Free CCDV-F Agents and Workflows Practice Test — Claude Certified Developer Questions

This free CCDV-F Agents and Workflows practice test covers designing agentic systems with Claude — agent loops, workflows vs agents, orchestration patterns, subagents, agent memory, and multi-step task decomposition. Each question includes a detailed explanation aligned to Anthropic's official Claude Certified Developer – Foundations exam outline.

Key Topics in CCDV-F Agents and Workflows

6 Free CCDV-F Agents and Workflows Practice Questions with Answers

Each question below includes 4 answer options, the correct answer, and a detailed explanation. These are real questions from the FlashGenius CCDV-F question bank for the Agents and Workflows domain (14.7% of the exam).

Sample Question 1 — Agents and Workflows

A team is automating monthly expense report handling with Claude. Every report must follow the same sequence: extract fields, check policy rules, route exceptions to a human queue, and generate a summary. The branching conditions are fixed and success is easy to verify. Which architecture is the best fit?

  1. A. A deterministic workflow that calls Claude only at defined steps (Correct answer)
  2. B. A fully autonomous agent that decides each next action
  3. C. A manager agent that delegates every report to subagents
  4. D. A long-running agent that stores every report interaction

Correct answer: A

Explanation: Correct answer (A): A deterministic workflow is the best fit because the process has a known sequence, predictable branching, and clear success criteria. Claude can still be used inside defined steps, but the orchestration should not be left to an autonomous agent when the application already knows the correct order and routing logic. Why the other options are wrong: - Option B: An autonomous agent may appear flexible, but the task does not require dynamic planning or open-ended tool choice. It would add unnecessary variability and complexity. - Option C: Subagents may help with specialized decomposition, but this scenario is a simple fixed process. A manager/subagent pattern would add coordination overhead without a clear benefit. - Option D: Long-running memory is not needed for a predictable monthly workflow. Keeping every interaction would risk context bloat without improving the fixed routing process.

Sample Question 2 — Agents and Workflows

A developer is building a Claude-powered internal research assistant. User requests vary widely, and the assistant must decide whether to search documentation, inspect previous notes, ask a clarifying question, synthesize findings, or stop based on intermediate results. Which design is most appropriate?

  1. A. A fixed workflow with the same steps for every request
  2. B. An agent loop that plans, acts, observes, and stops (Correct answer)
  3. C. A batch job that summarizes all notes nightly
  4. D. A single prompt that forbids asking clarifying questions

Correct answer: B

Explanation: Correct answer (B): An agent loop is appropriate because the task requires dynamic planning, choosing among actions, reacting to intermediate observations, and deciding when to ask for clarification or stop. These choices cannot be fully enumerated as a fixed sequence for every research request. Why the other options are wrong: - Option A: A fixed workflow may seem easier to operate, but it is too rigid for requests that require different paths based on intermediate findings. - Option C: A nightly batch summary may be useful for a separate reporting use case, but it does not support interactive planning and adaptive research. - Option D: Forbidding clarifying questions removes a useful agent behavior. The scenario explicitly includes cases where clarification may be the right next action.

Sample Question 3 — Agents and Workflows

A Claude-powered support agent repeatedly checks the same ticket metadata tool after receiving unchanged results. The application currently lets the model decide whether to continue, with no retry limit or completion criteria. What is the best primary change?

  1. A. Add explicit stop conditions and retry limits to the loop (Correct answer)
  2. B. Increase the conversation history kept for each ticket
  3. C. Split every ticket into several subagent assignments
  4. D. Replace all tool calls with a fixed daily report

Correct answer: A

Explanation: Correct answer (A): Agent loops should have explicit stopping conditions, retry limits, and clear handling for repeated or unhelpful tool results. This prevents runaway loops and unnecessary repeated attempts when the agent is not making progress. Why the other options are wrong: - Option B: More history may make the loop even larger without addressing the missing termination logic that is causing repeated tool checks. - Option C: Subagents can help with decomposition, but the immediate flaw is a loop-control problem, not a lack of specialized workers. - Option D: A fixed daily report avoids the loop but does not satisfy the interactive support-agent requirement described in the scenario.

Sample Question 4 — Agents and Workflows

A Claude-powered due diligence assistant reviews large acquisition packets. One part analyzes financial tables, another checks contract obligations, and another summarizes technical risks. A single general agent is mixing evidence across domains and exceeding its useful context. What is the best architecture change?

  1. A. Keep one agent and append all evidence to its memory
  2. B. Use a manager agent with specialized subagents per domain (Correct answer)
  3. C. Convert the process into one fixed linear extraction workflow
  4. D. Ask the general agent to be more careful about sources

Correct answer: B

Explanation: Correct answer (B): A manager/subagent pattern is appropriate when a complex task decomposes into specialized subtasks. Specialized subagents can receive narrower context and tool access, reducing evidence mixing and improving context isolation while a manager coordinates the overall result. Why the other options are wrong: - Option A: Appending all evidence worsens context pressure and does not address cross-domain confusion. It reinforces the single overloaded-agent failure mode. - Option C: A fixed linear workflow may work for predictable extraction, but the scenario involves specialized analysis and synthesis across complex domains. - Option D: Better instructions may help slightly, but they do not solve the architectural issue of one agent handling too much unrelated context.

Sample Question 5 — Agents and Workflows

A recruiting assistant uses an agent to screen incoming candidate messages. After the agent classifies a message as needing human review, the application must always create a task in the HR system at that exact point. Which implementation pattern is best?

  1. A. Tell the model to remember to create the HR task
  2. B. Use a deterministic hook after the review classification (Correct answer)
  3. C. Let the agent choose whether task creation is needed
  4. D. Store the decision in memory for the next conversation

Correct answer: B

Explanation: Correct answer (B): Hooks are appropriate when a specific action must occur deterministically at a defined point in an agent workflow. The model can classify the message, but the application should enforce the required side effect instead of relying only on model discretion. Why the other options are wrong: - Option A: Prompting the model may appear simple, but instructions alone do not make the side effect deterministic at a specific point in the workflow. - Option C: The scenario says the task must always be created after the classification. Leaving the decision to the agent conflicts with that requirement. - Option D: Memory can preserve useful state, but saving the decision for later does not perform the required immediate workflow action.

Sample Question 6 — Agents and Workflows

A startup is building its first Claude-powered operations agent. The team wants supported agent-building abstractions for loop handling and tool dispatch, and it does not need custom state-machine behavior yet. Which implementation choice is most appropriate?

  1. A. Use the Claude Agent SDK for the initial agent (Correct answer)
  2. B. Build a fully custom orchestration harness first
  3. C. Avoid an agent and use a static prompt only
  4. D. Create subagents before defining the main task

Correct answer: A

Explanation: Correct answer (A): The Claude Agent SDK is appropriate when the team wants supported abstractions instead of implementing loop, state, and tool-dispatch behavior manually. A custom harness is better reserved for cases needing tight orchestration control or specialized integration behavior. Why the other options are wrong: - Option B: A custom harness can be valuable, but the scenario says the team wants supported abstractions and lacks special state-machine requirements. - Option C: A static prompt does not provide the agent loop and tool-dispatch behavior the team is explicitly seeking. - Option D: Subagents should be introduced to solve decomposition or context-isolation needs, not before the main task and architecture are defined.

How to Study CCDV-F Agents and Workflows

Combine these CCDV-F Agents and Workflows practice questions with the official Anthropic documentation and hands-on projects. Build a small Claude-powered application with tool use, try Claude Code on a real repository, and iterate on prompts with evals — practical experience is the fastest way to master this domain.

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