Your agent achieves a low first-contact resolution rate because it attempts to autonomously handle complex policy exceptions, while simultaneously escalating straightforward tasks. What is the most effective approach to improve this escalation calibration?

• A.Add explicit escalation criteria to the system prompt with few-shot examples demonstrating when to escalate versus resolve autonomously.
• B.Deploy a separate classifier model to predict which requests need escalation before the main agent begins.
• C.Require the agent to self-report a confidence score (1-10) and route to humans when confidence falls below 7.
• D.Implement sentiment analysis to detect frustration levels and automatically escalate when they are high.

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Which statement BEST describes Retrieval-Augmented Generation?

• A.It permanently retrains Claude.
• B.It supplies relevant external knowledge during inference.
• C.It compresses model weights.
• D.It changes token pricing.

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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.Share the full coordinator conversation history with all subagents to ensure maximum context propagation.
• B.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.
• C.Force the coordinator agent to use the Bash tool to run grep manually instead of reading files.
• D.Switch from dynamic adaptive decomposition to static prompt chaining to force a linear review path.

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

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Which of the following scenarios represent architecturally appropriate use cases for implementing hooks in a production Claude application? Choose 2 correct answers.

• A.Normalizing tool outputs, such as date formats or status codes, before they are appended to the context window.
• B.Guaranteeing that an extracted JSON object has no semantic reasoning errors.
• C.Ensuring Claude maintains a conversational and friendly tone with customers.
• D.Intercepting tool calls to deterministically block policy-violating actions before they execute.

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