CCA-F최신시험공부자료 - CCA-F최신인증시험대비자료

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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Prompt Engineering & Structured Output	20%	- Advanced prompting techniques 1. System prompts and role framing 2. Few-shot and chain-of-thought prompting - Structured data generation 1. Output validation and reliability 2. JSON schema enforcement
Topic 2: Claude Code Configuration & Workflows	20%	- CI/CD and development integration 1. Plan mode vs direct execution 2. Pipeline automation and review - Configuration files and structure 1. CLAUDE.md and rules system 2. Custom commands and workflows
Topic 3: Tool Design & MCP Integration	18%	- Tool definition and best practices 1. Tool descriptions and selection logic 2. Error handling and validation - Model Context Protocol (MCP) 1. MCP server and client setup 2. Tools, resources, and prompts integration
Topic 4: Context Management & Responsible AI	15%	- Safety and compliance 1. Constitutional AI principles 2. Refusal handling and risk mitigation - Context window optimization 1. Token management and truncation strategies 2. Context retention and summarization
Topic 5: Agentic Architecture & Orchestration	27%	- Agent design patterns 1. Hub-and-spoke multi-agent systems 2. Agent loops and control flow - Anthropic Agent SDK usage 1. Session state and context handling 2. Task spawning and tool management

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CCA-F최신 인증시험 대비자료, CCA-F최신버전 덤프샘플문제

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최신 Claude Certified Architect CCA-F 무료샘플문제 (Q34-Q39):

질문 # 34
Which of the following strategies are explicitly recommended for designing multi-instance and multi-pass review architectures? Choose 2 correct answers.

A. Splitting multi-file reviews into focused per-file passes for local issues plus a separate cross-file integration pass.
B. Having the same session review its newly generated code to preserve maximum architectural context.
C. Forcing consensus across 3 monolithic runs to suppress false positives in large multi-file PRs.
D. Using an independent Claude instance to review generated code without the generator's reasoning context.

정답：A,D

설명：
Independent review instances without prior reasoning context effectively catch subtle issues without confirmation bias. Splitting reviews into focused per-file passes and integration passes addresses attention dilution. Same-session reviews and monolithic consensus runs are anti-patterns.

질문 # 35
When authoring a complex skill, relying on a massive 2000-line SKILL. md file wastes context window tokens. Which of the following describe the recommended "progressive disclosure" architectural pattern? Choose 2 correct answers.

A. Configure an automatic /compact command to execute every 10 turns within the skill definition.
B. Use the fork_session command explicitly on line 1 of the markdown to split the file structure.
C. Keep the SKILL .md file under 500 lines and link to supporting reference files that Claude reads only when needed.
D. Store executable validation code in a scripts/ directory and instruct Claude to run them rather than read their contents.

정답：C,D

설명：
Progressive disclosure in skill architecture involves keeping the main SKILL.md file small (under 500 lines) and linking to supporting files (in directories like references/ and scripts!) that Claude reads or executes only when relevant. Instructing Claude to run scripts rather than read them prevents the script's raw source code from consuming context tokens.

질문 # 36
Your document extraction tool uses ML models to extract invoice fields (vendor, amount, date).
The models return confidence scores (0.0-1.0) for each extracted field. In production, you observe: (1) the agent proceeds with low-confidence extractions that are incorrect 23% of the time, and (2) the agent requests unnecessary human review for 31% of extractions that were actually correct. How should you restructure the tool's output?

A. Return fields organized into verified and needs_verification objects based on confidence thresholds.
B. Compute an aggregate extraction_quality score across all fields and return it alongside the extracted values. Include a text summary describing the overall extraction reliability.
C. Return fields with their raw confidence scores and add detailed few-shot examples to your system prompt demonstrating how to interpret different confidence ranges and when to request human review.
D. Return fields with confidence scores, plus a request_review boolean computed using your tested confidence thresholds, along with a review_reasons array explaining which fields triggered review.

정답：D

설명：
Including a request_review flag based on confidence thresholds, along with reasons for review, gives the agent clear guidance on when human intervention is needed. This reduces both unnecessary reviews and errors caused by low-confidence extractions, improving overall reliability and efficiency.

질문 # 37
After integrating a local MCP server providing code analysis tools (analyze_dependencies, find_dead_code, calculate _complexity), you verify the server is healthy and tools appear in the tools/list response. However, you observe that the agent consistently uses Grep to search for import statements instead of calling analyze_dependencies -even when users explicitly ask about "code dependencies." Examining tool definitions reveals:
MCP: analyze_ dependencies - "Analyzes dependency graph"
Built-in: Grep - "Search file contents for a pattern using regular
expressions. Returns matching lines with line numbers and surrounding
context."
What's the most effective approach to improve the agent's selection of MCP tools?

A. Remove Grep from available tools when the MCP server is connected to eliminate functional overlap.
B. Expand MCP tool descriptions to detail capabilities and outputs - e.g., "Builds dependency graph showing direct imports, transitive dependencies, and cycles."
C. Add routing instructions to the system prompt specifying that dependency-related questions should use MCP tools rather than Grep.
D. Split analyze_dependencies into granular tools ( list_imports, resolve_transitive_deps, detect_circular_deps) so each has a focused purpose less likely to overlap with Grep.

정답：B

설명：
Claude selects tools primarily from their names and descriptions. A specific description distinguishing dependency-graph analysis-including direct imports, transitive dependencies, and cycles-from simple text search makes analyze_dependencies the clearer choice.

질문 # 38
The web search agent has gathered several relevant sources for a research topic. The document analysis agent now needs to examine these sources. How does information typically flow between these two specialized subagents?

A. The coordinator agent receives the web search agent's output and includes relevant findings in the prompt when invoking the document analysis agent.
B. The agents communicate through an event-driven message queue, with the document analysis agent subscribing to web search completion events.
C. Both agents access a shared memory store where the web search agent writes findings and the document analysis agent reads them.
D. The web search agent directly invokes the document analysis agent, passing the discovered sources as parameters.

정답：A

설명：
In a coordinated multi-agent pipeline, the coordinator mediates information flow. It collects outputs from the web search agent and includes the relevant findings in the prompt when invoking the document analysis agent, ensuring proper sequencing and context without tightly coupling the subagents.

질문 # 39
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