CCDV-F Agents and the Agent SDK Practice Question
A developer is creating an agent that uses the Anthropic SDK to answer customer support questions. The agent has access to a tool that retrieves order status from an internal API. During testing, the developer notices that the agent sometimes provides an order status without calling the tool, resulting in incorrect information. What is the most likely cause of this behavior?
⚠ Common exam trap
The trap here is blaming model parameters like temperature or tool_choice, when the real issue is often the clarity of the tool's description and instructions.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The tool's description is too vague, so the model does not understand when it should be used.
The most likely cause is a vague tool description. The model uses the description to understand the tool's purpose and when to invoke it. If the description does not clearly explain that the tool retrieves order status, the model may answer from its own knowledge, leading to incorrect information. Improving the description will guide the model to use the tool appropriately.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The agent's system prompt does not include the current date, so the model cannot determine order freshness.
Why it's wrong here
The absence of the current date in the system prompt is unlikely to cause the model to skip the tool entirely. While date context can be helpful, the primary reason for not calling a tool is usually insufficient tool description or unclear instructions. The model should still recognize that order status requires the tool.
- ✗
The `tool_choice` parameter is set to `{"type": "auto"}`, which allows the model to ignore tools.
Why it's wrong here
`tool_choice: {"type": "auto"}` is the default and allows the model to decide whether to use a tool. This is appropriate for an agent that should autonomously decide. The issue is not the parameter but the tool's description or the model's understanding. Setting it to `any` would force tool use, but that is not the root cause.
- ✓
The tool's description is too vague, so the model does not understand when it should be used.
Why this is correct
The model relies on the tool's name and description to decide when to invoke it. If the description is vague or does not clearly state that the tool retrieves order status, the model may not recognize the need to call it and instead fabricate an answer. Clear, specific descriptions are critical for correct tool use.
- ✗
The model's temperature is set too high, causing it to hallucinate tool calls.
Why it's wrong here
Temperature affects randomness in generation but does not cause the model to skip tool calls or hallucinate order statuses. A high temperature might lead to more varied responses, but the core issue is that the model is not recognizing the need to use the tool. Adjusting temperature is not the solution here.
About these practice questions
Courseiva writes every CCDV-F question from scratch — 257 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Anthropic exam blueprint
This CCDV-F practice question is part of Courseiva's free Anthropic certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the CCDV-F exam.