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Anthropic CCAR-F Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Agentic Architecture & Orchestration27%- Agent coordination and orchestration patterns
- Designing agentic systems and workflows
- Selecting appropriate Claude architectures
Topic 2: Prompt Engineering & Structured Output20%- Prompt design strategies
- Improving Claude response quality and consistency
- Structured output generation and validation
Topic 3: Tool Design & MCP Integration18%- Designing effective tools for Claude applications
- Model Context Protocol (MCP) concepts and integration
- Tool safety, reliability, and usability
Topic 4: Context Management & Reliability15%- Managing context windows and information flow
- Evaluation and reliability strategies
- Production deployment considerations
Topic 5: Claude Code Configuration & Workflows20%- Claude Code usage and configuration
- Integrating Claude Code into development processes
- Developer productivity workflows

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Anthropic Claude Certified Architect - Foundations Sample Questions (Q13-Q18):

NEW QUESTION # 13
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's CLAUDE.md includes a rule: "Use 4-space indentation and always run Prettier formatting." Despite this, code reviews reveal that roughly 30% of files Claude Code generates use inconsistent formatting-sometimes 2-space indentation, sometimes missing trailing commas. Adding emphasis ("IMPORTANT: You MUST use Prettier formatting") reduces violations to about 15%, but doesn't eliminate them.
What is the most effective way to ensure all generated code is consistently formatted?

Answer: D

Explanation:
Formatting is deterministic and should be enforced by deterministic tooling rather than stronger natural- language instructions. A PostToolUse hook executes after a successful tool operation. Matching Edit|Write restricts the hook to file modifications, allowing the edited file path to be passed directly to Prettier.
Anthropic provides this exact pattern in its official hooks guidance: configure a PostToolUse event with an Edit|Write matcher and run Prettier against the modified file. This ensures formatting occurs automatically after every relevant edit instead of depending on Claude remembering to execute a formatter. ( https://code.
claude.com/docs/en/hooks-guide )
Option A still relies on instruction-following and unnecessarily loads procedural material. Option B asks another probabilistic model evaluation to determine whether formatting is correct, even though Prettier can enforce the result directly. A Stop hook also runs later than necessary. Option C improves contextual relevance but does not guarantee compliance; path-scoped rules remain instructions rather than enforcement controls.
The hook should be stored in project settings so the workflow is shared by the team. The formatter's exit status should also be monitored so configuration or syntax failures are visible instead of silently ignored.
Official references/topics: Claude Code Hooks; PostToolUse; Edit|Write Matchers; Deterministic Formatting Enforcement.


NEW QUESTION # 14
After investigating a billing dispute for more than 25 turns, you determine that duplicate charges resulted from a payment-gateway timeout triggering retry logic. The required refund of $847 exceeds your $500 authorization limit, so you must invoke escalate_to_human. The human agent will not have access to the conversation transcript. What context should you pass to enable effective resolution?

Answer: B

Explanation:
Option C gives the human agent the operational state required to continue without replaying a long conversation. The handoff should include verified identifiers, the duplicate transaction evidence, the diagnosed timeout-and-retry mechanism, the $847 refund requirement, the agent's $500 authorization constraint, completed verification steps, prior actions, and the recommended resolution. Any unresolved uncertainty should be labeled explicitly.
Anthropic's effective context-engineering guidance recommends preserving high-value state in structured notes while removing redundant conversational and tool-call history. Its long-running-agent guidance likewise describes structured handoffs as the mechanism for maintaining continuity across context resets or agent boundaries.
Option A maximizes raw information but forces the human to locate the relevant facts among more than 25 turns, increasing delay and error risk. Option B preserves evidence but omits the authorization constraint, completed verification, and explicit recommended action. Option D is too sparse to support validation or execution. A structured handoff balances fidelity and efficiency: it contains everything needed for the next actor to make the refund decision while excluding greetings, repeated explanations, and irrelevant intermediate tool output.


