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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect - Foundations Sample Questions:

1. In addition to your CI pipeline, your organization has enabled Claude's managed Code Review through the Claude GitHub App on this repository, and reviews run automatically on every pull request. Reviews average
18 findings per pull request. Developer feedback reveals three categories of unwanted noise: (1) style and formatting issues already enforced by your CI linter, (2) findings on automatically generated template code under src/gen/*, and (3) rendering-helper patterns that are intentional project conventions but are flagged because they resemble common anti-patterns. Only approximately four findings per pull request are genuine logic bugs. What is the most effective way to reduce this noise while preserving the detection of real issues?

A) Add detailed explanations to the project's CLAUDE.md describing intentional patterns, stating that CI handles linting, and identifying src/gen/ as automatically generated code.
B) Create a REVIEW.md file at the repository root containing skip rules for CI-enforced checks and generated files, together with a verification requirement that rendering-related findings cite a specific line demonstrating incorrect behavior.
C) Configure separate GitHub Actions workflow files for each code area: one for generated code with findings suppressed, one for rendering code with custom instructions, and one general workflow for everything else.
D) Add custom review instructions to a GitHub Actions workflow file, using the action's prompt parameter to suppress duplicate lint findings, ignore generated template code, and impose stricter evidence requirements on rendering-related issues.

2. You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline.
The system runs automated code reviews, generates test cases, and provides feedback on pull requests. You need to design prompts that provide actionable feedback and minimize false positives.
Your automated review jobs take 18 seconds to initialize before Claude begins analyzing code. Profiling reveals that the delay results from automatically discovering hooks, MCP servers, plugins, skills, and multiple nested CLAUDE.md files throughout the monorepo.
You need to reduce startup time while ensuring reviews still enforce the coding standards documented in the root-level CLAUDE.md file.
What is the most effective approach?

A) Run in --bare mode and repeat all review criteria directly in the -p prompt for every invocation.
B) Replace the default prompt using --system-prompt-file ./CLAUDE.md, which bypasses default prompt assembly and loads only the project rules.
C) Keep the default initialization and add --exclude-dynamic-system-prompt-sections to improve prompt- cache reuse across CI runners.
D) Run in --bare mode and pass --append-system-prompt-file ./CLAUDE.md to load the required project standards explicitly while skipping automatic discovery.

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.
You've configured your Claude agent with three MCP servers: one for git operations, one for Jira ticket management, and one for documentation search.
When a user asks the agent to "create a branch for JIRA-123 and add documentation links to the ticket," how does the agent access tools across these servers?

A) Tools from all configured MCP servers are discovered at connection time and available simultaneously to the agent.
B) You must specify which MCP server to use for each turn, and the agent can only access one server's tools at a time.
C) The agent queries each server sequentially to determine which handles each tool, routing calls based on tool name prefixes.
D) The agent automatically selects the most relevant server based on the request and loads only that server' s tools.

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) Expand MCP tool descriptions to detail capabilities and outputs-e.g., "Builds dependency graph showing direct imports, transitive dependencies, and cycles."
B) Add routing instructions to the system prompt specifying that dependency-related questions should use MCP tools rather than Grep.
C) 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.
D) Remove Grep from available tools when the MCP server is connected to eliminate functional overlap.

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.
Your team has connected a custom MCP server that provides DevOps workflow templates. The server exposes several MCP prompts (such as deploy_checklist and incident_response ) in addition to tools.
How do these MCP prompts become accessible within Claude Code?

A) They are added to Claude Code's tool registry alongside the server's tools, invoked automatically by the model when relevant to the task.
B) They appear as slash commands (e.g., /mcp__servername__deploy_checklist ) that you can invoke, with arguments passed after the command name.
C) They are surfaced as @ -mentionable resources alongside files, fetched and attached to your message when referenced.
D) They are automatically prepended to every conversation as additional system-level context, influencing Claude's behavior throughout the session.

Solutions: