Quiz 2026 Anthropic CCA-F: Useful Claude Certified Architect Foundations (CCA-F) Valid Test Review

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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Tool Design & MCP Integration	18%	- Model Context Protocol (MCP) 1. Tool schema design 2. MCP client/server integration patterns
Topic 2: Prompt Engineering & Structured Output	20%	- Reliable structured generation 1. Prompt patterns for agents 2. Schema-guided outputs
Topic 3: Agentic Architecture & Orchestration	27%	- Agentic loop design and execution lifecycle 1. Multi-agent coordination and delegation patterns 2. Tool use decision flow (tool_use vs end_turn) - System orchestration patterns 1. Hub-and-spoke agent systems 2. Task decomposition strategies
Topic 4: Context Management & Reliability	15%	- Long-context optimization 1. Reliability and retry strategies 2. Context window management
Topic 5: Claude Code Workflows & Configuration	20%	- Claude Code operational patterns 1. Plan mode vs execution mode 2. CI/CD and workflow integration

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q78-Q83):

NEW QUESTION # 78
You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with Model Context Protocol (MCP) servers.
Your agent needs to insert a new helper function into the middle of a 150-line utility module, between two existing functions. The Edit tool fails because its old_string parameter cannot find unique text to match - the file has repetitive docstrings, variable names, and structural patterns.
What's the most reliable way to complete this insertion?

A. Use Edit with an extremely long old_string capturing 30+ lines of context to guarantee uniqueness
B. Use Edit's replace_all parameter to target a common pattern and embed the new function in the replacement text
C. Use Bash to append the function definition to the end of the file using heredoc syntax
D. Use Read to load the file, add the function at the appropriate location, then Write the updated file

Answer: D

Explanation:
When Edit cannot identify a unique match, rewriting the fully read file is the most reliable way to control the exact insertion point. The other options are brittle, place the function incorrectly, or risk unintended replacements.

NEW QUESTION # 79
After the web search and document analysis subagents complete their tasks, the coordinator needs to spawn the synthesis subagent to synthesize the findings. What is the correct approach for providing the synthesis subagent with the information it needs?

A. Pass reference identifiers and configure the subagent with read access to a shared memory store where other subagents deposited their results
B. Include the complete findings from both subagents directly in the synthesis subagent's prompt
C. Spawn the subagent with only a brief task description, relying on automatic context inheritance from the coordinator
D. Provide the subagent with tool definitions that allow it to request outputs from other subagents via callbacks

Answer: B

Explanation:
The synthesis subagent requires the actual content from prior subagents to perform its task.
Including the complete findings in its prompt ensures it has the necessary context to accurately synthesize information without relying on indirect references or external state.

NEW QUESTION # 80
What is the primary architectural difference between programmatic enforcement and prompt-based guidance in a multi-step workflow?

A. Prompt-based guidance is 100% reliable, whereas programmatic enforcement relies on probabilistic LLM reasoning.
B. Programmatic enforcement provides deterministic compliance (such as prerequisite gates), whereas prompt instructions have a non-zero failure rate.
C. Programmatic enforcement executes synchronously, while prompt guidance requires the Message Batches API.
D. Prompt-based guidance runs before tool execution, whereas programmatic enforcement only runs after tool execution.

Answer: B

Explanation:
Programmatic enforcement (such as hooks and prerequisite gates) executes as code, providing deterministic, 100% reliable guarantees. Prompt-based guidance relies on the LLM's probabilistic pattem matching, carrying a non-zero failure rate where the model may ignore the instructions.

NEW QUESTION # 81
Using the @anthropic-ai/claude-agent-sdk, you want to programmatically narrow the set of tools available to a specific query loop to prevent the agent from making unintended modifications. Which configuration is used to restrict tools in the SDK?

A. Set tool choice: "none" to force the model to only use search tools.
B. Inject a permissions: read-only tag into the top-level AgentDefinition.
C. Pass the allowedTooIs: [ " Read , '" ' Glob"] array inside the options object of the query() function.
D. Edit the . mcp. j son file to globally disable the write tools for the entire project.

Answer: C

Explanation:
In the @anthropic-ai/claude-agent-sdk, you restrict the toolset for a specific execution loop by passing the 'allowedTools' array (e.g., ["Read", "Glob")) in the options object of the 'query()' function. This maps to the CLI's -allowedTools flag.

NEW QUESTION # 82
The agent attempts to call a lookup_order tool, but the backend database is down due to a timeout. What structured error response should the tool return to the agent?

A. A structured object containing isError: true, an error category of 'timeout', isRetryab1e: true, and context of what was attempted.
B. An empty JSON array [J so the agent can smoothly transition to an alternative tool.
C. {"error : " A fatal exception that immediately terminates the agentic loop.
D. A generic string " Operation failed"} to avoid leaking infrastructure details to the LLM.

Answer: A

Explanation:
Silently returning an empty array for an access failure is a catastrophic anti-pattern that makes the agent think the data doesn't exist. Returning structured error metadata (isError, errorCategory, isRetryable, context) allows the agent to make intelligent recovery or escalation decisions.

NEW QUESTION # 83
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