NEW QUESTION # 15
The coordinator agent has AgentDefinition objects configured for all four specialized subagents, each with appropriate descriptions, prompts, and tool restrictions. During testing, you notice that the coordinator correctly reasons about when to delegate--it generates messages such as, "I'll ask the web-search agent to find sources on this topic"--but no subagent execution occurs. The coordinator then proceeds as if the delegation happened and continues with incomplete information. Logs show no errors. What is the most likely cause?

Answer: A

Explanation:
Option B identifies the missing executable capability. Defining specialized agents makes their configurations available, but the coordinator must still be permitted to call the tool that invokes them. Without that tool, Claude can describe an intended delegation in ordinary text but cannot create a subagent execution.
The current Claude Agent SDK documentation requires "Agent" in allowedTools to auto-approve subagent invocations. The tool was renamed from "Task" to "Agent" in Claude Code 2.1.63, so the terminology in the original candidate question required correction. Older integrations may still expose "Task" in initialization or permission records.


NEW QUESTION # 16
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 infrastructure-as-code repository includes Terraform modules ( /terraform/ ), Kubernetes manifests (
/kubernetes/ ), and CI/CD pipeline scripts ( /pipelines/ ). Each requires different conventions, but your single root CLAUDE.md has grown to 500+ lines. When developers work on Kubernetes files, Terraform-specific rules load into context unnecessarily, consuming tokens.
What is the best approach to reorganize so only relevant guidance loads when editing specific file types?

Answer: A

Explanation:
Path-scoped rules directly satisfy the requirement that instructions load only when Claude works with matching files. Each infrastructure domain can have a separate Markdown file under .claude/rules/ , with YAML paths frontmatter targeting Terraform files, Kubernetes manifests, or pipeline configuration.
Anthropic documents that .claude/rules/ keeps project guidance modular and supports conditional loading based on glob patterns. Rules with a paths field apply only when Claude works with matching files, reducing irrelevant context and token consumption. Rules without path frontmatter load unconditionally. ( https://code.
claude.com/docs/en/memory )
Option B improves readability but leaves all 500-plus lines in every session. Option C can provide directory- specific CLAUDE.md guidance, but path-scoped rules are more precise when conventions depend on extensions or patterns spanning multiple directories. Option D still requires manual imports and does not provide the documented conditional rule-loading mechanism.
A suitable design would use rules such as terraform.md scoped to terraform/**/*.tf , kubernetes.md scoped to kubernetes/**/*.{yaml,yml} , and pipelines.md scoped to the pipeline directory. Broad project-wide commands and repository etiquette can remain in the root CLAUDE.md.
Official references/topics: .claude/rules/ ; Path-Specific Rules; YAML Frontmatter; Context-Efficient Instruction Loading.


NEW QUESTION # 17
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?

Answer: B

Explanation:
Option A uses the dedicated configuration mechanism for Anthropic's managed Code Review service. The official Code Review documentation states that a root-level REVIEW.md is injected into every review agent as the highest-priority instruction block. It can redefine severity, suppress categories already enforced by CI, skip generated paths, and require concrete evidence before particular findings are reported.
The proposed rules map directly to the observed noise. Skipping lint and formatting findings eliminates duplication with deterministic CI checks. Excluding src/gen/* prevents comments on machine-generated code. Requiring a specific source line demonstrating incorrect behavior raises the verification threshold for rendering-helper findings without suppressing genuine defects.
Options B and C configure self-hosted GitHub Actions workflows, but the scenario concerns managed Code Review running through the Claude GitHub App on Anthropic's infrastructure. Those workflow prompts do not govern the managed reviewer. Option D supplies useful general project context, but CLAUDE.md applies to all Claude Code tasks and has lower review-specific authority. The documentation states that REVIEW.md is the stronger control for changing what managed Code Review flags and how findings are reported. It therefore provides the most targeted solution with the least unnecessary infrastructure.


NEW QUESTION # 18
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