Claude Certified Architect Foundations Practice Exam Questions and Answers – Part 23/24

Answer: C. Run a stop_reason driven loop with tool_choice: {"type":"auto"} and let Claude choose tool use or a final reply each turn.

Using a stop_reason driven loop with automatic tool choice lets Claude dynamically select the necessary tools based on the current context. Predefined chains fail because they cannot adapt to the varying requirements of individual billing disputes.

Answer: B. Add unclear and other enum values, plus an other_detail field, and instruct when to use each.

Adding fallback categories like unclear and other with a detail field provides valid choices for ambiguous or unanticipated inputs. This maintains the integrity of your structured schema without forcing the model into incorrect categorizations.

Answer: C. Enter plan mode so Claude Code researches the codebase and proposes changes for approval before editing files.

Plan mode allows Claude Code to research the unfamiliar codebase and propose a structural plan for engineer approval before editing. Direct execution is a poor choice here because large architectural refactors require human review to validate the approach first.

Answer: C. Add 3-5 XML-wrapped examples that show relevant claim-evidence cases, edge cases, and ideal report phrasing.

Adding structured few-shot examples directly demonstrates the intended judgment boundary for nuanced phrasing decisions. This targeted approach fixes reasoning inconsistencies better than simply adjusting instructions or enforcing structural validation rules.

Answer: B. Run query() with resume=baseline_session_id and fork_session=True for each strategy, then store each new session_id.

Using the fork session parameter creates a new branch of the original history for independent exploration. This ensures the baseline session remains completely unchanged while generating two distinct paths you can resume later.

Answer: D. Run a separate Claude session with fresh context and provide the requirements, diff, and review checklist.

A separate reviewer session with fresh context provides an unbiased audit free from the original generator rationalizations. The strongest distractor fails because compacting history does not eliminate the self-validation bias inherent to self review.

Answer: D. Return no-match lookups as successful empty results, and return timeout failures as error tool results with retry context.

Successful empty results represent valid negative evidence while timeouts represent missing evidence that requires explicit error context. Collapsing both into empty arrays causes the model to assume the data is absent rather than unreachable.

Answer: C. Run focused per-file review passes first, then run a separate integration pass over the summarized local findings and cross-file data flow.

Focused per-file reviews prevent attention dilution before a final integration pass checks cross-file data flow. Reviewing everything at once causes context overload, making the model miss localized defects while trying to track global dependencies.

Answer: C. Maintain a structured case facts block that is updated after each relevant turn and made available on every relevant turn.

Maintaining a structured case facts block preserves critical transactional data outside the summarized conversation history. Relying on conversational memory or frequent summarization risks data loss, so exact state must live in a durable structured layer.

Answer: D. Condense prior exploration into a source-linked summary and include it in each next subagent's delegation prompt.

Condensing prior exploration into a source-linked summary gives the next subagent the relevant state without carrying verbose artifacts forward. Attaching full transcripts wastes context, while keeping delegations independent causes duplicated effort.

Answer: B. Create .claude/rules/testing.md with paths frontmatter matching the test file patterns, then place the testing guidance below it.

Path-scoped rule files apply instructions only to matching files using glob patterns in the frontmatter. Duplicating guidance across multiple directories creates maintenance overhead, and root instructions apply too broadly.

Answer: D. Rewrite the system prompt and tool description with narrower use boundaries and ordinary wording for audit reports.

Rewriting the system prompt and tool descriptions removes the forceful language causing the tool to trigger on common words. Tool choice configuration cannot fix bad trigger conditions, so defining clear boundaries is the highest-leverage fix.

Answer: C. Require each research subagent to return schema-conformant JSON that includes source dates and a date basis for every substantive finding.

Subagents operate in isolated contexts and return only their final output to the parent. Reverting to schema JSON with explicit source dates ensures the parent agent receives the exact metadata needed to distinguish between current information and outdated compatibility notes.

Answer: B. Define all three servers in mcp_servers, add one matching mcp_toolset per server in tools, and let Claude choose among the discovered tools.

The Messages API requires defining each server connection in the servers block and enabling its tools through an MCP toolset. This allows Claude to dynamically choose from all available tools during a single request rather than requiring rigid pre-selection per document.

Answer: D. Measure precision and recall by finding category, then narrow or pause the noisy dead-code checks.

Measuring precision and recall by finding category identifies the specific class causing the false positives. Narrowing the noisy dead-code checks prevents developers from completely ignoring the automated review output, preserving trust in the highly accurate defect findings.