CCDV-F Agents and the Agent SDK Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  Set the `temperature` to 0 for the Coordinator to ensure deterministic routing decisions.

  Why it's wrong here

  Setting temperature to 0 reduces randomness but does not guarantee deterministic routing, as the model's outputs can still vary due to other factors. More importantly, deterministic routing is not essential for effective delegation; the Coordinator needs to adapt to context. This parameter tuning is not a core practice for managing multi-agent delegation.

• ✓

  Include the full conversation history, including all tool_use and tool_result blocks, in each subsequent request to the Coordinator so it can reason about prior delegations.

  Why this is correct

  The Messages API is stateless; the model does not retain memory between requests. To maintain context, the developer must include the entire conversation history, including tool_use and tool_result blocks, in each request. This allows the Coordinator to see what tasks have been delegated, what results were returned, and avoid redundant delegations.

• ✓

  Define separate tools for each specialized agent (e.g., `delegate_to_researcher`, `delegate_to_writer`) with clear descriptions of their capabilities and expected inputs.

  Why this is correct

  Providing distinct tools for each agent with descriptive names and input schemas helps the Coordinator model understand when and how to delegate. Clear tool descriptions reduce ambiguity and improve the model's ability to route tasks correctly. This is a recommended practice for building effective multi-agent systems with the Anthropic SDK.

• ✗

  Implement a separate memory store (e.g., a database) that the Coordinator queries before each delegation to check if the task was already completed.

  Why it's wrong here

  While external memory can be useful, it is not essential for the Coordinator to manage delegation effectively. The conversation history already provides the necessary context. Adding an external memory store introduces complexity and potential consistency issues. The core requirements are maintaining conversation history and defining clear delegation tools.

• ✗

  Use the `max_tokens` parameter to limit the Coordinator's response length, ensuring it does not generate overly long delegations.

  Why it's wrong here

  While `max_tokens` controls response length, it does not help the Coordinator manage delegation or maintain conversation state. Limiting tokens could truncate necessary reasoning or tool calls, harming performance. It is not an essential practice for effective delegation; proper context management and clear tool definitions are far more important.