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Anthropic CCA-F Exam Syllabus Topics:

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

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q97-Q102):

NEW QUESTION # 97
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. Use a Notification hook to alert a manager while simultaneously allowing the transaction to proceed.
B. Implement a tool call interception hook (e.g., PreToolUse or PostToolUse) that programmatically blocks the policy-violating action and redirects to an escalation workflow.
C. Provide 5 negative few-shot examples in the prompt demonstrating the agent refusing high-value refunds.
D. Include a capitalized, bold warning in the agent's system prompt forbidding refunds over $500.

Answer: B

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 # 98
Which of the following statements accurately describe the characteristics and constraints of the Message Batches API? Choose 2 correct answers.

A. It offers a 50% cost savings compared to standard synchronous API calls.
B. It uses custom_id fields to correlate asynchronous requests with their respective responses.
C. It provides a guaranteed I-hour latency SLA for enterprise tier accounts.
D. It is optimized to support interactive, real-time chatbot workflows at scale.

Answer: A,B

Explanation:
The Message Batches API provides a 50% cost savings over synchronous calls and utilizes custom_id fields for request/response correlation. It does not provide latency SLAs (taking up to 24 hours) and is definitely not for real-time chatbot workloads.

NEW QUESTION # 99
If the Edit tool fails to modify an existing file because it cannot find unique anchor text matching its targeted changes, which of the following represent valid, reliable fallback strategies? Choose 2 correct answers.

A. Use the Read tool to load the full file contents, followed by the Write tool to rewrite the entire file with the modifications applied.
B. Retry the Edit tool by modifying the target block to match a smaller, more specific and unique text segment.
C. Delete the file entirely using Bash, and rely on the Glob tool to recreate it from a cached state.
D. Use the Bash tool to execute a sed or awk command to force the text replacement regardless of unique anchors.

Answer: A,B

Explanation:
When Edit fails due to non-unique text matches, the recommended fallbacks are to either retry the Edit with a smaller, more unique text block, or use Read to load the full contents followed by Write to rewrite the file safely. Using Bash (like sed) to force replacements is an anti-pattern.

NEW QUESTION # 100
You are analyzing a massive legacy codebase and want to explore an alternative, potentially destructive refactoring approach without polluting your main session's context window. Which session management feature should you use?

A. / clear
B. / compact
C. - resume
D. fork session

Answer: D

Explanation:
The fork_session feature creates a branched session for exploration that inherits the existing context but keeps subsequent interactions isolated. This allows you to explore divergent approaches safely without exploration noise polluting your main conversation context.

NEW QUESTION # 101
When passing context between agents in a multi-agent orchestration, why is it highly recommended to use structured data formats?

A. To compress the token count of the prompt by 50% using the Message Batches API.
B. To bypass the maximum token limit of the subagent's isolated context window.
C. To automatically trigger JSON schema validation by the Claude API.
D. To separate content from metadata (such as source URLs, document names, and page numbers) to preserve proper attribution.

Answer: D

Explanation:
Using structured data formats to separate content from metadata (like source URLs, document names, and publication dates) when passing context between agents ensures that downstream synthesis agents preserve proper source attribution and information provenance.

NEW QUESTION # 102
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