CCDV-F Agents and the Agent SDK Practice Question
A developer is building a support agent with the Claude Agent SDK. The agent must pause execution, ask a human operator to approve a refund above $500, and resume the exact same session with the operator's decision injected as a new message. Which SDK capability should the developer configure to accomplish this reliably?
⚠ Common exam trap
The trap here is assuming that telling the model to ask for confirmation in the system prompt is equivalent to an enforced human-approval pause.
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
✓
Permission callbacks combined with session persistence, so the agent suspends on the sensitive action and later resumes from the saved session state.
Approval gates require an enforcement point plus durable state. Permission callbacks intercept the sensitive tool call before it executes, and session persistence stores the conversation so the run can be resumed later with the operator's decision appended. Together they suspend and continue the same session deterministically, which prompt instructions, blocking handlers, or retry loops cannot provide.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Wrapping the refund tool in a retry loop that re-invokes the model until the operator approves in a separate chat window.
Why it's wrong here
Re-invoking the model starts or continues a generation, but a retry loop has no notion of a suspended session or an out-of-band approval channel. It wastes tokens, can duplicate side effects, and cannot inject the operator's decision as a first-class conversation event, so the agent cannot reliably resume the identical paused execution.
- ✗
A custom tool whose handler blocks on stdin and returns the operator's typed answer as a tool_result.
Why it's wrong here
Blocking a tool handler on interactive stdin stalls the agent process and cannot resume a previously serialized session; the operator may not even be attached to the same host. It also bypasses the SDK's structured pause and resume semantics, so conversation state and pending tool calls are not durably preserved across the approval window.
- ✗
Increasing max_tokens and instructing the model in the system prompt to ask for confirmation before calling the refund tool.
Why it's wrong here
A prompt instruction only nudges model behavior and provides no enforcement mechanism; the model can still emit the refund tool call directly. Raising max_tokens merely allows longer outputs. Neither feature pauses execution, captures an external decision, or restores a suspended session, so the approval guarantee the scenario requires is absent.
- ✓
Permission callbacks combined with session persistence, so the agent suspends on the sensitive action and later resumes from the saved session state.
Why this is correct
Permission callbacks let the SDK intercept a sensitive tool invocation and hand the decision to your code before execution, while session persistence saves the full conversation and pending state. Resuming the same session with the operator's decision injected as a new message continues the run exactly where it paused, which is the intended approval pattern.
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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.