Claude Certified Architect Foundations Practice Exam Questions and Answers – Part 14/16

Answer: B. Delegate code search and file discovery to the Explore subagent, and return concise findings to the main conversation.

Delegating code search to an exploration subagent moves high-volume output into a separate context window. This preserves the main conversation for high-level coordination without losing important architecture details to verbose exploration logs.

Answer: A. Have the main thread issue the independent Agent calls in one assistant turn, then return all matching tool_result blocks together in the next user message.

Issuing multiple independent Agent tool calls in a single assistant turn allows the orchestrator to execute them concurrently. Grouping the returned tool result blocks in the next user message completes the parallel cycle, preventing the main thread from blocking on sequential subagent responses.

Answer: B. Define an escalate_to_human client tool whose input_schema requires customer_id, root_cause, refund_amount, and recommended_action.

Defining an escalation client tool with a strict input schema forces the model to generate structured arguments for every handoff. This guarantees downstream systems receive consistent data, whereas relying on prompt instructions for ticket content remains purely probabilistic.

Answer: D. Start plan mode with all failing fixtures, shared schema constraints, and the validation command.

Because these parser failures share dependencies, plan mode allows Claude to inspect the codebase and propose a coherent strategy addressing all cross-effects upfront. Fixing independent issues sequentially often pollutes the context window and degrades results for unrelated tasks.

Answer: D. Add a short examples block showing representative finding inputs and ideal cited-bullet outputs, including edge cases.

Providing concrete input and output examples clarifies the exact transformation boundary that prose instructions leave ambiguous. Broad wording or configuration files fail to enforce strict structural mapping, and hooks are better suited for blocking side effects than formatting text.

Answer: D. Run claude -p "Continue the refactor investigation from yesterday." –resume "$session_id"

Passing the captured session ID to the resume flag explicitly restores the exact prior conversation context before sending the new prompt. Putting the identifier inside the prompt text only passes a string to the model, failing to direct the CLI to load that session.

Answer: C. Run a separate review request that receives the source document, extracted JSON, and explicit discrepancy criteria.

Providing the source document, extracted output, and explicit discrepancy criteria creates an isolated review pass that objectively audits the original extraction. A follow-up prompt in the same context risks confirmation bias, as the model often assumes its previous output is already correct.

Answer: D. Add three to five tagged source snippet and expected JSON examples covering typical and edge-case missing values.

Providing concrete input and output examples is the most reliable way to enforce strict formatting rules and handle edge cases. Expanding abstract prose instructions often fails to correct nuanced mapping inconsistencies because the model lacks specific examples to anchor its behavior.

Answer: B. Segment the evaluation by document type and extracted field before changing review thresholds.

Segmenting the evaluation by document type and field reveals concentrated failures that a high aggregate accuracy score easily masks. Relying solely on an overall metric might cause you to approve a release with critical errors in rarer document categories.

Answer: C. Return a CallToolResult with isError set and structuredContent describing the error category, retryability, affected fields, and correction hint.

Returning a tool result with the error flag set and structured content gives Claude machine-readable context for recovery. Treating failures as normal text results causes loops because the model lacks the clear signal needed to understand the validation failure.

Answer: D. Give the synthesis subagent a narrow verify_fact tool and route broader investigation requests through the coordinator.

Providing a narrow verification tool allows the synthesis subagent to quickly resolve minor evidence questions without overstepping its role. Giving it broad exploration tools would duplicate work, while removing all tools causes unnecessary coordinator delays.

Answer: B. Return structured tool_result errors with failure category, retryability, message, and corrective guidance.

Structured tool results provide the exact failure category, retryability, and corrective guidance Claude needs to choose the right next step. Generic error messages force the model to guess, causing inappropriate retries or escalations that break the workflow.

Answer: B. Pass the relevant findings and source metadata directly in the synthesis task message.

Passing the relevant findings and source metadata directly in the task message gives the subagent the required data. Subagents operate with isolated context windows, so they cannot automatically read the previous research transcripts stored by the coordinator.

Answer: B. Add a PreToolUse prerequisite gate that denies Bash until the project root check has been recorded.

A PreToolUse gate intercepts the request before execution, allowing you to programmatically block unsafe tool calls. System prompts and few-shot examples are behavioral suggestions, meaning the model might still bypass the required ordering under complex conditions.

Answer: D. Connect each required MCP server for the subagent, list tools after each connection, and expose a unified registry while routing calls to the owning server.

Connecting to all required servers simultaneously allows the host to aggregate tools into a unified registry for the subagent. Switching between single active servers creates unnecessary connection overhead and limits the agent from chaining tools effectively.