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CCDV-F Exam Practice Questions

Claude Certified Developer – Foundations

CCDV-F English PDF practice questions: 53 questions in source order, with options supported by the source format, answers and available explanations. Access covers this exam only. One-time payment; no automatic renewal.

Exam overview

For engineers developing applications with the Claude API, tool use and agent capabilities.

The provider describes exams for Claude Partner Network members. Confirm eligibility, languages and scheduling in Partner Academy.

Exam code
CCDV-F
Official exam / credential
Claude Certified Developer – Foundations
Exam format
Proctored, identity-verified certification assessment delivered through Pearson
Official exam languages
A complete language list could not be confirmed from the public official material. Check the provider’s booking page.

Official exam languages and practice-question file languages are listed separately. Confirm the exam version and available languages when booking with the provider.

Official sources: Provider reference
Information checked: 2026-10-20

Supported languages

  • English
  • Simplified Chinese
Try before you buy

First 20 practice questions

53 total questions

Questions follow the source order. Expand each answer to see its explanation.

Disclaimer: All questions on ExamPico are compiled from internet sources and are provided for study reference only.

Question 16

Question#16Topic1

A teammate is reviewing the team’s threat model for a Claude application and has asked you to identify the categories of AI-specific threats that the model should cover. The teammate has already listed traditional web application threats and wants to know what additional categories apply to a Claude application.
Which AI-specific threat categories would you add?

  1. A. Supply chain attacks on the Claude SDK because the SDK itself is the only point of vulnerability that a Claude application introduces beyond traditional web application threats.
  2. B. Network-level denial of service and physical infrastructure attacks, because these categories cover the threats most likely to affect any Claude application in production.
  3. C. Cross-site scripting and SQL injection, because these traditional web application threats apply with equal weight to any application that uses Claude in any way.
  4. D. Prompt injection, data leakage from prompts or context, jailbreak attempts, and unsafe model output that bypasses application controls.
Show answer and explanation

Answer

D

Explanation

AI-specific threat categories for Claude applications include prompt injection, data leakage from prompts or context, jailbreak attempts, and unsafe model output that bypasses application controls. Source: https://docs.anthropic.com/en/docs/test-and-evaluate/strengthen-guardrails/mitigate-jailbreaks

Question 17

Question#17Topic1

A team has deployed a multi-agent system in which a primary agent decomposes user requests and delegates subtasks to three specialized subagents: one for data retrieval, one for analysis, and one for report generation. In production, the team observes that subagents are making redundant tool calls, occasionally exceeding token budgets, and sometimes producing outputs that contradict each other – all of which the primary agent passes along without catching. What is the most appropriate way to address these failures?

  1. A. Strengthen the primary agent’s management layer to enforce per-subagent tool budgets, validate outputs against a defined schema before passing them forward, and establish explicit handoff contracts between stages.
  2. B. Give each subagent read access to the other subagents’ outputs so they can identify and resolve contradictions without routing back through the primary agent.
  3. C. Add retry logic to each subagent so that when a tool call fails, the subagent retries automatically before escalating – and configure each subagent to log its tool calls and outputs to a shared trace so the team can audit redundancy and contradictions after the fact.
  4. D. Collapse the three subagents into a single large-context model call that handles retrieval, analysis, and generation in one pass.
Show answer and explanation

Answer

A

Explanation

Strengthen the primary agent's management layer with per-subagent tool budgets, output schema validation before handoff, and explicit handoff contracts between stages. Source: https://docs.anthropic.com/en/docs/agents-and-tools/agent-patterns

Question 18

Question#18Topic1

A teammate has asked you to explain when a Skill would be the right choice over an MCP server. The teammate is unsure how the two differ in practice when both can be reused across teams. How would you explain the distinction?

  1. A. A Skill is preferable for cross-team reuse because it loads more efficiently than an MCP server during normal operation in the team’s typical multi-team workloads.
  2. B. A Skill bundles prompts, scripts, and data into a package the model loads as a unit while a MCP server exposes resources, tools, and prompts through a standard client interface.
  3. C. A Skill and an MCP server are equivalent extension mechanisms that the team can use interchangeably for any reusable capability that needs to be accessible across teams.
  4. D. A Skill is the older mechanism and an MCP server is the newer one, so the team should prefer an MCP server for any reusable capability that the team builds going forward.
Show answer and explanation

Answer

B

Explanation

A Skill bundles prompts, scripts, and data into a package the model loads as a unit, while an MCP server exposes resources, tools, and prompts through a standard client interface. Source: https://docs.anthropic.com/en/docs/claude-code/skills

Question 19

Question#19Topic1

You are designing a Claude application that will process customer support tickets in two stages: a triage stage that classifies tickets and a response stage that drafts replies. The team is debating whether to use a single Claude call that handles both stages or separate Claude calls for each stage. How would you structure the application?

  1. A. Use separate Claude calls for triage and response, because each stage has distinct inputs, outputs, and success criteria that benefit from focused prompts.
  2. B. Use a single Claude call for triage and then use a non-Claude rule-based system for response generation, on the grounds that rule-based systems are more reliable for drafting replies.
  3. C. Use multiple Claude calls in parallel that each draft a complete ticket reply, then have a fourth Claude call select the best one to send to the customer.
  4. D. Use a single Claude call for both stages, on the grounds that a single call is cheaper than multiple calls in any production Claude application setup.
Show answer and explanation

Answer

A

Explanation

Use separate Claude calls for triage and response because each stage has distinct inputs, outputs, and success criteria that benefit from focused prompts. Source: https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/chain-prompts

Question 20

Question#20Topic1

Your Claude application uses structured output that is consumed by downstream code. The team wants to handle malformed or unexpected output gracefully so it does not crash downstream systems. The best choice for handling this issue would be to ...

  1. A. use the output the model produces and leave schema enforcement to a later phase of production after the application is more complete.
  2. B. apply defensive parsing to handle unexpected fields, missing values, and type mismatches that the downstream code might otherwise crash on.
  3. C. crash on any unexpected output and require manual recovery on affected requests the application handles during normal operation.
  4. D. silently drop any output that does not match expectations so downstream systems do not see the malformed output the application receives from the model.
Show answer and explanation

Answer

B

Explanation

Apply defensive parsing to handle unexpected fields, missing values, and type mismatches so downstream systems do not crash on malformed structured output. Source: https://docs.anthropic.com/en/docs/build-with-claude/structured-outputs

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