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Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

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?

A. 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.
B. 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.
C. 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.
D. 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.

Question 2

Your Claude application runs long agentic workflows where the agent makes many tool calls, and the conversation history grows quickly. After about 20 tool calls, you notice the agent's responses become less focused and sometimes ignore earlier task constraints.
How would you address this?

A. Increase the model's context window so the agent can hold every tool output at full detail across the entire workflow no matter how many tool calls it accumulates.
B. Remove tool calling from the workflow entirely so the agent operates as a single text-generation step with no tool outputs accumulating in the context window.
C. Restart the agent every five tool calls to prevent any drift, with the agent losing all task state at each restart point during the workflow.
D. Apply context engineering techniques such as tool output pruning or compaction to keep the active task state visible while reducing the volume of older content.

Question 3

Your Claude agent has access to a tool that retrieves customer records. A teammate has noticed that the agent occasionally calls the tool with arguments the schema does not declare, and the tool's downstream service returns an error each time. The teammate proposes loosening the schema so the tool accepts whatever arguments the model produces.
How would you respond?

A. Keep the schema strict, validate arguments before dispatching, and return a structured error so the agent can retry.
B. Loosen the schema as the teammate proposed so the downstream service receives every call the agent makes during normal operation.
C. Add a system prompt instruction telling the model to produce schema-conforming arguments, treating the prompt instruction as the primary mechanism for keeping the agent's tool calls valid.
D. Remove the schema entirely and rely on the downstream service to reject invalid calls, treating the downstream service as the team's primary enforcement layer.

Question 4

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

Question 5

Your team is debating how to manage the prompts used in your Claude application. Some prompts are checked into the code repository, some live in a separate configuration file, and some are constructed inline at runtime. The result is inconsistent, and a recent prompt change went out without code review.
What steps would you take?

A. Establish a single source of truth for prompts but keep change review optional, allowing developers to update prompts directly when changes are urgent.
B. Move all prompts to inline runtime construction so the team can update them quickly through a streamlined process outside the standard code review workflow.
C. Establish a single source of truth for prompts, version-control them alongside code, and require code review for prompt changes.
D. Move all prompts out of version control to a separate spreadsheet that team members can edit freely as the application evolves over time.

Solutions: