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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Context Management & Reliability	15%	- Context window optimization 1. Managing long conversation degradation 2. "Lost in the middle" mitigation strategies - System reliability 1. Escalation strategies (fail vs retry vs human) 2. Error propagation handling
Topic 2: Tool Design & MCP Integration	18%	- Tool interface design 1. Structured tool input/output schemas 2. Clear tool descriptions and boundaries - Model Context Protocol (MCP) 1. Tool selection and routing strategies 2. MCP server integration patterns
Topic 3: Claude Code Configuration & Workflows	20%	- Claude Code configuration 1. CLAUDE.md hierarchy and scoping 2. Project-level vs user-level configuration - CI/CD and workflow integration 1. Automated pipeline integration 2. Command vs plan mode usage
Topic 4: Prompt Engineering & Structured Output	20%	- Instruction design 1. Few-shot prompting strategies 2. Deterministic output formatting (e.g., JSON) - Tool-augmented prompting 1. Tool-use driven reasoning patterns 2. Validation and retry loops
Topic 5: Agentic Architecture & Orchestration	27%	- Multi-agent orchestration 1. Parallel task decomposition 2. Coordinator / sub-agent patterns - Agentic loops & lifecycle design 1. Tool use loop execution (request → tool_use → result → next step) 2. Stop reason handling and control flow

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CCA-F Praxisprüfung - CCA-F Deutsch Prüfungsfragen

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

82. Frage
In a coordinator-subagent research system, a web search subagent times out while attempting to retrieve information on a complex topic. How should this failure be propagated back to the coordinator agent?

A. The subagent should catch the timeout and return an empty JSON array L] marked as successful so the workflow continues smoothly.
B. Propagate the timeout exception directly to a top-level handler to immediately terminate the entire research workflow.
C. Return structured error context to the coordinator, including the failure type, the attempted query, any partial results, and potential alternative approaches.
D. Implement automatic retry logic indefinitely within the subagent, returning a generic search unavailable status if it ultimately fails.

Antwort: C

Begründung:
Structured error propagation is critical. Returning structured error context (failure type, what was attempted, partial results) enables the coordinator to make an intelligent recovery decision. Silently suppressing the error by returning an empty result is a severe anti-pattern, and returning generic messages hides context needed for recovery.

83. Frage
When designing an automated code review system for a large repository, you notice that developers are experiencing 'alert fatigue' because the AI flags too many non-issues and stylistic preferences. What is the most effective prompt engineering technique to reduce these false positives?

A. Define explicit, measurable review criteria, such as flag functions exceeding 50 lines of code, instead of relying on vague instructions.
B. Provide at least 15 few-shot examples covering every possible coding style in the repository.
C. Set the model's temperature to 0.0 to ensure deterministic output and eliminate all false positives.
D. Instruct the model to be thorough and flag everything suspicious to ensure no bugs are missed.

Antwort: A

Begründung:
Explicit, measurable criteria produce consistent, actionable results that build developer trust and reduce false positives. Vague instructions like 'be thorough' lead to over-flagging and alert fatigue. Temperature adjustments do not fix vague criteria, and providing 15 few-shot examples bloats the prompt without proportional benefit.

84. Frage
Production monitoring shows that follow-up queries like "summarize what we learned about market trends" consistently take 40+ seconds. Investigation reveals the coordinator spawns the synthesis subagent for each summarization request, passing 80K+ tokens of accumulated findings. The coordinator already has these findings in its context from orchestrating the research.
What's the most effective way to improve response time for these follow-up summaries?

A. Enable prompt caching on the synthesis subagent to reduce the overhead of repeatedly transferring the same research findings.
B. Spawn the synthesis subagent with reduced context and have it request specific findings from the coordinator on-demand.
C. Pre-generate and cache summaries at multiple granularities whenever new findings accumulate.
D. Have the coordinator handle straightforward summarization requests directly using its existing context, reserving subagent spawning for complex analysis.

Antwort: D

Begründung:
The coordinator already holds the accumulated findings and can perform simple summarizations directly. Avoiding repeated spawning of the synthesis subagent for straightforward queries reduces token processing and latency, improving response speed while maintaining accuracy.

85. Frage
During long-running customer support sessions, an agent repeatedly summarizes the conversation history. Over time, it forgets the customer's exact account ID and order amount. What architectural pattern best prevents this specific context degradation?

A. Increasing the summarization frequency to occur every 3 turns instead of every 10 turns.
B. Utilizing the ---resume flag to inject the entire historical database record.
C. Switching to a model with a larger context window and disabling summarization entirely.
D. Extracting transactional facts into an immutable "case facts" block positioned at the start of the context window.

Antwort: D

Begründung:
Progressive summarization silently destroys critical details over time. Extracting transactional facts into a persistent "case facts" block included in each prompt, outside summarized history, mitigates this issue.

86. Frage
In a hub-and-spoke multi-agent architecture, what is the best practice for passing context from the coordinator agent down to a specialized subagent?

A. Rely on automatic context inheritance, as subagents inherently share the coordinator's memory.
B. Share the entire coordinator conversation history to ensure the subagent has maximum context visibility.
C. Grant the subagent access to a shared global state object where the coordinator writes its findings.
D. Pass only the explicit context, findings, and parameters specifically relevant to that subagent's assigned subtask.

Antwort: D

Begründung:
Context isolation is a core principle of multi-agent orchestration. Subagents do not automatically inherit parent context and should not receive the full conversation history, as this causes context pollution and wastes tokens. They should only be passed explicit, relevant context specific to their task.

87. Frage
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