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Anthropic Claude Certified Architect – Foundations Sample Questions:

1. You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JavaScript Object Notation (JSON) schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.
Your system must extract event details from calendar invitations and output JSON that strictly conforms to a schema with fields for title, date, time, location, and attendees. Downstream systems reject any malformed or non-conformant JSON.
What approach provides the most reliable schema compliance?

A) Include detailed JSON formatting instructions and the target schema in your prompt, then parse Claude' s text response as JSON.
B) Pre-fill Claude's response with an opening brace to force JSON output, then complete and parse the response.
C) Define a tool with your target schema as input parameters and have Claude call it with the extracted data.
D) Append instructions like "Output only valid JSON matching the schema exactly" and implement retry logic to re-prompt when JSON parsing fails.

2. You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JavaScript Object Notation (JSON) schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.
Your system extracts event metadata (date, location, organizer, attendee_count) from news articles using a JSON schema with all nullable fields. During evaluation, you observe the model frequently generates plausible but incorrect values for fields not mentioned in the article-for example, outputting "500" for attendee_count when the source contains no attendance information.
What's the most effective way to reduce these false extractions?

A) Add a post-processing step using a second LLM call to verify each extracted value exists in the source document.
B) Add prompt instructions to return null for any field where information is not directly stated in the source.
C) Upgrade to a more capable model tier with improved instruction-following to reduce hallucination tendencies.
D) Make all schema fields required (non-nullable) with strict validation rules to ensure the model only outputs verifiable data.

3. You are building a customer support resolution agent using the Claude Agent SDK. The agent handles high- ambiguity requests like returns, billing disputes, and account issues. It has access to your backend systems through custom Model Context Protocol (MCP) tools ( get_customer , lookup_order , process_refund , escalate_to_human ). Your target is 80%+ first-contact resolution while knowing when to escalate.
A customer raises three separate issues during one session: a refund inquiry (turns 1-15), a subscription question (turns 16-30), and a payment method update (turns 31-45). At turn 48, the customer asks "What happened with my refund?" The conversation is approaching context limits.
What strategy best maintains the agent's ability to address all issues throughout the session?

A) Rely on MCP tools to re-fetch relevant information on demand when the customer references earlier issues.
B) Implement sliding window context that retains the most recent 30 turns.
C) Extract and persist structured issue data (order IDs, amounts, statuses) into a separate context layer.
D) Summarize earlier turns into a narrative description, preserving full message history only for the active issue.

4. 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.
You're tasked with adding real-time updates to the application. This could be implemented using WebSockets, Server-Sent Events, or polling, each with different complexity, browser support, and infrastructure requirements.
What's the most effective way to begin this task?

A) Start direct execution with WebSockets, then refactor if infrastructure issues arise.
B) Enter plan mode to explore the architecture, evaluate trade-offs, and present options for team approval before implementing.
C) Use direct execution with a prompt asking Claude to analyze all approaches and implement the one it determines is best.
D) Use direct execution to implement polling first, then evaluate whether to upgrade to WebSockets later.

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.
You've configured your Claude agent with three MCP servers: one for git operations, one for Jira ticket management, and one for documentation search.
When a user asks the agent to "create a branch for JIRA-123 and add documentation links to the ticket," how does the agent access tools across these servers?

A) The agent queries each server sequentially to determine which handles each tool, routing calls based on tool name prefixes.
B) The agent automatically selects the most relevant server based on the request and loads only that server' s tools.
C) Tools from all configured MCP servers are discovered at connection time and available simultaneously to the agent.
D) You must specify which MCP server to use for each turn, and the agent can only access one server's tools at a time.

Solutions: