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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Context Management & Reliability	15%	- Context window optimization 1. "Lost in the middle" mitigation strategies 2. Managing long conversation degradation - System reliability 1. Error propagation handling 2. Escalation strategies (fail vs retry vs human)
Topic 2: 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
Topic 3: Tool Design & MCP Integration	18%	- Model Context Protocol (MCP) 1. MCP server integration patterns 2. Tool selection and routing strategies - Tool interface design 1. Clear tool descriptions and boundaries 2. Structured tool input/output schemas
Topic 4: Agentic Architecture & Orchestration	27%	- Multi-agent orchestration 1. Parallel task decomposition 2. Coordinator / sub-agent patterns - Agentic loops & lifecycle design 1. Tool use loop execution (request → tool_use → result → next step) 2. Stop reason handling and control flow
Topic 5: Prompt Engineering & Structured Output	20%	- Tool-augmented prompting 1. Tool-use driven reasoning patterns 2. Validation and retry loops - Instruction design 1. Few-shot prompting strategies 2. Deterministic output formatting (e.g., JSON)

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

NEW QUESTION # 78
The coordinator provides detailed step-by-step instructions to the web search subagent, specifying exact search queries, source priorities, and date filters. Production monitoring reveals three issues: (1) the subagent reports "insufficient results" rather than trying alternative approaches when pre-specified searches fail, (2) research quality drops for emerging topics that don't match expected patterns, and (3) the subagent rarely surfaces valuable tangential sources.
What's the most effective way to improve subagent adaptability?

A. Implement a topic classification step where the coordinator categorizes requests as "well-defined" or "exploratory" and uses different instruction styles for each category.
B. Remove procedural details entirely, delegating with simple goals like "research X thoroughly" and relying on the subagent's general capabilities.
C. Add explicit fallback directives to the detailed instructions: "If specified searches yield fewer than N results, attempt alternative query formulations before reporting failure."
D. Specify research goals and quality criteria (coverage breadth, source diversity, recency) rather than procedural steps, letting the subagent determine its search strategy.

Answer: D

Explanation:
Delegating goals and quality criteria gives the subagent room to adapt its strategy while still defining what good research looks like. This improves handling of failed searches, emerging topics, and useful tangential sources because the subagent can vary queries, sources, and filters to satisfy the research objective rather than rigidly following preset steps.

NEW QUESTION # 79
When the coordinator agent delegates a subtask to a specialized document analysis subagent, what is the best practice for passing context to ensure optimal performance?

A. Grant the subagent access to the coordinator's scratchpad file using a Read tool.
B. Use the /compact command to summarize the coordinator's history before injecting it into the subagent's context.
C. Pass ONLY the explicit context and findings relevant to that specific subagent's assigned task.
D. Share the full coordinator conversation history with the subagent so it has the maximum possible context.

Answer: C

Explanation:
Subagents do not automatically inherit parent context and should not receive the full conversation history, as this causes context pollution. The correct approach is to explicitly pass only the specific, relevant context and parameters needed for the subagent's assigned task.

NEW QUESTION # 80
When implementing multi-turn conversations with tool usage in the Claude API, how must the application handle the follow-up request after executing a tool?

A. Send only the new tool result to save token context space in the context window.
B. Use the /compact command to summarize the tool output before returning it.
C. Pass the tool result inside an assistant message with an is_error flag.
D. Append a user message containing a tool_result block with the matching tool_use_id, and include the full prior conversation history.

Answer: D

Explanation:
Because Claude is stateless and does not remember past turns, you must provide the entire conversation history. When returning a tool result, it must be appended as a user message containing a tool_result block that includes the specific tool_use_id matching the request.

NEW QUESTION # 81
Your track_shipment(tracking_id) tool queries an external logistics API that sometimes fails - the API may be temporarily unavailable, the tracking ID may be malformed, or the shipment may not exist. Currently, your tool raises a Python exception when errors occur. Users report the agent gives unhelpful responses like "I'm having trouble with that request" instead of suggesting alternatives such as verifying the tracking number format or checking by order number. How should you handle errors in tool results?

A. Create dedicated error-recovery tools (retry_tracking_lookup, search_by_order_number) that the model can invoke after the primary tracking tool returns a failure indicator.
B. Return structured error information as normal tool output including error type, recoverability status, and actionable context for the user.
C. Return a generic error response (e.g., {"success": false, "error": "lookup_failed"}) for all failure cases to maintain a consistent schema and avoid exposing internal error details.
D. Implement retry logic with exponential backoff inside the tool implementation so transient errors are automatically handled and only return a result after all retry attempts are exhausted.

Answer: C

Explanation:
Structured error output gives the agent enough information to respond usefully. Including the error type, whether the issue is recoverable, and actionable guidance allows the agent to distinguish malformed tracking IDs, missing shipments, and temporary API failures, then suggest the correct next step to the user.

NEW QUESTION # 82
Your expense reimbursement agent processes employee requests using a
process_reimbursement tool. Company policy requires that reimbursements above $500 must be approved by a manager before funds are disbursed. The agent handles hundreds of requests daily, and you need the threshold enforcement to be tamper-proof regardless of how the agent is prompted. Which design ensures the $500 approval threshold cannot be bypassed?

A. Provide two tools: auto_reimburse (hard-coded limit of $500) and request_manager_approval.
Include detailed system prompt instructions telling the agent to check the amount and call the appropriate tool. Add a PostToolUse hook that logs which tool was called for auditing.
B. The process_reimbursement tool accepts amount and details, and internally enforces the threshold: amounts <$500 are auto-disbursed and the tool returns a success confirmation; amounts >$500 cause the tool to create a pending approval request and return a status indicating manager review is pending.
C. The process_reimbursement tool accepts an approved_by_manager: boolean parameter. The system prompt instructs the agent to only set this to true after confirming that a manager has approved the request. A nightly audit script reviews all reimbursements where approved_by_manager was set to true.
D. Implement the threshold check in a PreToolUse hook that inspects the amount parameter before process_reimbursement executes. If the amount exceeds $500, the hook modifies the tool call to add a requires_approval: true flag, which the tool checks before disbursing.

Answer: B

Explanation:
Enforcing the approval threshold within the tool itself makes it tamper-proof and independent of agent behavior or prompts. The tool controls disbursement and ensures manager approval is required for amounts over $500, preventing accidental or intentional bypass.

NEW QUESTION # 83
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