최신Anthropic Claude Certified Architect Foundations (CCA-F) - CCA-F무료샘플문제

A. Create a fast-path for factual questions that bypasses subagents entirely, routing all other queries through the complete pipeline to ensure research thoroughness.

B. Implement pattern-based routing that categorizes queries by structure (single-fact vs.
comparative vs. analytical) and maps each category to a predefined subagent combination.

C. Train a query complexity classifier on labeled historical data to predict optimal subagent combinations, retraining periodically as query patterns evolve.

D. Have the coordinator analyze each query and dynamically decide which subagents to invoke based on its assessment of query requirements.

A. Remove procedural details entirely, delegating with simple goals like "research X thoroughly" and relying on the subagent's general capabilities.

B. Implement a topic classification step where the coordinator categorizes requests as "well-defined" or "exploratory" and uses different instruction styles for each category.

C. Add explicit fallback directives to the detailed instructions: "If specified searches yield fewer than N results, attempt alternative query formulations before reporting failure."

D. Specify research goals and quality criteria (coverage breadth, source diversity, recency) rather than procedural steps, letting the subagent determine its search strategy.

A. Configure subagents to only report findings meeting a high-confidence threshold, filtering uncertain information before it reaches the coordinator.

B. Instruct the synthesis agent to structure reports with explicit sections distinguishing well- established findings from contested ones, preserving original source characterizations and methodological context.

C. Add a verification subagent that cross-references findings across sources, only passing claims to synthesis that are corroborated by at least two independent sources.

D. Implement a confidence calibration layer that normalizes subagent uncertainty expressions to standardized probability scores (0.0-1.0), then weight-average findings by their calibrated confidence.

A. Keep the single tool but add an analyze_type enum parameter requiring explicit selection between extraction, summarization, and verification modes

B. Have the coordinator pre-classify each analysis request before passing instructions to the document analysis agent

C. Split the generic tool into purpose-specific tools - extract_data_points, summarize_content, verify_claim_against_source - each with defined input/output contracts

D. Enhance the tool description with detailed examples showing how different instruction phrasings should map to different output formats

A. Define a fixed sequence of investigation steps upfront - grep for error patterns, then read error handlers, then check database queries, then examine middleware - executing each step regardless of intermediate findings.

B. Have the agent dynamically generate investigation subtasks based on what it discovers at each step, adapting its exploration plan as new information about the error path emerges.

C. Run parallel worker agents that simultaneously investigate all four layers, then synthesize their findings to identify where the error originates.

D. Have the agent first create a comprehensive plan mapping all code paths through the endpoint before beginning any file exploration or code reading.

A. Read the project's README and service configuration files to understand the architecture, then systematically Read source files in each service directory.

B. Use Grep to find all files that import the project's error handling module, then Read those files to locate custom error definitions.

C. Use Grep to search for distinctive text from the error message (like "SYNC_CONFLICT" or "entity version mismatch"), then Read the matching files to understand context.

D. Use Glob to find files in directories commonly associated with error handling (such as errors/, exceptions/,or handlers/) across all services, then Read each matching file.

A. Implement automatic retry logic at the tool level for technical errors only, passing business errors to Claude without retries.

B. Add few-shot examples showing how to distinguish retriable from non-retriable errors by parsing error message text.

C. Return structured error responses with retriable: false for business errors and a customer-friendly explanation for Claude to use.

D. Add a check_refund_eligibility tool that must be called before process_refund to prevent business rule violations.

A. Keep one unified tool with a nested operation_details object parameter whose internal structure varies by operation type, documented in the tool description.

B. Keep one unified tool but add JSON Schema if-then-else conditionals to enforce that parameters like amount are required only when the operation type is "refund".

C. Split into three separate tools (issue_refund, cancel_order, request_reshipment), each defining only the parameters required for that specific operation.

D. Keep one unified tool with all parameters marked optional, but add detailed few-shot examples in the system prompt showing correct parameter combinations for each operation type.