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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Agentic Architecture & Orchestration	27%	- Anthropic Agent SDK usage 1. Task spawning and tool management 2. Session state and context handling - Agent design patterns 1. Agent loops and control flow 2. Hub-and-spoke multi-agent systems
Topic 2: Prompt Engineering & Structured Output	20%	- Structured data generation 1. JSON schema enforcement 2. Output validation and reliability - Advanced prompting techniques 1. Few-shot and chain-of-thought prompting 2. System prompts and role framing
Topic 3: Context Management & Responsible AI	15%	- Context window optimization 1. Token management and truncation strategies 2. Context retention and summarization - Safety and compliance 1. Constitutional AI principles 2. Refusal handling and risk mitigation
Topic 4: Tool Design & MCP Integration	18%	- Tool definition and best practices 1. Tool descriptions and selection logic 2. Error handling and validation - Model Context Protocol (MCP) 1. Tools, resources, and prompts integration 2. MCP server and client setup
Topic 5: 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

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q37-Q42):

NEW QUESTION # 37
What is the PRIMARY purpose of few-shot prompting?

A. Encrypt prompts.
B. Demonstrate desired output patterns.
C. Reduce token costs.
D. Increase model size.

Answer: B

Explanation:
Few-shot prompting provides representative examples that illustrate the desired task and response style. Claude learns from these examples within the prompt, improving consistency without requiring model retraining.

NEW QUESTION # 38
According to best practices, which of the following scenarios should trigger a developer to use Plan Mode in Claude Code? Choose 2 correct answers.

A. When evaluating multiple valid approaches for a new feature implementation.
B. When implementing multi-file architectural changes.
C. When adding a single console. log statement to a known file.
D. When fixing a minor typo in project documentation.

Answer: A,B

Explanation:
Plan mode is specifically designed for complex tasks that involve multiple valid approaches, architectural decisions, and multi-file modifications. Simple, well-defined fixes like fixing typos or adding single log statements should use Direct Execution to avoid unnecessary overhead.

NEW QUESTION # 39
A customer support agent handles high-ambiguity requests. Which of the following is a valid, architecturally sound trigger for escalating a case to a human agent?

A. The conversation exceeds 10 turns.
B. The customer exhibits highly negative sentiment.
C. The agent detects a policy gap not covered by its existing rules.
D. The model's self-reported confidence score drops below 0.7.

Answer: C

Explanation:
Valid escalation triggers include policy gaps (situation not covered by rules), explicit customer requests for a human, capability limits, and business thresholds. Sentiment and self-reported confidence are unreliable metrics for escalation.

NEW QUESTION # 40
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?

A. Create files in .claude/rules/ with YAML frontmatter path-scoping (e.g., paths: ["terraform/**/*"]), loading rules only when editing matching files.
B. Keep the root CLAUDE.md and use @path/to/import syntax to modularly include tool-specific guidance files from separate documents.
C. Restructure the root CLAUDE.md into clearly labeled sections with headers (e.g, "## Terraform Conventions"), improving organization and readability.
D. Split content into subdirectory CLAUDE.md files (/terraform/CLAUDE.md,
/kubernetes/CLAUDE.md), so Claude loads directory-specific guidance.

Answer: A

Explanation:
The paths field conditionally loads each rule only when Claude works with matching files, preventing unrelated Terraform, Kubernetes, or pipeline guidance from consuming context.
Subdirectory CLAUDE.md files are directory-based, while path-scoped rules provide precise file- pattern targeting.

NEW QUESTION # 41
To guarantee that a specific data extraction tool is invoked by Claude during a workflow without the agent attempting conversational workarounds, which configuration must be applied?

A. tool_choice: {"type": "tool", "name": "SPECIFIC_TOOL NAME"}
B. allowedTools: ["SPECIFIC_TOOL NAME"}
C. tool_choice: "any"
D. tool choice: "auto"

Answer: A

Explanation:
Forcing a specific tool with tool_choice: {"type": "tool", "name": "..."} ensures a particular tool runs, which guarantees schema compliance for strict extraction tasks. "any" forces the model to pick a tool, but lets it decide which one. "auto" lets the model decide if it wants to use a tool at all.

NEW QUESTION # 42
......

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