Claude Certified Architect Foundations Practice Exam Questions and Answers – Part 9/12

Answer: B. Append each executed tool result to the conversation history using the matching tool_use_id before sending the next model request.

Claude can only reason over information explicitly included in the messages sent on the next request. Appending each tool result with its matching tool use ID bridges the context gap, whereas keeping data solely in application state leaves the model blind.

Answer: B. Define the shared server in the repository's .mcp.json, using environment variable placeholders for credentials rather than committed secrets.

Defining the server in the repository .mcp.json file makes shared tooling travel with the codebase. Using environment variable placeholders allows secure local credential injection, whereas documenting manual local setup steps breaks reproducibility for the team.

Answer: A. Update guidance to acknowledge frustration, proceed with supported resolution steps, and escalate only if the customer again asks for a human.

Frustration alone is not a reliable signal that a case requires human escalation. When the issue is within the agent's capability and the customer has not explicitly requested a human, the agent should attempt the supported resolution while remaining ready to escalate if the customer states that preference.

Answer: A. Rewrite delegated Task prompts to state the support objective, constraints, case facts, and resolution quality criteria, leaving investigation paths flexible.

This approach improves reliability by giving the subagent the context and success criteria needed to adapt its investigation to unusual case details. The coordinator still defines the goal and quality bar, but it avoids over-constraining the subagent with brittle procedural steps.

Answer: D. Run an interview-style refinement pass where Claude asks maintainers targeted questions, then fold clarified criteria into the CI review prompt.

An interview-style refinement pass is the best next step because the core problem is underspecified requirements, not just prompt wording. Having the model ask maintainers targeted questions surfaces hidden criteria and domain-specific risks before the workflow becomes mandatory.

Answer: D. Route subagent messages, errors, and follow-up requests through the coordinator, which manages delegation, recovery, and information flow.

A coordinator-centered pattern gives one agent responsibility for routing information, tracking failures, and deciding what should happen next. This improves observability because every handoff, retry, and aggregation step passes through a single control point, unlike a peer-to-peer mesh.

Answer: B. Add a stateful prerequisite gate that blocks process_refund unless verified customer and order owner IDs match, then escalates mismatches.

Adding a stateful prerequisite gate creates a deterministic control point outside the model's probabilistic reasoning. Since the required workflow depends on verified state from prior tool results, the gate directly prevents the unsafe downstream action when the prerequisite condition is not satisfied.

Answer: A. Restrict each subagent to role-relevant tools, adding only narrow cross-role utilities for frequent simple checks like source metadata lookup.

Scoped tool access keeps each subagent focused on its specialization and reduces tool selection confusion. Allowing only narrow cross-role utilities for common simple needs preserves efficiency without letting subagents take over responsibilities better handled by other agents or the coordinator.

Answer: D. Require each extracted obligation to carry source excerpts and locations, then preserve and merge that evidence into each synthesized matrix row.

Multi-source synthesis needs provenance that survives every handoff. The system should require each extracted obligation to include its supporting excerpt and location metadata, then merge those records into the final matrix row, rather than relying on a final bibliography or reconstructing citations later.

Answer: D. Keep universal review principles in project CLAUDE.md, and move specialized CI workflows into project skills invoked by relevant jobs.

Separating always-applicable guidance from task-specific procedures reduces irrelevant context during routine reviews. Use project CLAUDE.md for universal standards, and move specialized workflows into project skills invoked only by relevant jobs, preventing false positives on documentation-only pull requests.

Answer: A. Use Grep to search repository contents for the exact error string and refund handler names, then Read matching files.

Grep is the optimal tool to locate exact error strings and handler names across a repository. Glob only matches filenames, while reading entire directories wastes context and risks missing the targeted error message.

Answer: D. Configure Claude Code to emit structured JSON matching a schema containing required fields for inline review comments.

Configuring structured JSON output creates a predictable contract for reliable downstream automation. Markdown and raw text are fragile formats that require complex parsing, which inevitably breaks when wording slightly changes.

Answer: D. Add errorCategory and isRetryable fields to tool failures, retrying only failures marked retryable and preserving user-facing explanations.

Adding explicit error categories and retry flags gives the agent structured semantics for correct recovery routing. Relying on keyword parsing is brittle, and blanket escalation undermines the goal of automated first-contact resolution.

Answer: A. Define reportable evidence thresholds for performance findings, including unbounded input growth, hot paths, or repeated database calls inside loops.

Defining concrete evidence thresholds replaces vague caution with specific conditions the model can evaluate. Asking the model for longer reasoning or higher confidence scores fails to eliminate speculative findings because it lacks measurable constraints.

Answer: A. Review each changed file separately for local prompt and schema defects, then run a final pass checking cross-file consistency.

Reviewing individual files isolates local logic without exhausting the context window, preventing superficial later analysis. A final integration pass ensures schemas and validators match, whereas bulk reviews suffer from lost-in-the-middle attention failures.