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| Section | Weight | Objectives |
|---|---|---|
| Tool Design & MCP Integration | 18% | - Tool schema design and interface boundaries - Model Context Protocol (MCP) architecture and JSON-RPC 2.0 - MCP tool, resource and prompt implementation - Error handling and tool response formatting - Tool distribution and permission controls |
| Claude Code Configuration & Workflows | 20% | - Hooks vs advisory instructions - Custom slash commands and plan mode vs direct execution - CI/CD integration and non-interactive mode parameters - CLAUDE.md hierarchy, precedence and @import rules - Path-specific rules and .claude/rules/ configuration |
| Agentic Architecture & Orchestration | 27% | - Task decomposition and dynamic subagent selection - Session state management and workflow enforcement - Multi-agent patterns: coordinator-subagent and hub-and-spoke - Error recovery, guardrails and safety patterns - Agentic loop design and stop_reason handling |
| Context Management & Reliability | 15% | - Context window optimization and prioritization - Token budget management and cost control - Context pruning and summarization strategies - Idempotency, consistency and failure resilience |
| Prompt Engineering & Structured Output | 20% | - JSON schema design and structured output enforcement - Explicit criteria definition and few-shot prompting - System prompt design and persona alignment - Validation, parsing and retry loop strategies |
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NEW QUESTION # 114
The synthesis agent receives summarized findings from the web-search and document-analysis agents, then passes a consolidated summary to the report generator. During testing, you discover that the generated reports make factual claims without proper citations-the report generator cannot attribute statements to their original sources because that metadata was lost during the summarization steps. What is the most effective approach to ensure proper source attribution in the final reports?
Answer: A
Explanation:
Option B preserves provenance as structured data throughout every handoff. Each finding should include the summarized claim and an associated source record containing its URL or document identifier, page or section location, relevant excerpt, and possibly retrieval date and confidence. The synthesis agent can combine claims without destroying this relationship, and the report generator can produce citations deterministically.
Anthropic's multi-agent research system retains findings until a dedicated citation stage identifies the precise source locations supporting report claims. This demonstrates that citation provenance must remain available beyond initial retrieval and summarization.
Option A attempts to reconstruct provenance after it has been discarded, which is expensive and may associate a claim with a different or weaker source. Option C preserves evidence but wastes context by transferring approximately all raw search and document content. Option D is better than losing references entirely, but embedding citations only in prose makes programmatic validation, deduplication, and claim-to- source mapping less reliable. Structured content and source fields maintain both context efficiency and auditable attribution while allowing different agents to transform the narrative safely.
NEW QUESTION # 115
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.
You're implementing a caching layer for API responses to speed up the /products endpoint. You have a rough idea-Redis with a 5-minute TTL-but you're new to production caching and aren't sure what other considerations a robust implementation requires. What's the most effective way to start your iterative workflow?
Answer: C
Explanation:
Because the requirements are incomplete and production caching involves hidden design choices, an interview helps surface invalidation, consistency, failure handling, and other trade-offs before implementation. Anthropic recommends this approach for larger features when important requirements may not yet be identified.
NEW QUESTION # 116
The synthesis agent completes its initial pass but flags that three key research questions remain unanswered because the web search and document analysis agents didn't find relevant information on those specific subtopics. The coordinator currently proceeds directly to report generation, producing reports with incomplete coverage. What change would most effectively improve research completeness?
Answer: C
Explanation:
The coordinator should treat unanswered research questions as gaps in the workflow and route them back to the appropriate specialist agents with targeted follow-up tasks. This creates an iterative research loop that improves completeness before the final report is generated.
NEW QUESTION # 117
After investigating a billing dispute over 25+ turns, you've identified that duplicate charges occurred due to a payment gateway timeout triggering retry logic. The required refund ($847) exceeds your $500 authorization limit You need to call escalate_to_human, and the human agent won't have access to your conversation transcript. What context should you pass to enable effective resolution?
Answer: A
Explanation:
The human agent needs concise, complete handoff context because they cannot see the prior conversation. A structured summary with the customer ID, root cause, refund amount, and recommended action preserves the essential diagnostic and resolution details without overwhelming them with unnecessary transcript history.
NEW QUESTION # 118
The coordinator agent has AgentDefinition objects configured for all four specialized subagents, each with appropriate descriptions, prompts, and tool restrictions. During testing, you notice that the coordinator correctly reasons about when to delegate--it generates messages such as, "I'll ask the web-search agent to find sources on this topic"--but no subagent execution occurs. The coordinator then proceeds as if the delegation happened and continues with incomplete information. Logs show no errors. What is the most likely cause?
Answer: D
Explanation:
Option B identifies the missing executable capability. Defining specialized agents makes their configurations available, but the coordinator must still be permitted to call the tool that invokes them. Without that tool, Claude can describe an intended delegation in ordinary text but cannot create a subagent execution.
The current Claude Agent SDK documentation requires "Agent" in allowedTools to auto-approve subagent invocations. The tool was renamed from "Task" to "Agent" in Claude Code 2.1.63, so the terminology in the original candidate question required correction. Older integrations may still expose "Task" in initialization or permission records.
NEW QUESTION # 119
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