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| Section | Weight | Objectives |
|---|---|---|
| Agentic Architecture & Orchestration | 27% | - Agentic architecture patterns
|
| Context Management & Reliability | 15% | - Context handling
|
| Prompt Engineering & Structured Output | 20% | - Prompt design
|
| Claude Code Configuration & Workflows | 20% | - Claude Code
|
| Tool Design & MCP Integration | 18% | - Tool integration
|
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NEW QUESTION # 113
You are building a customer support resolution agent using the Claude Agent SDK. The agent handles high- ambiguity requests like returns, billing disputes, and account issues. It has access to your backend systems through custom Model Context Protocol (MCP) tools ( get_customer , lookup_order , process_refund , escalate_to_human ). Your target is 80%+ first-contact resolution while knowing when to escalate.
Anthropic's tool use documentation states: "Write instructive error messages. Instead of generic errors like
'failed', include what went wrong and what Claude should try next." A billing dispute agent uses lookup_order , which catches all exceptions and returns a tool_result with is_error: true and the message
"Tool execution failed". Monitoring shows two failure modes: the agent retries the identical call until hitting the turn limit, or it immediately calls escalate_to_human without trying alternative tools.
Which change follows the documented recommendation and gives Claude the information it needs to select the correct recovery action for each error type?
Answer: B
Explanation:
Option B preserves the formal failure indicator while making the returned content operationally useful.
Anthropic's tool-use guidance states that when a tool fails, the application should return the error through tool_result content and mark it with is_error: true . Claude can then use that information to retry with corrected input, seek clarification, or explain the limitation. ( https://docs.anthropic.com/en/docs/agents-and- tools/tool-use/bash-tool ) The two example messages identify both the cause and the appropriate recovery path. "Order not found" indicates that repeating the same identifier will not help and proposes an alternative lookup method.
"Database timeout" identifies a transient infrastructure condition for which a retry is reasonable. This eliminates blind repetition without removing Claude's ability to adapt.
Option A can be useful for tightly bounded low-level retries, but it does not solve permanent errors or tell the agent what happened after retries fail. Option C incorrectly disguises a failed operation as successful tool content. Option D moves semantic knowledge into hardcoded orchestration logic, making the system more rigid and duplicating information already known by the tool.
The most reliable tool interface combines the error flag, a stable error type, a retryability indicator, a concise causal explanation, and a recommended recovery action.
Official references/topics: is_error handling, instructive tool results, recovery guidance, resilient MCP tool design.
NEW QUESTION # 114
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.
An engineer asks the agent to understand how the caching layer works before adding a new cache-invalidation trigger. Initial Grep searches show that caching logic spans 15 files containing decorators, middleware, and service classes-approximately 8,000 lines in total.
What is the most effective next step for building understanding while managing context constraints?
Answer: D
Explanation:
Option A establishes the caching architecture before consuming thousands of implementation lines. The base class or protocol reveals the supported operations, lifecycle, cache-key rules, and invalidation contract.
Imports, subclasses, registrations, and call sites can then direct the agent toward only those concrete implementations relevant to the proposed trigger. Anthropic's effective context-engineering guidance explains that context is finite and that recall degrades as irrelevant tokens accumulate. It identifies Glob and Grep as mechanisms for retrieving code just in time rather than loading an entire repository upfront. Option B assumes file size or naming determines architectural importance; a small interface may define the system while a large service file contains incidental caching calls. Option C loads approximately 8,000 lines before establishing which portions matter. Option D is overly lexical and can miss invalidation implemented through event publication, key-version changes, inherited methods, or generically named hooks. Dependency-guided exploration provides a compact conceptual model first and expands the investigation only when concrete relationships show that additional files are relevant.
NEW QUESTION # 115
After the web search agent and document analysis agent complete their tasks, the coordinator invokes the synthesis agent. However, the synthesis agent responds that it cannot complete the task because no research findings were provided. What is the most likely cause of this issue?
Answer: A
Explanation:
The synthesis agent relies on the coordinator to provide relevant findings from prior subagents. If the coordinator fails to include these outputs in the synthesis prompt, the agent receives no actionable context and cannot produce a meaningful summary or analysis.
NEW QUESTION # 116
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.
An engineer who recently joined the team asks the agent to explain the authentication and authorization architecture before making security improvements. The codebase contains more than 800 files across multiple services.
What exploration strategy will most effectively build understanding while respecting context limits?
Answer: C
Explanation:
Option D builds an evidence-based architectural map without indiscriminately loading hundreds of files.
Authentication entry points may include route handlers, middleware registration, token-validation functions, session constructors, or identity-provider callbacks. After Grep identifies those anchors, targeted Read operations can establish their responsibilities, while imports, call sites, and configuration references reveal the downstream authorization flow. Anthropic's large-codebase guidance recommends scoping Claude to the portion of a repository touched by the task because unrelated instructions and file reads consume tokens and degrade performance. Its common workflows guidance similarly recommends beginning broadly and narrowing into specific components. Option A launches agents before the relevant service boundaries are known and may produce overlapping, inconsistent investigations. Option B is an uncontrolled lexical sweep that will include tests, documentation, unrelated tokens, and incidental terminology. Option C appropriately checks project guidance but incorrectly delegates technical file selection to a new engineer who may not know the architecture. Incremental dependency tracing maintains context efficiency while producing a verifiable end-to-end map grounded in actual code paths.
NEW QUESTION # 117
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.
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:
Option A describes the principal reason an independent review context is valuable. The implementing session contains the assumptions, interpretations, and reasoning that produced the refactor. When asked to review its own work, Claude may continue operating within those same assumptions and therefore overlook defects caused by them. A fresh reviewer evaluates the resulting diff and stated requirements independently, without inheriting the implementation narrative.
Anthropic's Claude Code best-practices guidance explicitly recommends an adversarial review step using a fresh subagent or separate context. It explains that the reviewer should see the diff and review criteria rather than the reasoning that produced the change.
NEW QUESTION # 118
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