger business alerts within
30 minutes of receipt. Both use the same JSON schema. You want to minimize API costs while meeting the latency requirements.
How should you architect the processing pipeline?

• A. Submit all documents to the Message Batches API with custom_id values for tracking. When results arrive, immediately process urgent documents and trigger delayed alerts for exceptions.
• B. Queue all documents and submit hourly batches, flagging urgent documents for expedited handling when batch results return.
• C. Submit all documents to the real-time Messages API to ensure consistent processing latency across document types.
• D. Route standard reports to the Message Batches API for 50% cost savings, and route urgent exception reports to the real-time Messages API.

解説: (Fast2test メンバーにのみ表示されます)

Your send_notification tool calls third-party messaging APIs. When these services time out during delivery, you cannot determine whether the message was actually sent. Currently, the tool returns is_error: true with a generic "Notification failed" message for all timeouts. Production monitoring reveals agents automatically retry these failures, frequently causing users to receive duplicate notifications. How should you modify the error response?

• A. Return is_error: true with the original message content echoed back.
• B. Return is_error: true with a message encouraging retry: "Delivery service temporarily unavailable.
  Please retry the notification."
• C. Return is_error: true with a message communicating uncertainty: "Timeout - status unknown.
  Message may have been sent. Avoid retry."
• D. Return is_error: true with a structured field retry_safe: true for timeouts, distinguishing them from permanent failures that should not be retried.

解説: (Fast2test メンバーにのみ表示されます)

You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JavaScript Object Notation (JSON) schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.
Your extraction system implements automatic retries when validation fails. On each retry, the specific validation error is appended to the prompt. This retry-with-error-feedback approach resolves most failures within 2? attempts.
For which failure pattern would additional retries be LEAST effective?

• A. The model extracts citation counts as locale-formatted strings ("1,234") when the schema requires integers.
• B. The model extracts keywords as a nested object organized by category when the schema requires a flat array of strings.
• C. The model extracts dates as ISO 8601 datetime strings ("2023-03-15T00:00:00Z") when the schema requires only the date portion (YYYY-MM-DD).
• D. The model extracts "et al." for co-authors when the full list exists only in an external document not in the input.

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)

Your control_device tool manages smart home devices through external APIs. When a device doesn't respond within the timeout period, the tool returns an error. Production logs show that the agent simply tells users "the device is not responding" without offering helpful next steps. Which error response structure would best enable the agent to provide useful follow-up?

• A. Set is_error: true with a structured technical error containing the device ID, timeout duration, and raw API response code for debugging purposes.
• B. Set is_error: false with an optimistic message indicating the command was dispatched successfully but device acknowledgment is still pending.
• C. Set is_error: true with a brief "Device offline" message and provide a separate tool the agent can call to retrieve context-specific troubleshooting suggestions.
• D. Set is_error: true with a message explaining the likely cause and suggesting troubleshooting steps the agent can offer the user.

解説: (Fast2test メンバーにのみ表示されます)