Anthropic CCAR-F 試験概要:

Anthropic CCAR-F 試験シラバストピック:

Anthropic Claude Certified Architect – Foundations 認定 CCAR-F 試験問題：

1. You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JavaScript Object Notation (JSON) schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.
The system routes documents with extraction confidence below 85% to human review. A quarterly audit reveals that 12% of high-confidence extractions (#85%) also contain errors-cases where the model finds plausible-but-incorrect values. Error sources vary: comparison tables showing competitor specs, appendices referencing different product variants, and ambiguous phrasing the model misinterprets. You need a sustainable strategy to catch these high-confidence errors and measure whether improvements reduce the error rate over time.
What approach is most effective?

A) Implement heuristic rules that flag documents containing comparison tables or appendices for review regardless of confidence score.
B) Add a verification pass that re-extracts from each high-confidence document, flagging cases where the two extraction attempts produce different results.
C) Lower the confidence threshold from 85% to 70%, routing a larger volume of extractions to human review.
D) Implement stratified random sampling reviewing a fixed percentage of high-confidence extractions weekly, enabling error rate measurement and novel pattern detection.

2. You are using Claude Code to accelerate software development. Your team uses it for code generation, refactoring, debugging, and documentation. You need to integrate it into your development workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.
Your team frequently migrates React components to Vue. You've written a step-by-step workflow for Claude Code to follow during each migration, and you want every developer on the team to invoke it by typing
/migrate-component . The workflow should stay in sync as the team iterates on it.
Where should you place the skill file?

A) In the project's .claude/settings.json using a skillOverrides entry to register and define the workflow.
B) In .claude/skills/migrate-component/SKILL.md at the project root, committed to version control.
C) As a detailed instruction block in the project's root CLAUDE.md file.
D) In ~/.claude/skills/migrate-component/SKILL.md on each developer's machine.

3. You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with Model Context Protocol (MCP) servers.
Your agent has analyzed a complex service module-reading 23 source files, tracing request flows, and identifying error handling patterns. A developer wants to compare two testing strategies before committing to one: end-to-end tests with mocked external services vs. snapshot tests capturing expected outputs. They need to independently develop both approaches to evaluate trade-offs.
How should you manage the sessions?

A) Export the analysis session's key findings to a file, then create two new sessions that reference this file.
B) Resume the analysis session with fork_session enabled, creating a separate branch for each testing strategy.
C) Continue in the original session, developing end-to-end tests first, then snapshot tests sequentially.
D) Start two fresh sessions, having each re-read the relevant source files before beginning.

4. You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with Model Context Protocol (MCP) servers.
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) Add routing instructions to the system prompt specifying that dependency-related questions should use MCP tools rather than Grep.
C) Expand MCP tool descriptions to detail capabilities and outputs-e.g., "Builds dependency graph showing direct imports, transitive dependencies, and cycles."
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.

5. You are using Claude Code to accelerate software development. Your team uses it for code generation, refactoring, debugging, and documentation. You need to integrate it into your development workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.
You're implementing a caching layer for API responses to speed up the /products endpoint. You have a rough idea-Redis with a 5-minute TTL-but you're new to production caching and aren't sure what other considerations a robust implementation requires.
What's the most effective way to start your iterative workflow?

A) Start with a minimal request: "Add Redis caching to /products with 5-minute TTL." Add features and fix issues through follow-up prompts as problems surface during testing.
B) Write a specification with your known requirements and "TBD" markers for uncertain areas, having Claude propose solutions for each TBD as it implements.
C) Use plan mode to analyze the current /products endpoint implementation, then provide your caching requirements once Claude explains how the existing code is structured.
D) Ask Claude to interview you about the caching requirements before implementing, surfacing considerations like invalidation strategies, cache layers, consistency guarantees, and failure modes.

質問と回答：