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Anthropic CCDV-F Exam Overview:

Anthropic CCDV-F Exam Syllabus Topics:

Anthropic Claude Certified Developer-Foundations Sample Questions:

Question 1

Your Claude agent has too many tools, and many of them have overlapping functionality. The agent often picks an inappropriate tool when several could plausibly handle a request.
How would you address the tool selection problem?

A. Restructure the tool set by consolidating overlapping tools, removing unused tools, and clarifying tool descriptions so each tool has a distinct purpose.
B. Add detailed examples to each tool's description so the agent can match incoming requests to the right tool by example, treating the examples as the team's selection mechanism.
C. Add more tools to cover every variation of the requests the agent handles, on the grounds that more tools give the agent more accurate options to choose from.
D. Remove all tools and rely on the agent's general capability instead, with the application losing the workflows that previously relied on tools.

Question 2

Your team is choosing how to add a capability to a Claude application. You want to apply the appropriate option, whether built-in tool, custom tool, Skill, or MCP server, based on the use case.
You would choose the option that...

A. Is the most familiar to the team based on prior experience with similar capabilities.
B. Matches the use case's scope, reuse needs, and integration context.
C. Is the easiest to build given the team's current development tools and workflows.
D. Is the newest available option among built-in tools, custom tools, Skills, and MCP servers.

Question 3

You are setting up the configuration management approach for a new Claude Code project. Your team will use CLAUDE.md files and settings.json files to control behavior, and you want to make sure changes are tracked and reviewable.
The configuration management approach would...

A. Version-control CLAUDE.md alongside the project's source code and settings.json files in a separate repository from the project's source code.
B. Duplicate CLAUDE.md and settings.json files in multiple repositories to provide redundancy, on the grounds that a single source of truth is risky for project configuration.
C. Version-control CLAUDE.md and settings.json files in a separate repository from the project's source code, so configuration evolves independently from the application code over time.
D. Version-control CLAUDE.md and settings.json files alongside the project's source code, with changes reviewed through standard pull request workflows the team applies.

Question 4

Your Claude application is hitting context window limits when processing long customer service transcripts.
A junior developer suggests increasing the temperature parameter to fix the issue.
How would you respond?

A. Adjust the temperature parameter together with the max_tokens parameter, treating the combined adjustment as the team's mechanism for managing context window pressure during long-transcript processing.
B. Explain that temperature controls sampling randomness and is unrelated to context capacity, then address the context issue through summarization or chunking.
C. Increase the temperature parameter as the junior developer suggested and observe whether the context window issue resolves over the next several runs of the application in production.
D. Remove the system prompt entirely to make room for longer transcripts in each request, freeing up context window space the system prompt would otherwise consume.

Question 5

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. 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.
C. 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.
D. 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.

Solutions: