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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prompt Engineering & Structured Output | 20% | - Prompt design strategies - Structured output generation and validation - Improving Claude response quality and consistency |
| Topic 2: Context Management & Reliability | 15% | - Managing context windows and information flow - Production deployment considerations - Evaluation and reliability strategies |
| Topic 3: Tool Design & MCP Integration | 18% | - Tool safety, reliability, and usability - Designing effective tools for Claude applications - Model Context Protocol (MCP) concepts and integration |
| Topic 4: Agentic Architecture & Orchestration | 27% | - Designing agentic systems and workflows - Agent coordination and orchestration patterns - Selecting appropriate Claude architectures |
| Topic 5: Claude Code Configuration & Workflows | 20% | - Claude Code usage and configuration - Developer productivity workflows - Integrating Claude Code into development processes |
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NEW QUESTION # 56
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?
Answer: C
Explanation:
Keeping only the return-relevant fields preserves the information needed for the current task while reducing unnecessary context load. This improves reliability and efficiency before adding more order lookups, because the agent retains structured, task-specific details without carrying verbose tool outputs that are no longer useful.
NEW QUESTION # 57
A customer sends: "This is frustrating. I've explained my issue twice and nothing is being resolved. I want to talk to a real person NOW." The agent has not yet called any tools to investigate the customer's account.
What should the agent do?
Answer: A
Explanation:
Option C respects the customer's explicit request for human assistance. The agent should not attempt to retain the interaction, gather additional account information, or require the customer to repeat the request. Because the escalation decision has already been made by the customer, further autonomous investigation would create unnecessary delay and disregard clear human direction.
Anthropic's trustworthy-agent framework emphasizes maintaining meaningful human control over agent autonomy. Anthropic's customer-support implementation guidance also recommends defining interaction branches and measuring escalation efficiency as part of the system's success criteria.
Option A deliberately delays escalation despite an unambiguous request. Option B performs unnecessary tool calls and may expose or retrieve account information that is not required before transferring the conversation.
Option D similarly introduces another conversational barrier. Since the current exchange is short and contains no tool-generated evidence, passing the available conversation history gives the human agent the immediate context-the customer's frustration, repeated unsuccessful attempts, and explicit transfer request-without pretending that account investigation has occurred.
NEW QUESTION # 58
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.
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 the pre-specified searches fail, (2) research quality drops for emerging topics that do not match expected patterns, and (3) the subagent rarely surfaces valuable tangential sources.
What is the most effective way to improve subagent adaptability?
Answer: C
Explanation:
Option A defines what successful research must achieve without hard-coding a brittle search procedure. The subagent receives measurable objectives-breadth, diversity, recency, and relevance-but retains authority to reformulate queries, follow promising leads, and adjust source selection when the topic does not match familiar patterns. Anthropic's account of its multi-agent research system states that subagents need an objective, expected output format, guidance about tools and sources, and clear task boundaries. This is more informative than option B's vague instruction, yet more adaptive than prescribing every query. Option C improves only one known failure path and still constrains the agent to a predefined procedure that may be unsuitable for emerging subjects. Option D adds orchestration complexity and a potentially incorrect classification step without solving over-prescription within either category. The coordinator should describe mandatory constraints separately from strategic guidance: authoritative-source requirements and time boundaries can remain fixed, while query formulation and exploration paths remain agent-controlled.
Evaluation should then measure source coverage, evidence quality, duplication, and discovery of relevant secondary leads rather than whether the subagent followed a particular series of searches.
NEW QUESTION # 59
A prompt asks Claude to produce Markdown tables. Which addition MOST increases consistency?
Answer: D
Explanation:
Explicit structural requirements reduce ambiguity. Providing exact column names, ordering, and formatting expectations helps Claude consistently generate Markdown tables that downstream users or systems can reliably consume.
NEW QUESTION # 60
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.
You've configured your Claude agent with three MCP servers: one for git operations, one for Jira ticket management, and one for documentation search.
When a user asks the agent to "create a branch for JIRA-123 and add documentation links to the ticket," how does the agent access tools across these servers?
Answer: A
Explanation:
MCP allows a Claude application to connect to multiple servers and expose their enabled tools within the same agentic interaction. Anthropic's MCP connector documentation explicitly supports connecting to multiple MCP servers in one request. Once connected, Claude can invoke a server's tool when the user's request corresponds to the capability described by that tool. ( https://docs.anthropic.com/en/docs/agents-and- tools/mcp-connector ) In this scenario, the git server can provide the branch-creation operation, the documentation server can locate the relevant links, and the Jira server can update ticket JIRA-123. The agent can coordinate these capabilities without requiring a separate conversational turn that restricts it to only one server. Tool descriptions and schemas tell Claude what each operation does and what inputs it requires.
Option B incorrectly describes sequential capability discovery. Server identity and tool definitions are established through the MCP configuration rather than discovered by querying every server for each operation. Option C is incorrect because connecting several servers does not inherently restrict the agent to a single selected server. Option D imposes a one-server-per-turn limitation that MCP does not require.
Access can still be controlled through allowlists, denylists, permissions, and per-tool configuration. Those controls restrict which tools are enabled; they do not change the fundamental ability to make tools from multiple configured servers available together.
Official references/topics: MCP Server Configuration, Multi-Server Tool Access, Tool Discovery, MCP Tool Permissions.
NEW QUESTION # 61
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