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| Section | Weight | Objectives |
|---|---|---|
| Context Management & Reliability | 15% | - Context handling
|
| Tool Design & MCP Integration | 18% | - Tool integration
|
| Claude Code Configuration & Workflows | 20% | - Claude Code
|
| Prompt Engineering & Structured Output | 20% | - Prompt design
|
| Agentic Architecture & Orchestration | 27% | - Agentic architecture patterns
|
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NEW QUESTION # 150
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.
Your team is configuring MCP servers in Claude Code. You want to add a shared venue lookup server that all team members should have access to, and you personally want to add an experimental music playlist server that only you are testing. Which configuration approach correctly applies MCP server scopes?
Answer: B
Explanation:
Project-scoped MCP servers are stored in .mcp.json and can be shared through version control with the whole team. Personal local or user-scoped servers are stored in ~/.claude.json and remain private to the individual user.
NEW QUESTION # 151
After investigating a billing dispute for more than 25 turns, you determine that duplicate charges resulted from a payment-gateway timeout triggering retry logic. The required refund of $847 exceeds your $500 authorization limit, so you must invoke escalate_to_human. The human agent will not have access to the conversation transcript. What context should you pass to enable effective resolution?
Answer: C
Explanation:
Option C gives the human agent the operational state required to continue without replaying a long conversation. The handoff should include verified identifiers, the duplicate transaction evidence, the diagnosed timeout-and-retry mechanism, the $847 refund requirement, the agent's $500 authorization constraint, completed verification steps, prior actions, and the recommended resolution. Any unresolved uncertainty should be labeled explicitly.
Anthropic's effective context-engineering guidance recommends preserving high-value state in structured notes while removing redundant conversational and tool-call history. Its long-running-agent guidance likewise describes structured handoffs as the mechanism for maintaining continuity across context resets or agent boundaries.
Option A maximizes raw information but forces the human to locate the relevant facts among more than 25 turns, increasing delay and error risk. Option B preserves evidence but omits the authorization constraint, completed verification, and explicit recommended action. Option D is too sparse to support validation or execution. A structured handoff balances fidelity and efficiency: it contains everything needed for the next actor to make the refund decision while excluding greetings, repeated explanations, and irrelevant intermediate tool output.
NEW QUESTION # 152
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.
An engineer asks your agent to identify untested code paths in a legacy payment processing module spanning 45 files. After reading the first 8 source files, the agent's responses are becoming noticeably less accurate - it's forgetting previously discussed code patterns and hasn't yet located all test files or traced critical payment flows. What's the most effective approach to complete this investigation?
Answer: C
Explanation:
Subagents isolate detailed exploration in separate context windows and return concise findings to the main agent. This prevents further context degradation while preserving high-level coordination across test discovery and payment-flow tracing.
NEW QUESTION # 153
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, and Glob-and integrates with Model Context Protocol (MCP) servers.
Your productivity agent connects to three MCP servers: an issue tracker with search_issues , get_issue , and create_comment ; a documentation wiki with search_docs , get_page , and list_spaces ; and a database explorer with run_query , get_schema , and list_databases . For cross-system questions such as, "Which database tables are affected by the authentication refactor in PROJ-1234?", the agent makes eight to ten sequential exploratory calls, lacks visibility into each server's available content, and exhausts context before completing complex investigations.
What architectural change best leverages MCP capabilities to address these problems?
Answer: D
Explanation:
Option C uses MCP resources for their intended purpose: exposing contextual data that applications and agents can discover and read without treating every lookup as an action-oriented tool invocation. Anthropic's Claude Code MCP documentation states that Claude Code automatically provides mechanisms to list and read resources exposed by connected MCP servers. Resources may contain text, JSON, structured data, or other server-provided content. The official MCP server concepts likewise explain that resources expose information from files, APIs, and databases through identifiable, discoverable URIs. Publishing issue summaries, the wiki hierarchy, and database schemas gives the agent an initial map of available evidence. It can identify relevant systems and retrieve only the necessary records before making targeted tool calls. Option A creates another opaque, high-level tool whose output quality depends on each server interpreting the investigation correctly.
Option B produces tight coupling and increases operational complexity. Option D prevents the cross-system investigation required by the question. Resource catalogs improve discoverability, reduce blind exploration, and preserve tools for searches, queries, and mutations that genuinely require execution.
NEW QUESTION # 154
A developer uses Claude Code to refactor a function during a development session. Before committing, the developer asks the same Claude session to review the code for issues. Later, a separate automated CI review catches several bugs that the same-session review missed. What best explains this discrepancy?
Answer: B
Explanation:
The key difference is reviewer independence. In the original session, Claude retains the reasoning, assumptions, implementation decisions, and intermediate conclusions that led to the refactor. That context can anchor the subsequent review toward defending or confirming the chosen approach instead of evaluating the resulting code independently. The separate CI review begins with fresh context and can assess the implementation solely against the code and review criteria.
Anthropic's Claude Code best-practices documentation explicitly states that fresh context improves code review because Claude is not biased toward code it has just written. It recommends a writer/reviewer pattern using separate sessions or a review subagent with an isolated context.
Option B is possible in an uncontrolled comparison, but the scenario's defining distinction is that one review occurs in the implementation session and the other is independent. Option C is false because local Claude Code can read and search the repository when permissions and tools permit it; it is not inherently restricted to the current file. Option D would require evidence of context saturation, such as degraded instruction following or an almost-full context window. No such evidence is supplied. Prior-reasoning bias most directly explains the observed discrepancy.
NEW QUESTION # 155
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