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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Context Management & Reliability	15%	- Long-context optimization 1. Context window management 2. Reliability and retry strategies
Agentic Architecture & Orchestration	27%	- Agentic loop design and execution lifecycle 1. Tool use decision flow (tool_use vs end_turn) 2. Multi-agent coordination and delegation patterns - System orchestration patterns 1. Task decomposition strategies 2. Hub-and-spoke agent systems
Claude Code Workflows & Configuration	20%	- Claude Code operational patterns 1. CI/CD and workflow integration 2. Plan mode vs execution mode
Tool Design & MCP Integration	18%	- Model Context Protocol (MCP) 1. MCP client/server integration patterns 2. Tool schema design
Prompt Engineering & Structured Output	20%	- Reliable structured generation 1. Schema-guided outputs 2. Prompt patterns for agents

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q14-Q19):

NEW QUESTION # 14
You must deterministically block any refund transaction exceeding $500 and redirect it to a human supervisor. How should you implement this using the Claude Agent SDK?

A. Implement a tool call interception hook (e.g., PreToolUse or PostToolUse) that programmatically blocks the policy-violating action and redirects to an escalation workflow.
B. Provide 5 negative few-shot examples in the prompt demonstrating the agent refusing high-value refunds.
C. Include a capitalized, bold warning in the agent's system prompt forbidding refunds over $500.
D. Use a Notification hook to alert a manager while simultaneously allowing the transaction to proceed.

Answer: A

Explanation:
When business rules require guaranteed compliance, tool call interception hooks must be used to block policy-violating actions (like high-value refunds) and securely redirect to alternative workflows. Prompt warnings and few-shot examples are probabilistic and can be ignored.

NEW QUESTION # 15
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. Split content into subdirectory CLAUDE.md files (/terraform/CLAUDE.md,
/kubernetes/CLAUDE.md), so Claude loads directory-specific guidance.
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. Create files in .claude/rules/ with YAML frontmatter path-scoping (e.g., paths: ["terraform/**/*"]), loading rules only when editing matching files.

Answer: D

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 # 16
While working in Claude Code, you press Shift + Tab to enter Plan Mode. Which subagent is typically associated with isolating the verbose discovery phase to prevent context window exhaustion during planning?

A. The Review subagent
B. The Write subagent
C. The Plan-Executor subagent
D. The Explore subagent

Answer: D

Explanation:
The Explore subagent is used for isolating verbose discovery output and returning focused summaries to preserve the main conversation's context window during the research and planning phase.

NEW QUESTION # 17
To keep the main agent's context clean while investigating a complex authentication flow, which architectural pattern is highly recommended?

A. Spawn a subagent to isolate the verbose exploration output, returning only a focused summary to the main agent.
B. Apply progressive summarization to the main conversation history every 2 turns.
C. Use the fork_session command to duplicate the main agent permanently.
D. Use the Message Batches API to process the exploration synchronously.

Answer: A

Explanation:
Subagent delegation is the recommended pattern to isolate verbose exploration output (like reading multiple files and tracing functions) from the main coordinator. The subagent does the heavy lifting in its own isolated context and returns only a clean synthesis to the main agent.

NEW QUESTION # 18
Which of the following statements represent correct principles of multi-agent orchestration design? Choose 2 correct answers.

A. The coordinator should route all inter-subagent communication to maintain observability and consistent error handling.
B. A flat architecture where all agents share a global state is generally preferred over a hub-and-spoke architecture.
C. Subagents should automatically inherit the coordinator's memory across invocations to save token costs.
D. Parallel execution of subagents is achieved by emitting multiple Task tool calls in a single coordinator response.

Answer: A,D

Explanation:
Parallel execution is properly implemented by having the coordinator emit multiple Task tool calls in a single turn. Furthermore, in a hub-and-spoke architecture, the coordinator routes all inter-agent communication, providing observability and controlled information flow. Flat architectures with global state and automatic memory inheritance are anti-patterns leading to context exhaustion.

NEW QUESTION # 19
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