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Anthropic CCAR-F Exam Syllabus Topics:

Section	Weight	Objectives
Prompt Engineering & Structured Output	20%	- System prompt design and persona alignment - JSON schema design and structured output enforcement - Validation, parsing and retry loop strategies - Explicit criteria definition and few-shot prompting
Context Management & Reliability	15%	- Context window optimization and prioritization - Idempotency, consistency and failure resilience - Token budget management and cost control - Context pruning and summarization strategies
Claude Code Configuration & Workflows	20%	- CLAUDE.md hierarchy, precedence and @import rules - Hooks vs advisory instructions - CI/CD integration and non-interactive mode parameters - Custom slash commands and plan mode vs direct execution - Path-specific rules and .claude/rules/ configuration
Agentic Architecture & Orchestration	27%	- Multi-agent patterns: coordinator-subagent and hub-and-spoke - Agentic loop design and stop_reason handling - Task decomposition and dynamic subagent selection - Error recovery, guardrails and safety patterns - Session state management and workflow enforcement
Tool Design & MCP Integration	18%	- Tool distribution and permission controls - Tool schema design and interface boundaries - Model Context Protocol (MCP) architecture and JSON-RPC 2.0 - MCP tool, resource and prompt implementation - Error handling and tool response formatting

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CCAR-F Prüfungsfragen Prüfungsvorbereitungen, CCAR-F Fragen und Antworten, Claude Certified Architect - Foundations

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Anthropic Claude Certified Architect - Foundations CCAR-F Prüfungsfragen mit Lösungen (Q82-Q87):

82. Frage
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 the agent to find all callers of a function before removing it. The function is defined in a core library but is also exposed through wrapper modules that rename the function for domain-specific use (e.
g., calculateTax in the library becomes computeOrderTax in the orders module).
What exploration strategy will most reliably identify all callers?

A. Read the library and wrapper modules to identify all exposed names for the function, then Grep for each name across the codebase.
B. Use Grep to find all files that import from the library or wrapper modules, then read each file to check whether it uses the function.
C. Use Grep to search for the function's original name across the codebase.
D. Search for the function name in project documentation to understand intended usage patterns and navigate to documented integration points.

Antwort: A

Begründung:
The search must first establish the function's complete naming surface. Reading the core definition and every wrapper or re-export reveals aliases such as computeOrderTax , names introduced through intermediate modules, and potentially different import paths. Once those names are known, the agent can search the entire codebase for each exposed identifier and inspect the resulting call sites.
Claude Code's Grep tool searches patterns inside file contents, whereas Read provides the surrounding implementation needed to determine whether a wrapper delegates to, renames, or conditionally invokes the original function. These tools are complementary: Read establishes semantic identity; Grep provides broad reference discovery. ( https://code.claude.com/docs/en/tools-reference?utm_source=chatgpt.com ) Option B misses every caller using a wrapper alias. Option A may find importing files, but import-level discovery is indirect and can miss re-exports, namespace imports, dependency injection, or calls made through a locally renamed symbol. It also requires unnecessary manual inspection of every consumer of the module. Option D relies on documentation, which may be incomplete or stale and cannot prove that all executable references have been found.
Before removal, the agent should also inspect tests, dynamic registrations, configuration-driven references, and generated code where relevant. The defining requirement is to map the alias chain first and then search all discovered public names.
Official references/topics: Read and Grep Tool Behavior; Symbol and Alias Discovery; Codebase Reference Tracing.

83. Frage
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 the agent to find all files in the monorepo that import the @company/auth package to understand how authentication is used across services. Which built-in tool is most appropriate for this task?

A. Bash, to execute find. -type d -name "*auth*" and explore matching directories
B. Read, starting with package.json files to trace dependency declarations
C. Glob, to find files with "auth" in their filename or path
D. Grep, to search for the import statement pattern across file contents

Antwort: D

Begründung:
Grep searches file contents across the repository, making it the correct tool for locating every source file that imports @company/auth. Glob searches filenames and paths, not code content.

