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

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q102-Q107):

NEW QUESTION # 102
Why is providing more than 6 examples in a few-shot prompt generally considered an anti-pattern?

A. It disables the model's ability to use the tool_use block.
B. It causes the model to ignore system prompts.
C. It forces the Claude API to throw a schema validation error.
D. It bloats the prompt context window without adding proportional benefit.

Answer: D

Explanation:
Providing too many examples (more than 4-6) wastes valuable context window tokens and bloats the prompt without offering a proportional increase in output quality or instruction adherence.

NEW QUESTION # 103
Why is it heavily recommended to use Agent SDK hooks rather than prompt instructions to enforce critical business rules in a application?

A. Hooks provide deterministic guarantees, whereas prompt instructions rely on probabilistic compliance and carry a non-zero failure rate.
B. Hooks inherently consume zero tokens from the context window.
C. Hooks automatically implement strict JSON schema validation for all tool_use calls.
D. Prompt instructions cannot be modified without restarting the entire MCP server architecture.

Answer: A

Explanation:
The core distinction is that hooks run as programmatic code, providing deterministic, 100% reliable enforcement for business policies. Prompts rely on the LLM's probabilistic pattern matching, meaning the model can and occasionally will ignore critical instructions.

NEW QUESTION # 104
In a multi-agent system, a subagent times out querying a database. How should this error be propagated back to the coordinator agent?

A. Propagate the exception directly to a top-level handler to terminate the entire workflow.
B. Catch the timeout and return an empty result set marked as successful to keep the workflow moving.
C. Return structured error context including the failure type, what was attempted, and partial results.
D. Return a generic string {"error": "Operation failed"}.

Answer: C

Explanation:
Structured error propagation is critical. Returning structured error context (failure type, what was attempted, partial results) enables the coordinator to make intelligent recovery decisions. Silently returning empty results or terminating the whole workflow immediately are anti-patterns.

NEW QUESTION # 105
Which of the following scenarios is the most appropriate use case for selecting Direct Execution rather than Plan Mode?

A. Restructuring a monolithic application into discrete microservices.
B. Adding a date validation conditional to a single, specific utility function.
C. Redesigning the database schema and updating all corresponding data access objects.
D. Evaluating multiple integration approaches for a new third-party payment provider.

Answer: B

Explanation:
Direct execution is highly appropriate for simple, well-scoped changes with a clear boundary, such as adding a validation conditional to one function. Complex tasks involving architectural decisions or multi-file restructuring require Plan Mode.

NEW QUESTION # 106
When configuring a project-level Jira Model Context Protocol (MCP) server for a development team, what is the required method for securely managing authentication credentials?

A. Store the credentials in an encrypted secrets .json file referenced by the CLAUDE .md configuration.
B. Hardcode the API tokens directly in the .mcp.json file to ensure all team members can access the integration.
C. Define the server in the project-scoped .mcp.json file using environment variable expansion like ${JIRA_TOKEN}.
D. Configure the server in the user-scoped ~/ . claude. json file so credentials remain local to each developer.

Answer: C

Explanation:
Project-level MCP configurations that are shared via version control must use the .mcp.json file. To prevent leaking credentials, environment variable expansion syntax (e.g., ${JIRA TOKEN}) is required so the secrets remain in the local environment and out of the codebase.

NEW QUESTION # 107
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