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Anthropic CCA-F Exam Syllabus Topics:

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

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q46-Q51):

NEW QUESTION # 46
When processing a batch of 10,000 documents via the Message Batches API, 45 requests fail due to context window limits. What is the recommended failure handling strategy?

A. Ignore the failures, as the API inherently guarantees a 99% success SLA.
B. Resubmit the entire batch of 10,000 requests to guarantee correct ordering.
C. Switch immediately to the synchronous API to retry the failed documents.
D. Resubmit only the failed documents (identified by their custom_id) after modifying them, such as chunking oversized documents.

Answer: D

Explanation:
Batch failures should be handled by identifying the specific failed requests using their custom_id, modifying them appropriately (e.g., chunking oversized documents to fit context limits), and resubmitting only those failed items.

NEW QUESTION # 47
A large pull request modifies 15 files. A single-pass review produces superficial comments and misses obvious cross-file bugs. How should you restructure the automated review architecture? Choose 2 correct answers.

A. Run three independent full reviews and require consensus before posting comments.
B. Switch to a higher-tier model with a larger context window to give all 15 files adequate attention in one pass.
C. Run a separate integration-focused pass examining cross-file data flow.
D. Split into focused passes: analyze each file individually for local issues.

Answer: C,D

Explanation:
Splitting large code reviews into per-file local analysis passes (to catch syntax/local logic bugs) plus a separate cross-file integration pass prevents attention dilution. Relying solely on larger context windows or requiring consensus across full monolithic runs are anti-patterns.

NEW QUESTION # 48
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 Bash to append the function definition to the end of the file using heredoc syntax
B. Use Read to load the file, add the function at the appropriate location, then Write the updated file
C. Use Edit's replace_all parameter to target a common pattern and embed the new function in the replacement text
D. Use Edit with an extremely long old_string capturing 30+ lines of context to guarantee uniqueness

Answer: B

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 # 49
An MCP server offers a templated resource to fetch specific documentation pages by ID. What is the correct URI syntax pattern utilized by the MCP Python SDK to represent this parameterized resource?

A. Option A
B. Option D
C. Option B
D. Option C

Answer: A

Explanation:
Templated resources in MCP utilize path parameters enclosed in braces, such as docs://documents/{doc_id}. The MCP Python SDK automatically parses these parameters from the URI and passes them as keyword arguments to the backing function.

NEW QUESTION # 50
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.
Your team has connected a custom MCP server that provides DevOps workflow templates. The server exposes several MCP prompts (such as deploy_checklist and incident_response) in addition to tools. How do these MCP prompts become accessible within Claude Code?

A. They are added to Claude Code's tool registry alongside the server's tools, invoked automatically by the model when relevant to the task.
B. They are surfaced as @-mentionable resources alongside files, fetched and attached to your message when referenced.
C. They are automatically prepended to every conversation as additional system-level context, influencing Claude's behavior throughout the session.
D. They appear as slash commands (e.g., mcp_servername_deploy_checklist) that you can invoke, with arguments passed after the command name.

Answer: D

Explanation:
Claude Code dynamically exposes MCP server prompts as commands using the format
/mcp__servername__promptname, such as /mcp__devops__deploy_checklist. Any prompt arguments are passed afterward, separated by spaces.

NEW QUESTION # 51
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