Claude Certified Architect Foundations Practice Exam Questions and Answers – Part 8/8

Answer: D. Return successful empty results only for completed searches, and structured retryable errors when order lookup cannot access the backend.

Separating valid empty results from access failures provides the necessary state for correct control flow. Distinguishing between a completed search with zero matches and a backend outage prevents false denials and enables proper retry logic or escalation.

Answer: B. Have agents maintain concise scratchpad files with key findings, file paths, and decisions, then reference them in later prompts.

Persistent scratchpad files preserve important discoveries outside the model's shifting conversation context. Referencing these files in later prompts helps counteract context degradation and keeps the investigation grounded in previously verified facts.

Answer: C. Use Glob with **/*.policy-case.json, review the matched paths, then Read only the relevant fixture files.

Using Glob is the most direct approach when the selection criterion is a filename pattern rather than file contents. Reviewing matched paths before reading keeps the context focused and avoids unnecessary token usage from loading irrelevant files.

Answer: B. Move specialized guidance into .claude/rules/ files with YAML paths globs so only rules relevant to changed files load.

Path-scoped rule files load conditionally based on matching file paths, keeping irrelevant guidance out of the active context. This directly reduces token usage and false positives while preserving automatic rule application during continuous integration review.

Answer: D. Run the review as a separate Claude Code invocation using only the diff, repository context, and review criteria.

A separate review invocation prevents the model from carrying forward implementation reasoning that might make it less likely to question its own choices. Providing the diff and repository context preserves necessary information without inheriting generator assumptions.

Answer: D. Create a project skill in .claude/skills/test-gap-review/SKILL.md, configuring argument-hint and allowed-tools frontmatter, then include the reusable checklist.

A project skill packages reusable task-specific workflows directly in the repository. Frontmatter elements like argument-hint and allowed-tools control execution behavior, making this approach superior to slash commands or relying on generic CLAUDE.md rules for constrained tool access.

Answer: D. Add a preprocessing layer that stores full tool outputs externally and appends only schema-relevant fields and provenance to conversation history.

Storing full tool outputs externally and appending only schema-relevant fields to the context prevents verbose data from degrading model performance. This approach solves context bloat and lost-in-the-middle effects, whereas simply increasing max tokens or using prose summaries fails to fix the architectural issue.

Answer: C. Rewrite the affected tool descriptions to specify purposes, required inputs, side effects, examples, and boundaries between refund and escalation workflows.

Rewriting tool descriptions to specify boundaries, required inputs, and side effects directly addresses inconsistent tool selection. Claude relies heavily on these descriptions to differentiate between similar actions, making explicit boundaries far more reliable than adding brittle keyword routers or merging distinct workflows.

Answer: A. Configure tool_choice to any so Claude must call one available tool while retaining model-driven selection among applicable tools.

Configuring tool_choice to any guarantees the agent will execute a backend action rather than returning generic text. This setting enforces tool usage while still allowing the model to select the most contextually appropriate tool, avoiding the brittleness of forcing a specific hardcoded tool.

Answer: A. Keep tool_use schema enforcement, add deterministic checks for line ranges and file membership, then retry with those failures included.

Adding deterministic checks for file membership and line ranges catches semantic inconsistencies that JSON schema validation alone misses. Including these specific failures in a targeted retry provides actionable feedback to the model, which is much more effective than running blind retries or tightening schema enums.

Answer: C. Update each MCP tool to return categorized failures with retryability and customer-safe guidance tailored to the specific backend condition.

Updating tools to return categorized failures with retryability and customer-safe guidance gives the agent the context needed to choose correct recovery paths. This allows the agent to distinguish between temporary timeouts and permanent policy denials, which generic error messages or hard-coded retry loops cannot do.

Answer: D. Run Claude Code with –output-format json and –json-schema defining required fields for each pull request finding.

Using structured JSON output with an explicit schema gives the CI script a stable contract for parsing findings. Relying on regex to parse markdown is a brittle anti-pattern, whereas structured JSON directly enforces required fields like severity and line ranges for reliable automation.

Answer: D. Have the coordinator assess request scope, delegate only to relevant specialist subagents, then aggregate their findings into one response.

Having the coordinator assess scope and delegate only to relevant specialists eliminates unnecessary work for simple requests. This pattern preserves multi-specialist aggregation for complex cases while avoiding the fragility of keyword routing and the anti-pattern of subagents messaging each other directly.

Answer: C. Populate each Task prompt with the verified customer facts, relevant order records, prior findings, and needed decision criteria.

Subagents operate with isolated context and cannot automatically view the coordinator's transcript. Populating the Task prompt with verified facts and decision criteria ensures the subagent has the necessary information, preventing duplicate tool calls and redundant questions to the customer.

Answer: A. Replace vague confidence guidance with concrete reportable and non-reportable categories, severity definitions, and code examples for each finding type.

Replacing vague confidence guidance with concrete categories and severity definitions gives the model operational boundaries for deciding what to report. A 95% certainty threshold is too restrictive and eliminates useful findings, whereas specific examples calibrate the reviewer effectively.