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Anthropic Claude Certified Architect – Foundations Sample Questions:

1. 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.
After expanding the agent's MCP tools with delivery-specific capabilities (check_delivery_status, contact_driver, issue_credit, apply_promo_code, update_delivery_address, reschedule_delivery), the total tool count has grown from 4 to 10. Your evaluation suite shows tool selection accuracy has dropped from 88% to
71%. Log analysis reveals the majority of errors involve the agent selecting between semantically overlapping tools-calling issue_credit when process_refund was correct, and calling check_delivery_status when lookup_order already returns the needed data.
Which approach structurally eliminates the semantic overlap identified in the logs as the error source?

A) Add few-shot examples to the system prompt demonstrating correct selection for each ambiguous tool pair, such as showing when issue_credit applies versus when process_refund is appropriate.
B) Consolidate semantically overlapping tools-merge issue_credit and process_refund into a single resolve_compensation tool with an action parameter, and fold check_delivery_status into lookup_order with an optional include_tracking flag.
C) Split the tools across two sub-agents-a "financial resolution" agent with process_refund, issue_credit, and apply_promo_code, and a "delivery operations" agent with the remaining delivery tools-with a coordinator routing between them.
D) Enable the tool search tool with defer_loading on the six new tools, keeping the original four always loaded, so the agent dynamically discovers specialized tools only when needed.

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

3. 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.
An engineer asks the agent to find all callers of a function before removing it. The function is defined in a core library but is also exposed through wrapper modules that rename the function for domain-specific use (e.
g., calculateTax in the library becomes computeOrderTax in the orders module).
What exploration strategy will most reliably identify all callers?

A) Read the library and wrapper modules to identify all exposed names for the function, then Grep for each name across the codebase.
B) Search for the function name in project documentation to understand intended usage patterns and navigate to documented integration points.
C) Use Grep to find all files that import from the library or wrapper modules, then read each file to check whether it uses the function.
D) Use Grep to search for the function's original name across the codebase.

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

5. 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 implementing a caching layer for API responses to speed up the /products endpoint. You have a rough idea-Redis with a 5-minute TTL-but you're new to production caching and aren't sure what other considerations a robust implementation requires.
What's the most effective way to start your iterative workflow?

A) Ask Claude to interview you about the caching requirements before implementing, surfacing considerations like invalidation strategies, cache layers, consistency guarantees, and failure modes.
B) Use plan mode to analyze the current /products endpoint implementation, then provide your caching requirements once Claude explains how the existing code is structured.
C) Start with a minimal request: "Add Redis caching to /products with 5-minute TTL." Add features and fix issues through follow-up prompts as problems surface during testing.
D) Write a specification with your known requirements and "TBD" markers for uncertain areas, having Claude propose solutions for each TBD as it implements.

Solutions: