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Anthropic CCA-F Exam Syllabus Topics:

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

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q23-Q28):

NEW QUESTION # 23
To prevent Claude from fabricating values when a requested field is absent from the source document, how should you engineer your JSON extraction schema?

A. Reduce the temperature to 0.0 to eliminate hallucinations.
B. Set the tool parameter tool_choice: " any".
C. Add a system prompt instruction to "never fabricate data".
D. Design the field with "type" : [" string ,"null"] and mark it as optional/nullable.

Answer: D

Explanation:
If a field is strictly required but the data doesn't exist, the model may fabricate a value to satisfy the schema constraint. Making the field optional or nullable (e.g., allowing 'null') provides a valid escape hatch so the model can comply with the schema without hallucinating.

NEW QUESTION # 24
While configuring prompt engineering standards for a production application, you must decide when to implement few-shot examples. Which of the following scenarios represent the most effective use cases for few-shot prompting? Choose 2 correct answers.

A. Ambiguous classification tasks where the boundaries between categories are fuzzy or subjective.
B. Tasks requiring standard output formats like valid JSON, where tool_use is already implemented.
C. Simple, well-defined data extraction tasks with clear objective criteria.
D. Tasks requiring a custom, non-standard output format that Claude does not handle natively.

Answer: A,D

Explanation:
Few-shot prompting is most valuable when the task has ambiguous boundaries (like detecting sarcasm) or requires custom output formats that aren't standard. It is generally unnecessary for simple, well-defined tasks or standard formats like JSON which are better handled natively or via tool_use.

NEW QUESTION # 25
What configuration is strictly required for a coordinator agent to be able to spawn subagents?

A. A PreToolUse hook must be registered to manage process limits.
B. The agent must be executed in plan mode rather than direct execution.
C. The coordinator's allowedTools array must explicitly include the Task tool.
D. The tool_choice parameter must be set to 'auto'.

Answer: C

Explanation:
The Task tool is the mechanism used for spawning subagents. For a coordinator to invoke subagents, its allowedTools configuration must explicitly include 'Task'.

NEW QUESTION # 26
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.

Answer: D

Explanation:
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.

NEW QUESTION # 27
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. Enter plan mode first to create a detailed implementation strategy before making the change.
C. Enter plan mode to analyze how the validation might impact other parts of the reservation flow.
D. Start with extended thinking mode enabled to ensure thorough reasoning about the validation logic.

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 # 28
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