84. Frage
Your send_notification tool calls third-party messaging APIs. When these services time out during delivery, you cannot determine whether the message was actually sent. Currently, the tool returns is_error: true with a generic "Notification failed" message for all timeouts. Production monitoring reveals agents automatically retry these failures, frequently causing users to receive duplicate notifications. How should you modify the error response?

A. Return is_error: true with a message encouraging retry: "Delivery service temporarily unavailable.
Please retry the notification."
B. Return is_error: true with the original message content echoed back.
C. Return is_error: true with a structured field retry_safe: true for timeouts, distinguishing them from permanent failures that should not be retried.
D. Return is_error: true with a message communicating uncertainty: "Timeout - status unknown.
Message may have been sent. Avoid retry."

Antwort: C

Begründung:
Adding a structured retry_safe flag distinguishes uncertain, potentially idempotent errors from permanent failures. This allows the agent to make informed decisions about automatic retries, preventing duplicate notifications while maintaining reliability for recoverable errors.

85. Frage
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 add comprehensive tests to a legacy codebase with 200 files and minimal existing test coverage. The engineer hasn't specified which modules to prioritize.
How should the agent decompose this open-ended task?

A. Start writing tests for the first module alphabetically, using test failures and imports to discover related files organically.
B. Create a fixed testing schedule upfront based on directory structure, allocating equal effort to each top- level directory regardless of code complexity or business importance.
C. Systematically read all 200 files to create a complete function inventory before writing any tests, ensuring the testing plan accounts for every function before beginning.
D. Use Glob and Grep to map codebase structure, identify heavily-coupled modules, create a prioritized plan for high-impact areas, and revise as dependencies are discovered.

Antwort: D

Begründung:
The task is open-ended because neither the critical modules nor the required testing sequence is known in advance. The agent should first use lightweight discovery tools to map the repository, locate existing tests, identify central modules, and determine which components have high fan-in, business significance, complex branching, or extensive external dependencies. It can then produce an initial risk-based testing plan and refine it as new dependency information appears.
Anthropic distinguishes predefined workflows from agents that dynamically control their processes and tool usage. Agents are appropriate when the required steps cannot be reliably hardcoded and must adapt to environmental evidence. During execution, they should obtain ground truth through tool results and use that feedback to determine subsequent actions. ( https://www.anthropic.com/research/building-effective-agents ) Anthropic also identifies orchestrator-worker designs as suitable for complex coding and search tasks where the necessary subtasks depend on what the investigation reveals. ( https://www.anthropic.com/research
/building-effective-agents )
Option A assigns effort using directory boundaries rather than risk. Option C exhausts context before delivering value. Option D uses alphabetical order, which has no relationship to impact or coverage priority.
Option B establishes an evidence-driven decomposition: discover, prioritize, test high-impact paths, measure results, and revise the plan as dependencies and uncovered risks emerge.
Official references/topics: Dynamic Task Decomposition; Adaptive Agent Loops; Orchestrator-Workers; Risk-Based Test Planning.

86. Frage
Your agent is handling a billing dispute. After calling get_customer and lookup_order, it identifies that the dispute involves a promotional pricing error requiring manager approval - beyond the agent's authorization level. How should the workflow handle this mid-process escalation?

A. Attempt the refund with process_refund anyway, escalating only if the system rejects the transaction.
B. Persist the complete conversation and tool response history to a database, then call escalate_to_human with a reference ID.
C. Compile a structured handoff with customer details, order info, and the identified issue before calling escalate_to_human.
D. Call escalate_to_human passing only the customer's original message.

Antwort: C

Begründung:
A structured handoff containing the customer details, order information, and the specific issue ensures the human agent has all relevant context to act immediately. This approach avoids delays or repeated clarification and preserves continuity when authority limits prevent the agent from completing the task.

87. Frage
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