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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Tool Design & MCP Integration	18%	- Tool interface design 1. Clear tool descriptions and boundaries 2. Structured tool input/output schemas - Model Context Protocol (MCP) 1. Tool selection and routing strategies 2. MCP server integration patterns
Context Management & Reliability	15%	- System reliability 1. Error propagation handling 2. Escalation strategies (fail vs retry vs human) - Context window optimization 1. "Lost in the middle" mitigation strategies 2. Managing long conversation degradation
Agentic Architecture & Orchestration	27%	- Multi-agent orchestration 1. Parallel task decomposition 2. Coordinator / sub-agent patterns - Agentic loops & lifecycle design 1. Stop reason handling and control flow 2. Tool use loop execution (request → tool_use → result → next step)
Prompt Engineering & Structured Output	20%	- Instruction design 1. Deterministic output formatting (e.g., JSON) 2. Few-shot prompting strategies - Tool-augmented prompting 1. Validation and retry loops 2. Tool-use driven reasoning patterns
Claude Code Configuration & Workflows	20%	- Claude Code configuration 1. CLAUDE.md hierarchy and scoping 2. Project-level vs user-level configuration - CI/CD and workflow integration 1. Command vs plan mode usage 2. Automated pipeline integration

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q32-Q37):

NEW QUESTION # 32
Your MCP server exposes a Templated Resource with the URI pattern docs://documents/{doc_id}. How does the MCP Python SDK handle this pattern?

A. It requires the client to pass the doc_id via an HTTP POST body.
B. It requires the model to write a regex to extract the doc_id before passing it to the server.
C. It automatically parses the doc_id from the URI and passes it as a keyword argument to the underlying resource function.
D. It treats the entire URI as a static string and expects the function to manually parse it.

Answer: C

Explanation:
For templated resources, the MCP Python SDK automatically parses parameters from the URI structure (like '{doc_id}') and passes them directly as keyword arguments to your Python function, avoiding manual string parsing.

NEW QUESTION # 33
You are designing a security-sensitive skill that audits code for vulnerabilities. You want to guarantee that this skill can only analyze files and cannot accidentally modify the codebase. How is this enforced?

A. By executing the skill inside a stateless Docker container using the Bash tool.
B. By adding a strong warning in the SKILL.md markdown text: "DO NOT USE WRITE TOOLS".
C. By configuring allowed-tools: Read, Grep, Glob in the skill's YAML frontmatter.
D. By appending a - -read -only flag when invoking the skill via the terminal.

Answer: C

Explanation:
To strictly restrict which tools Claude can use when a skill is active, you must configure the 'allowed-tools' property in the SKILL.md YAML frontmatter. Relying on prompt-based instructions in the markdown text is probabilistic and unsafe for security guarantees.

NEW QUESTION # 34
Why is it considered an architectural anti-pattern to configure the exact same Claude session to review its newly generated code?

A. The reviewer retains the reasoning context and assumptions from the generation phase, creating confirmation bias.
B. Tools invoked during the first pass are permanently locked and cannot be reused in the review pass.
C. The Message Batches API does not support synchronous self-review workflows.
D. It exceeds the maximum token limit of the context window during the generation phase.

Answer: A

Explanation:
Same-session self-review is an anti-pattern because the model retains the context and reasoning from the generation phase, leading to a blind spot or confirmation bias. Independent review instances with fresh contexts are much more effective at objectively evaluating code.

NEW QUESTION # 35
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.
A critical bug is affecting production users. Error logs show exceptions in the OrderProcessing module with a clear stack trace pointing to a specific function. You haven't worked with this module before. What's the most effective approach?

A. Enter plan mode to explore the module's architecture and dependencies before attempting any fixes.
B. Start with direct execution to gather initial information, then switch to plan mode to design a comprehensive solution before implementing any changes.
C. Use plan mode to analyze the error in context of the module's design, enumerate potential root causes, and prioritize fixes systematically.
D. Use direct execution to examine the stack trace, read the relevant code, and implement a fix once you identify the root cause.

Answer: A

Explanation:
Because the module is unfamiliar, plan mode allows safe, read-only investigation of the stack trace, relevant code, and dependencies before changing production code. Anthropic recommends planning when working with unfamiliar code.

NEW QUESTION # 36
To ensure that a model consistently classifies the severity of identified code issues, what is the best prompt engineering technique?

A. Instruct the model to self-report a confidence score from 1-10 for each finding.
B. Lower the max_tokens limit so the model focuses only on critical bugs.
C. Allow the model to dynamically generate severity labels based on context.
D. Define explicit severity criteria with concrete code examples for each severity level.

Answer: D

Explanation:
Providing explicit severity criteria paired with concrete code examples for each level bounds the model's behavior, leading to consistent severity classification and preventing subjective miscategorization.

NEW QUESTION # 37
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