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Anthropic CCA-F Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Context Management & Reliability | 15% | - Long-context optimization
|
| Agentic Architecture & Orchestration | 27% | - Agentic loop design and execution lifecycle
|
| Prompt Engineering & Structured Output | 20% | - Reliable structured generation
|
| Tool Design & MCP Integration | 18% | - Model Context Protocol (MCP)
|
| Claude Code Workflows & Configuration | 20% | - Claude Code operational patterns
|
Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions:
Anthropic's tool use documentation states: "Write instructive error messages. Instead of generic errors like 'failed', include what went wrong and what Claude should try next." A billing dispute agent uses lookup_order, which catches all exceptions and returns a tool_result with is_error:
true and the message "Tool execution failed". Monitoring shows two failure modes: the agent retries the identical call until hitting the turn limit, or it immediately calls escalate_to_human without trying alternative tools. Which change follows the documented recommendation and gives Claude the information it needs to select the correct recovery action for each error type?
- A. Remove is_error: true and return the error details as normal tool content, so Claude reasons about the response as data rather than treating it as a flagged failure condition that biases retry behavior.
- B. Implement retry logic with exponential backoff inside each tool implementation so transient errors are resolved transparently within the tool before any failure result is surfaced to Claude in the agentic loop.
- C. Add an error classification step in the agentic loop that intercepts tool errors before Claude sees them, tags each as "retry," "try_alternative," or "escalate," and appends that recommendation to the tool result.
- D. Return error-type-specific messages with is_error: true, e.g., "Order not found-try get_customer to search by phone" for data errors and "Database timeout (transient)-retry should succeed" for infrastructure errors.
Correct Answer: D 🗳️
Explanation: Only visible for VCE4Plus members. You can sign-up / login (it's free).
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. Remove procedural details entirely, delegating with simple goals like "research X thoroughly" and relying on the subagent's general capabilities.
- B. Add explicit fallback directives to the detailed instructions: "If specified searches yield fewer than N results, attempt alternative query formulations before reporting failure."
- C. Implement a topic classification step where the coordinator categorizes requests as "well-defined" or "exploratory" and uses different instruction styles for each category.
- D. Specify research goals and quality criteria (coverage breadth, source diversity, recency) rather than procedural steps, letting the subagent determine its search strategy.
Correct Answer: D 🗳️
Explanation: Only visible for VCE4Plus members. You can sign-up / login (it's free).
Your agent has called lookup_order multiple times while investigating a customer's return requests. Each response includes 40+ fields (items, shipping details, payment info, status history). Tool outputs now represent the majority of the conversation's context. The customer mentions two more orders they want to discuss. What's the most effective approach before making additional lookups?
- A. Extract only the return-relevant fields (items, purchase date, return window, status) from each existing order response, removing verbose details
- B. Have the model generate a natural language summary of each order's key details, replacing structured responses with prose descriptions
- C. Move all tool responses to a vector database with semantic indexing, retrieving relevant portions as the conversation continues
- D. Proceed with additional lookups without modifying the existing tool output context
Correct Answer: A 🗳️
Explanation: Only visible for VCE4Plus members. You can sign-up / login (it's free).
You are building a multi-agent research system using the Claude Agent SDK. A coordinator agent delegates to specialized subagents: one searches the web, one analyzes documents, one synthesizes findings, and one generates reports. The system researches topics and produces comprehensive, cited reports.
When researching "renewable energy adoption," the web search agent returns recent statistics (2024: 35% adoption) while the document analysis agent extracts data from internal reports (2021: 18% adoption). The synthesis agent incorrectly flags these as contradictory sources rather than recognizing the data shows growth over time. What change would best enable the synthesis agent to correctly interpret such temporal differences?
- A. Configure the web search agent to only return results from the past 6 months.
- B. Require subagents to include publication or data collection dates in their structured outputs.
- C. Instruct the synthesis agent to always treat the most recent data as authoritative and place older findings in a separate historical appendix.
- D. Add a conflict resolution agent that automatically discards older data when newer data exists for the same metric.
Correct Answer: B 🗳️
Explanation: Only visible for VCE4Plus members. You can sign-up / login (it's free).
A customer raises three separate issues during one session: a refund inquiry (turns 1-15), a subscription question (turns 16-30), and a payment method update (turns 31-45). At turn 48, the customer asks "What happened with my refund?" The conversation is approaching context limits.
What strategy best maintains the agent's ability to address all issues throughout the session?
- A. Rely on MCP tools to re-fetch relevant information on demand when the customer references earlier issues.
- B. Extract and persist structured issue data (order IDs, amounts, statuses) into a separate context layer.
- C. Implement sliding window context that retains the most recent 30 turns.
- D. Summarize earlier turns into a narrative description, preserving full message history only for the active issue.
Correct Answer: B 🗳️
Explanation: Only visible for VCE4Plus members. You can sign-up / login (it's free).
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