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Anthropic CCAR-F Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Claude Code Configuration & Workflows	20%	- Developer productivity workflows - Claude Code usage and configuration - Integrating Claude Code into development processes
Topic 2: Context Management & Reliability	15%	- Evaluation and reliability strategies - Managing context windows and information flow - Production deployment considerations
Topic 3: Prompt Engineering & Structured Output	20%	- Prompt design strategies - Improving Claude response quality and consistency - Structured output generation and validation
Topic 4: Tool Design & MCP Integration	18%	- Designing effective tools for Claude applications - Tool safety, reliability, and usability - Model Context Protocol (MCP) concepts and integration
Topic 5: Agentic Architecture & Orchestration	27%	- Selecting appropriate Claude architectures - Designing agentic systems and workflows - Agent coordination and orchestration patterns

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CCAR-F Reliable Test Topics & Anthropic CCAR-F Guide: Claude Certified Architect - Foundations Exam Pass Once Try

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Anthropic Claude Certified Architect - Foundations Sample Questions (Q122-Q127):

NEW QUESTION # 122
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. As a detailed instruction block in the project's root CLAUDE.md file
B. In .claude/skills/migrate-component/SKILL.md at the project root, committed to version control
C. In ~/.claude/skills/migrate-component/SKILL.md on each developer's machine
D. In the project's.claude/settings.json using a skillOverrides entry to register and define the workflow

Answer: B

Explanation:
A project-scoped skill is available to everyone working in that repository and stays synchronized through version control. The skill directory name exposes it as /migrate-component.

NEW QUESTION # 123
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.
An engineer asks your agent to identify untested code paths in a legacy payment processing module spanning 45 files. After reading the first 8 source files, the agent's responses are becoming noticeably less accurate - it's forgetting previously discussed code patterns and hasn't yet located all test files or traced critical payment flows. What's the most effective approach to complete this investigation?

A. Switch to using Grep to search for specific function names instead of reading full files, reducing the content loaded into context for remaining exploration.
B. Clear context with /clear, then selectively re-read only the most critical files discovered so far, writing key findings to a scratchpad file that persists between context resets.
C. Document all current findings in a summary report, clear context completely, then use that report as the sole reference for continuing the investigation.
D. Spawn subagents to investigate specific questions (e.g., "find all test files for payment processing," "trace refund flow dependencies") while the main agent coordinates findings and preserves high-level understanding.

Answer: D

Explanation:
Subagents isolate detailed exploration in separate context windows and return concise findings to the main agent. This prevents further context degradation while preserving high-level coordination across test discovery and payment-flow tracing.

NEW QUESTION # 124
The document-analysis agent has a single analyze_document tool that accepts a document and a free-text instruction parameter. During evaluation, requests such as "extract the key financial metrics" often return narrative summaries, while "summarize the methodology" sometimes returns raw data tables. The synthesis agent reports that 35% of analysis results require new requests with clarified instructions. What is the most effective way to improve reliability?

A. Enhance the tool description with detailed examples showing how different instruction phrasings should map to different output formats.
B. Retain the single tool but add an analysis_type enum requiring explicit selection among extraction, summarization, and verification modes.
C. Have the coordinator preclassify each analysis request before passing instructions to the document- analysis agent.
D. Split the generic tool into purpose-specific tools-extract_data_points, summarize_content, and verify_claim_against_source-each with defined input and output contracts.

Answer: D

Explanation:
Option A removes the semantic ambiguity created by one generic tool performing three substantially different operations. Each replacement tool can have a distinct name, focused description, appropriate required parameters, and an output schema designed for its task. For example, extract_data_points can return typed records, while verify_claim_against_source can return a verdict, supporting excerpt, and source location.
Anthropic's tool-design guidance recommends thoughtful tools with clear, distinct purposes and natural task boundaries. Ambiguous or overlapping capabilities make it harder for agents to select the correct operation and interpret its results consistently.
Option B improves the existing interface, but the implementation and result contract remain overloaded, increasing the possibility that the model or tool will mix behavior across modes. Option C adds another probabilistic classification stage without repairing the underlying interface. Option D may reduce some errors, but free-text interpretation remains the principal control mechanism. Purpose-specific tools encode the intended operation directly into the callable interface, permit strict schemas tailored to each result type, and make evaluation failures easier to diagnose. This produces a stronger contract between the agent and deterministic document-processing system.

NEW QUESTION # 125
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 complex graph traversal algorithm with specific performance requirements and edge cases to handle (disconnected nodes, cycles, weighted edges). You want to structure your workflow for efficient iterative refinement with Claude. What approach will most effectively enable progressive improvement across multiple iterations?

A. Write a test suite covering expected behavior, edge cases, and performance requirements before implementation. Ask Claude to write code that passes the tests, then iterate by sharing test failures with each refinement request.
B. Provide Claude with a detailed natural language specification of the algorithm, including all requirements and edge cases. Review each output manually and provide descriptive feedback on what behavior needs to change.
C. Provide Claude with a reference implementation from documentation, then ask it to rewrite the code to match your codebase style and add the required edge case handling, comparing outputs against the reference.
D. Have Claude extensively research the algorithm and create a detailed implementation plan using extended thinking, then implement the complete solution based on that plan.

Answer: A

Explanation:
Tests provide an executable specification and objective feedback for each iteration. Claude can implement against the suite, run it, inspect failures, and progressively refine the algorithm until correctness and performance requirements are met. Anthropic recommends running tests and fixing failures as an iterative Claude Code workflow.

NEW QUESTION # 126
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 need to add a date validation check ensuring event dates are in the future. This requires adding a conditional statement to one existing function in a single file. What is the most appropriate approach?

A. Use direct execution to make the change.
B. Start with extended thinking mode enabled to ensure thorough reasoning about the validation logic.
C. Enter plan mode to analyze how the validation might impact other parts of the reservation flow.
D. Enter plan mode first to create a detailed implementation strategy before making the change.

Answer: A

Explanation:
This is a small, well-defined modification in one function and one file. Plan mode is better suited to complex, high-impact, or multi-file changes that require review before editing.

NEW QUESTION # 127
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