Anthropic CCA-F : Claude Certified Architect Foundations (CCA-F)

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions:

Question #1
Your MCP server includes archive_file(file_id) and delete_file(file_id) tools. Production logs show the agent calls delete_file when users ask to "remove old backups," but company policy requires archiving backup files. Both tools currently have minimal descriptions: "Archives a file" and
"Deletes a file." Which change most directly improves tool selection for this scenario?

A. Expand tool descriptions to clarify use cases, adding guidance like "Do not use for backup files" to delete_file.
B. Add a confirmation step that requires users to type "CONFIRM DELETE" before delete_file executes.
C. Implement server-side validation that rejects delete_file calls for files tagged as backups, returning an error message suggesting archive_file.
D. Add few-shot examples to the system prompt demonstrating that requests involving "backup" or
"old" should use archive_file.

Question #2
You are using Claude Code to accelerate software development. Your team uses it for code generation, refactoring, debugging, and documentation. You need to integrate it into your development workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.
Your team's CLAUDE.md includes a rule: "Use 4-space indentation and always run Prettier formatting." Despite this, code reviews reveal that roughly 30% of files Claude Code generates use inconsistent formatting - sometimes 2-space indentation, sometimes missing trailing commas. Adding emphasis ("IMPORTANT: You MUST use Prettier formatting") reduces violations to about 15%, but doesn't eliminate them. What is the most effective way to ensure all generated code is consistently formatted?

A. Split the formatting rules into path-scoped .claude/rules/files that load when Claude works on matching file types.
B. Add a Stop hook with a prompt-based check that evaluates whether generated code follows formatting standards and prompts Claude to fix violations.
C. Extract the formatting rules into a dedicated skill that Claude loads automatically when generating code, with more detailed examples of correct formatting.
D. Configure a PostToolUse hook with an Edit|Write matcher that automatically runs Prettier on each file Claude modifies.

Question #3
A financial services company plans to integrate Claude into an internal document analysis platform. The architects want to minimize exposure of confidential client information while maintaining high-quality responses. Which approach BEST aligns with Anthropic's recommended architecture?

A. Store every prompt permanently for auditing.
B. Remove unnecessary sensitive information before sending prompts whenever possible.
C. Replace Claude with a smaller local model regardless of task complexity.
D. Send every document without preprocessing to maximize context.

Question #4
During a billing dispute resolution, your agent successfully retrieves customer info via get_customer and order details via lookup_order, but when attempting to call process_refund, the tool returns a timeout error. The agent has enough information to explain the charges and verify refund eligibility, but cannot actually process the refund due to the backend failure. What approach best balances first-contact resolution with appropriate error handling?

A. Implement automatic retries with exponential backoff for process_refund, keeping the conversation open until the refund is successfully processed
B. Explain the billing confirm refund eligibility, acknowledge the system issue preventing immediate processing, and offer escalation or retry later
C. Escalate immediately to a human agent since the refund action cannot be completed
D. Confirm the refund will be processed and close the conversation, since the system has all necessary information to complete it automatically

Question #5
You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with Model Context Protocol (MCP) servers.
Your agent has spent 25 minutes exploring a game engine's rendering subsystem -reading shader code, buffer management, and frame synchronization logic. An engineer now asks it to understand how the physics engine integrates with rendering for collision debug overlays. You notice recent responses reference "typical rendering patterns" rather than the specific VulkanPipeline and FrameGraph classes it discovered earlier.
What's the most effective approach?

A. Continue in the current context with more targeted prompts referencing the specific classes by name.
B. Use /clear to reset context completely, then start fresh with physics exploration using file paths from the project's CLAUDE.md.
C. Summarize key rendering findings, then spawn a sub-agent for physics exploration with that summary in its initial context.
D. Spawn a sub-agent to explore physics independently, then manually synthesize its findings with the rendering knowledge accumulated in the main conversation.

Solutions: