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| Section | Weight | Objectives |
|---|---|---|
| Claude Code Configuration & Workflows | 20% | - Developer productivity workflows - Integrating Claude Code into development processes - Claude Code usage and configuration |
| Context Management & Reliability | 15% | - Managing context windows and information flow - Production deployment considerations - Evaluation and reliability strategies |
| Agentic Architecture & Orchestration | 27% | - Selecting appropriate Claude architectures - Designing agentic systems and workflows - Agent coordination and orchestration patterns |
| Prompt Engineering & Structured Output | 20% | - Improving Claude response quality and consistency - Prompt design strategies - Structured output generation and validation |
| Tool Design & MCP Integration | 18% | - Tool safety, reliability, and usability - Model Context Protocol (MCP) concepts and integration - Designing effective tools for Claude applications |
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NEW QUESTION # 73
You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JavaScript Object Notation (JSON) schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.
Your system extracts event metadata (date, location, organizer, attendee_count) from news articles using a JSON schema with all nullable fields. During evaluation, you observe the model frequently generates plausible but incorrect values for fields not mentioned in the article--for example, outputting "500" for attendee_count when the source contains no attendance information.
What's the most effective way to reduce these false extractions?
Answer: A
Explanation:
The schema already supports the correct representation of missing evidence: null. The remaining defect is behavioral. Claude must be explicitly instructed that absence of information is a valid outcome and that values may be populated only when directly supported by the supplied article.
Anthropic's hallucination-reduction guidance recommends explicitly permitting Claude to express uncertainty, grounding outputs in the source, and retracting claims that lack supporting evidence.
It also recommends restricting the model to the provided documents rather than allowing unsupported external knowledge. Option C translates those controls directly into the extraction contract: when no source evidence exists, the model returns null.
NEW QUESTION # 74
You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline.
The system runs automated code reviews, generates test cases, and provides feedback on pull requests. You need to design prompts that provide actionable feedback and minimize false positives.
Your test generation produces unit tests for new code, but reviews show that 55% are low-value: trivial assertions that only verify functions do not throw exceptions, tests duplicating existing coverage, or tests ignoring your team's fixture conventions.
How do you reduce the rate of low-value tests being generated in the first place?
Answer: A
Explanation:
Option D improves the generation conditions instead of filtering defective output afterward. Anthropic recommends using CLAUDE.md for repository-wide standards and information that Claude should apply in every session. The file can define what constitutes a useful test, require assertions on observable behavior, identify approved fixture factories, prohibit duplication of existing scenarios, and provide contrasting examples of strong and trivial tests. These instructions are available before Claude decides what tests to create.
Option A may remove some weak tests, but it doubles model work and still permits the first stage to generate low-quality material. Option B treats line coverage as a quality measure even though a trivial assertion can execute new lines without validating behavior. Option C abandons difficult areas rather than improving generation. The standards should also direct Claude to inspect nearby tests and fixtures before writing new cases, identify the behavior or regression each test protects, and run the relevant suite afterward. Because CLAUDE.md consumes context in every session, the guidance should remain concise; lengthy testing procedures are better placed in a reusable skill referenced from the project instructions.
NEW QUESTION # 75
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's CLAUDE.md includes a rule: "Use 4-space indentation and always run Prettier formatting." Despite this, code reviews reveal that roughly 30% of files Claude Code generates use inconsistent formatting - sometimes 2-space indentation, sometimes missing trailing commas. Adding emphasis ("IMPORTANT: You MUST use Prettier formatting") reduces violations to about 15%, but doesn't eliminate them. What is the most effective way to ensure all generated code is consistently formatted?
Answer: C
Explanation:
Hooks provide deterministic enforcement. Running Prettier automatically after every file edit or write guarantees consistent formatting, whereas instructions, rules, skills, or prompt-based checks still depend on model compliance.
NEW QUESTION # 76
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.
Production monitoring shows that the research phase takes longer than expected. Analysis reveals that the coordinator invokes the web-search subagent, waits for its response, and then invokes the document-analysis subagent. These tasks are independent; neither requires the other's output.
How should you modify the system to run these subagents concurrently?
Answer: D
Explanation:
Option B expresses both independent delegations in the same orchestration turn, allowing the runtime to execute them concurrently and return their results together. The current Claude Agent SDK calls the subagent-spawning capability the Agent tool; Task is its former name. Anthropic's SDK subagent documentation explicitly identifies parallel analysis as a primary subagent use case. Claude tool responses can also contain multiple tool_use blocks, enabling independent calls to be handled as one parallel group rather than as serial model turns.
NEW QUESTION # 77
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 used Claude Code yesterday to investigate authentication flows in a legacy monolith, building up significant context over a 2-hour session. Today she wants to continue that specific investigation. She's worked on three other codebases since then and knows the session was named "auth-deep-dive".
How should she resume?
Answer: A
Explanation:
Claude Code supports resuming a specific saved session by either its identifier or its assigned name. Because the engineer knows the target session is named auth-deep-dive , the appropriate command is:
claude --resume auth-deep-dive
Anthropic's CLI reference explicitly states that --resume can resume a session by ID or name and gives named-session usage in the same form. Resuming restores the relevant conversation history and accumulated context, including the prior analysis and files discussed during the investigation. ( https://docs.anthropic.com
/en/docs/claude-code/cli-reference )
Option B is incorrect because --continue resumes the most recent session in the current directory. The engineer has conducted three subsequent sessions, so it may open an unrelated investigation. Option A uses a flag that is not the documented Claude Code mechanism for selecting a prior session; --resume itself accepts the session identifier when an ID is used. Option C discards two hours of established context and unnecessarily repeats codebase exploration.
Named sessions are particularly useful when engineers alternate among multiple projects or parallel investigations. Assigning descriptive names allows the correct thread to be retrieved deterministically rather than depending on chronological recency.
Official references/topics: Claude Code Session Persistence, Named Sessions, --resume , --continue .
NEW QUESTION # 78
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