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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Claude Code Configuration & Workflows	20%	- CI/CD and development integration 1. Plan mode vs direct execution 2. Pipeline automation and review - Configuration files and structure 1. CLAUDE.md and rules system 2. Custom commands and workflows
Topic 2: 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
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. Refusal handling and risk mitigation 2. Constitutional AI principles
Topic 4: Prompt Engineering & Structured Output	20%	- Advanced prompting techniques 1. Few-shot and chain-of-thought prompting 2. System prompts and role framing - Structured data generation 1. Output validation and reliability 2. JSON schema enforcement
Topic 5: Agentic Architecture & Orchestration	27%	- Agent design patterns 1. Hub-and-spoke multi-agent systems 2. Agent loops and control flow - Anthropic Agent SDK usage 1. Task spawning and tool management 2. Session state and context handling

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q52-Q57):

NEW QUESTION # 52
Which of the following strategies are highly recommended for integrating Claude into a robust test generation workflow? Choose 2 correct answers.

A. Execute tests automatically within a PreToolUse hook to prevent Claude from saving failing code.
B. Document testing standards, valuable test criteria, and available fixtures in the project-level CLAUDE .md.
C. Rely on aggregate test coverage metrics to determine if the generated tests are semantically correct.
D. Share specific test failure outputs with Claude to guide progressive improvement of the implementation.

Answer: B,D

Explanation:
Documenting testing standards and fixtures in CLAUDE.md ensures baseline consistency across the project. Sharing test failures guides iterative refinement, enabling the model to self-correct. PreToolUse hooks block execution and cannot run tests automatically on unsaved code, while aggregate metrics mask semantic correctness issues.

NEW QUESTION # 53
Which tool must be explicitly included in a coordinator agent's configuration to enable spawning subagents?

A. Spawn
B. SubAgent
C. Fork
D. Task

Answer: D

Explanation:
The Task tool is the designated mechanism used for spawning subagents. A critical configuration requirement is that the coordinator's allowedTools array must explicitly include the 'Task' tool to enable subagent creation.

NEW QUESTION # 54
Production logs show that when the agent handles complex billing disputes requiring 6+ tool calls, it sometimes exhausts its max_turns limit after gathering data but before completing resolution or escalating. The team's goal is to guarantee that every customer interaction ends with either a completed resolution or a human handoff, regardless of how the agent loop terminates. Which approach achieves this guarantee?

A. Add system prompt instructions telling the agent to call escalate_to_human with a summary of its findings whenever it determines it cannot complete resolution within its remaining actions.
B. Split the workflow into two sequential agent invocations - a first agent gathers information via get_customer and lookup_order, then a second agent receives that data and handles process_refund or escalate_to_human, each with separate turn budgets.
C. Add orchestration-layer code that checks the agent's outcome after each loop termination - if the loop ended without a completed resolution or escalation, programmatically call escalate_to_human with the accumulated conversation context and tool results.
D. Implement a pre-tool-use hook that counts tool invocations and terminates the loop with an automatic escalation once the agent reaches 80% of its max_turns limit.

Answer: C

Explanation:
A system prompt cannot guarantee compliance, and turn-count hooks may escalate prematurely.
An orchestration-level fallback runs regardless of why the agent loop stopped, ensuring every interaction ends in either resolution or human escalation.

NEW QUESTION # 55
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're implementing a new payment processing module that must follow your project's established patterns for database transactions, error handling, and audit logging. You've identified three existing modules that exemplify these patterns: db_utils.py, error_handlers.py, and audit_logger.py. This is a one-off integration task - these patterns are well-documented in your team wiki and don't need additional project-level documentation. What's the most effective approach?

A. Describe the patterns from the three modules in natural language in your prompt, explaining the transaction handling approach, error format, and logging conventions Claude should follow.
B. Add documentation of each pattern to your CLAUDE.md file, establishing them as project conventions that Claude will apply automatically.
C. Use @ references to include the three modules directly in your prompt, giving Claude concrete code examples of the patterns to follow.
D. Ask Claude to explore your codebase to find and understand the transaction, error handling, and logging patterns before generating the new module.

Answer: C

Explanation:
This is a one-off task, so directly attaching the relevant files gives Claude concrete, authoritative examples without permanently expanding CLAUDE.md. Claude Code supports @ references specifically for bringing files or directories into the current task's context.

NEW QUESTION # 56
An automated pipeline is using a PreToolUse hook to block unauthorized file reads by evaluating the requested file path. How does the hook command properly communicate to Claude *why* the action was blocked so the agent can adjust its behavior?

A. By silently terminating the session and initiating a new one with an updated system prompt.
B. By overriding the context window entirely with a generic access denied template.
C. By returning an exit code of 2 and writing the explanation to standard error, which is fed back to Claude as feedback.
D. By returning an empty JSON array [] on standard output.

Answer: C

Explanation:
In Claude Code hooks, an exit code of 2 in a PreToolUse hook blocks the tool call. Any message written to standard error (stderr) is fed back directly to Claude as feedback, explaining exactly why the operation was blocked so the model can adapt.

NEW QUESTION # 57
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