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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 - Error handling and tool response formatting - MCP tool, resource and prompt implementation - Tool distribution and permission controls |
| Claude Code Configuration & Workflows | 20% | - CLAUDE.md hierarchy, precedence and @import rules - Path-specific rules and .claude/rules/ configuration - Hooks vs advisory instructions - Custom slash commands and plan mode vs direct execution - CI/CD integration and non-interactive mode parameters |
| Prompt Engineering & Structured Output | 20% | - Explicit criteria definition and few-shot prompting - System prompt design and persona alignment - Validation, parsing and retry loop strategies - JSON schema design and structured output enforcement |
| Context Management & Reliability | 15% | - Idempotency, consistency and failure resilience - Token budget management and cost control - Context window optimization and prioritization - Context pruning and summarization strategies |
| Agentic Architecture & Orchestration | 27% | - Session state management and workflow enforcement - Error recovery, guardrails and safety patterns - Multi-agent patterns: coordinator-subagent and hub-and-spoke - Task decomposition and dynamic subagent selection - Agentic loop design and stop_reason handling |
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NEW QUESTION # 88
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.
NEW QUESTION # 89
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: C
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.
NEW QUESTION # 90
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 has three requirements for Claude Code's behavior in your project
1. Claude must never modify files in the db/migrations/ directory
2. Claude should prefer your custom logging module over console.log
3. All TypeScript files must be auto-formatted with Prettier after
every edit
All three are currently written as instructions in your project's CLAUDE.md. During a complex refactoring session, a developer discovers that Claude edited a migration file, violating requirement #1. How should you restructure these requirements across Claude Code's configuration mechanisms?
Answer: D
Explanation:
Hard restrictions belong in permission controls, coding preferences belong in CLAUDE.md, and deterministic formatting belongs in an automated hook. Instructions alone cannot reliably prevent prohibited file edits.
NEW QUESTION # 91
You've configured the system so that all four subagents have access to the complete set of
18 tools. During testing, agents frequently call tools outside their specialization - the synthesis agent attempts web searches, and the report generator tries to analyze documents. What is the primary cause of this poor tool selection behavior?
Answer: C
Explanation:
Providing all agents with access to a large set of tools increases the cognitive load for tool selection. When the number of options grows beyond a manageable threshold, agents are more likely to misuse tools outside their specialization, reducing efficiency and accuracy.
NEW QUESTION # 92
After the web-search and document-analysis subagents complete their tasks, the coordinator needs to spawn the synthesis subagent to synthesize the findings. What is the correct approach for providing the synthesis subagent with the information it needs?
Answer: C
Explanation:
Option B follows the Claude Agent SDK's default context-isolation model. A newly spawned subagent receives a fresh context window and does not automatically inherit the parent's conversation history or previous tool results. The coordinator must therefore include the information required for synthesis directly in the spawning prompt, preferably using clearly separated structured sections for web findings, document findings, source metadata, conflicts, and unresolved questions.
Anthropic's official SDK subagent documentation states that the Agent tool's prompt string is the content passed from the parent to the new subagent. It specifically advises including required file paths, errors, and decisions in that prompt because parent context is not inherited.
Option A could work only if the application had deliberately implemented and authorized such a shared- memory architecture. The question establishes no such mechanism, and reference identifiers alone provide no evidence to the subagent. Option C introduces a callback protocol that is unnecessary for a normal handoff.
Option D is incorrect because subagent isolation expressly prevents automatic inheritance. "Complete findings" means the complete evidence needed for synthesis, not every intermediate search trace or irrelevant tool result.
NEW QUESTION # 93
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