CCA-F Quizfragen Und Antworten - CCA-F Zertifizierung

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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Tool Design & MCP Integration	18%	- Tool definition and best practices 1. Error handling and validation 2. Tool descriptions and selection logic - Model Context Protocol (MCP) 1. Tools, resources, and prompts integration 2. MCP server and client setup
Context Management & Responsible AI	15%	- Safety and compliance 1. Refusal handling and risk mitigation 2. Constitutional AI principles - Context window optimization 1. Context retention and summarization 2. Token management and truncation strategies
Agentic Architecture & Orchestration	27%	- Anthropic Agent SDK usage 1. Task spawning and tool management 2. Session state and context handling - Agent design patterns 1. Hub-and-spoke multi-agent systems 2. Agent loops and control flow
Claude Code Configuration & Workflows	20%	- CI/CD and development integration 1. Pipeline automation and review 2. Plan mode vs direct execution - Configuration files and structure 1. Custom commands and workflows 2. CLAUDE.md and rules system
Prompt Engineering & Structured Output	20%	- Advanced prompting techniques 1. Few-shot and chain-of-thought prompting 2. System prompts and role framing - Structured data generation 1. Output validation and reliability 2. JSON schema enforcement

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Anthropic Claude Certified Architect Foundations (CCA-F) CCA-F Prüfungsfragen mit Lösungen (Q99-Q104):

99. Frage
During an extended codebase exploration session, the context window fills with verbose discovery output and tool results, leading to degraded reasoning. Which built-in command is designed to mitigate this issue while preserving key session findings?

A. / compact
B. fork_session
C. / init
D. / clear

Antwort: A

Begründung:
The /compact command is specifically designed to compress conversation history and reduce context usage during extended exploration sessions. It frees up context space while attempting to preserve the essential knowledge Claude has accumulated, unlike /clear which completely wipes the slate clean.

100. Frage
An architect is designing an MCP tool that occasionally fails due to downstream rate limits. Which fields should be included in a well- designed structured error response to help the agent recover? Choose 2 correct answers.

A. isRetryable: true
B. system_prompt_override
C. temperature _ adjustment
D. isError: true

Antwort: A,D

Begründung:
A structured error response should explicitly signal a failure using the 'isError' flag and indicate if the agent should attempt the call again using the 'isRetryable' boolean. It should also include the error category and context. System prompt overrides and temperature adjustments are not part of standard tool error metadata.

101. Frage
During a long-running customer support session, the agent repeatedly summarizes the conversation history to save context space. By turn 10, the agent forgets the customer's specific account number and the exact promotional price they were quoted. How should you redesign the context management to prevent this?

A. Increase the frequency of progressive summarization to occur every 2 turns instead of 5.
B. Extract transactional facts into an immutable 'case facts' block positioned at the start of the context that is never summarized.
C. Store the conversation in an external database and run a lexical search query on every turn.
D. Restart the session from scratch after 5 turns and ask the customer to repeat their details.

Antwort: B

Begründung:
Progressive summarization silently destroys critical details over time. The solution is to use 'case facts' blocks-immutable, structured reference sections placed at the high-recall beginning of the context window that preserve critical information without being compressed.

102. Frage
How does a coordinator agent most efficiently execute multiple subagents in parallel to accelerate a research pipeline?

A. By calling the parallel_execute method natively provided in the Claude Agent SDK.
B. By invoking the fork_session command across different isolated branches sequentially.
C. By setting tool _choice: 'any" alongside parallel threading parameters.
D. By emitting multiple Task tool calls within a single coordinator response.

Antwort: D

Begründung:
Spawning parallel subagents is effectively accomplished by emitting multiple Task tool calls in a single coordinator response rather than across separate turns. This allows the system to process the corresponding subtasks simultaneously.

103. Frage
When implementing multi-turn conversations with tool usage in the Claude API, how must the application handle the follow-up request after executing a tool?

A. Pass the tool result inside an assistant message with an is_error flag.
B. Use the /compact command to summarize the tool output before returning it.
C. Append a user message containing a tool_result block with the matching tool_use_id, and include the full prior conversation history.
D. Send only the new tool result to save token context space in the context window.

Antwort: C

Begründung:
Because Claude is stateless and does not remember past turns, you must provide the entire conversation history. When returning a tool result, it must be appended as a user message containing a tool_result block that includes the specific tool_use_id matching the request.

104. Frage
......

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