Anthropic CCDV-F - Claude Certified Developer-Foundations

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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

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?

A. Collapse the three subagents into a single large-context model call that handles retrieval, analysis, and generation in one pass.
B. 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.
C. Give each subagent read access to the other subagents' outputs so they can identify and resolve contradictions without routing back through the primary agent.
D. 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.

Question 2

You are extending a Claude agent with a capability that needs to be reusable across multiple teams in the organization, with each team able to invoke and use it independently.
How would you build the capability?

A. As a Skill or MCP server because both are purpose-built for cross-team reuse independently by each consuming team.
B. As a shared library that each team imports into its own Claude application code, with each team responsible for keeping the library up to date in its integration.
C. As a wrapper around an existing built-in tool that adds the missing functionality, on the grounds that built-in tools cover the reuse pattern when extended carefully.
D. As a custom tool embedded in this team's agent only, with other teams able to copy the implementation into their own agents when they need the capability.

Question 3

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?

A. 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.
B. 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.
C. Use separate Claude calls for triage and response, because each stage has distinct inputs, outputs, and success criteria that benefit from focused prompts.
D. 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.

Question 4

A new Claude model release includes performance improvements for several reasoning tasks but has changed the format of its responses to system prompts that use multi-section instructions. Your application uses multi- section system prompts heavily. Initial evaluation on the application's actual workload shows the new model performs 8 percent better on reasoning tasks but produces malformed output on roughly 3 percent of requests because of the format change. The team is debating whether to upgrade.
How would you decide?

A. Upgrade immediately, because the 8 percent reasoning improvement outweighs the 3 percent malformed output rate across the application's typical request distribution.
B. Stay on the previous model permanently to avoid the malformed output rate and any future format changes that subsequent model releases might introduce in the application.
C. Adapt the application's system prompt to the new model's format expectations and re-evaluate, then upgrade only if the adapted prompt eliminates the malformed output while preserving the reasoning improvements.
D. Upgrade and add a downstream validation step that catches the 3 percent malformed output before it reaches users, treating the validation step as the team's mitigation for the format change.

Question 5

You are running Claude Code as part of an automated continuous integration pipeline. The pipeline needs Claude Code to execute a set of well-defined tasks without prompting for confirmation, and the output needs to be captured for downstream processing.
How would you configure the pipeline?

A. Replace Claude Code with a different tool that does not require any configuration to operate without confirmation prompts in the pipeline.
B. Run Claude Code in headless mode with the required permissions configured in settings.json and capture its output for downstream processing.
C. Disable Claude Code's confirmation prompts globally across all environments so the pipeline runs without interruption from any prompt.
D. Run Claude Code in interactive mode and have a developer manually approve every confirmation prompt while the pipeline executes its tasks.

Solutions: