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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Model Selection and Optimization | 16.8% | - Model Capabilities and Trade-offs - Model Selection - Performance Optimization - Cost and Latency Optimization |
| Topic 2: Applications and Integration | 33.1% | - Software Engineering Fundamentals - Streaming, Error Handling and Reliability - Claude API and Client SDKs - API Integration and Application Development - Multimodal and Structured Outputs - Message Batches and Prompt Caching |
| Topic 3: Agents and Workflows | 14.7% | - Agent Architecture - Agent Construction with Claude - Agent Patterns and Frameworks |
| Topic 4: Eval, Testing, and Debugging | 2.6% | - Evaluation, Testing, and Debugging |
| Topic 5: Tools and MCPs | 10.6% | - Tool Use and Tool Schemas - Model Context Protocol - Building Custom Tools and MCP Servers |
| Topic 6: Security and Safety | 8.1% | - Prompt Injection and Untrusted Content - Application Security - Safety and Responsible Development - Secure Tool Use and Guardrails |
| Topic 7: Prompt and Context Engineering | 11% | - Context Engineering - Prompt Engineering - Context Management and Long-Context Techniques |
| Topic 8: Claude Code | 3.1% | - Claude Code Configuration and Extensibility |
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NEW QUESTION # 91
The team is debating whether to integrate with the Claude API directly or through a third-party abstraction layer that supports multiple LLM providers. The team has identified that all current and projected use cases run on Claude, no internal customer has requested LLM portability, and the team's product roadmap does not mention multi-provider support over the next two years. The third-party abstraction would add roughly 15 percent overhead in code complexity and introduce one additional dependency.
Which integration approach would you recommend?
Answer: A
Explanation:
D follows the principle of choosing the simplest architecture that satisfies demonstrated requirements .
The supplied examination item explicitly marks D. In this scenario, portability is neither a present functional requirement nor a foreseeable roadmap requirement. Adding an abstraction therefore creates measurable complexity without delivering an identified product capability.
Anthropic provides official general-purpose SDKs for Claude in multiple languages. These expose the Messages API directly while adding idiomatic interfaces, type safety, streaming support, retries, and error handling. Anthropic separately describes compatibility layers and framework-specific libraries as alternative integration surfaces rather than requirements for ordinary Claude development.
A third-party abstraction becomes rational when there is a genuine requirement for multiple providers, vendor switching, standardized cross-model interfaces, or an existing architectural platform that mandates it. None exists here. Building that flexibility speculatively increases dependencies, debugging surface, version- compatibility work, and the possibility that provider-specific Claude capabilities are hidden behind a lowest- common-denominator API.
A optimizes for hypothetical future requirements. B doubles operational complexity. C creates an even larger maintenance burden.
Relevant Claude Developer topics: Claude App Design, SDK selection, abstraction boundaries, dependency management, YAGNI, integration architecture, and provider portability requirements .
NEW QUESTION # 92
You are extending a Claude agent with a capability that needs to be reusable across multiple teams in the organization, with each team able to invoke and use it independently.
How would you build the capability?
Answer: C
Explanation:
Option C is correct because Skills and MCP are first-class Claude extension mechanisms intended to make capabilities reusable rather than embedding one-off logic inside a single agent. Claude documentation describes Skills as reusable knowledge, instructions, and workflows that can be loaded when relevant. It describes MCP as the standard mechanism for connecting Claude to external services, tools, prompts, and resources. Claude Code plugins can package Skills and MCP servers for distribution across projects and teams.
Option A tightly couples the capability to one team's agent and requires copying code, creating version drift and duplicated maintenance. Option B is technically reusable software, but it leaves every consuming Claude application responsible for its own integration and does not expose the capability through Claude's native extension interfaces. Option D assumes an existing built-in tool is the correct abstraction even though the scenario specifically requires an independently reusable capability.
The precise choice between Skill and MCP depends on what is being reused: use a Skill for reusable instructions/workflows; use MCP when the capability exposes external data or actions. Therefore, C best reflects the Claude Developer extension model. Relevant topics: Agent Skills, MCP, plugins, tool integration, reuse, and cross-team capability distribution.
NEW QUESTION # 93
You are designing an agent that handles a multi-step research task. You want the agent to break the task into smaller pieces, hand each piece to a focused subagent, and consolidate the results.
The agent pattern you would apply is...
Answer: C
Explanation:
The supplied Claude Developer source explicitly marks A . The scenario contains the defining elements of an orchestrator/subagent architecture : decomposition of a larger objective, delegation of independent subtasks to specialized workers, and aggregation of their outputs by a coordinating agent.
This architecture is appropriate when subtasks can be performed with focused context or specialized tools.
Instead of forcing one agent to carry every intermediate detail, the orchestrator can formulate assignments, launch suitable subagents, receive condensed results, identify missing information, and synthesize the final research product. This also enables context isolation and potentially parallel execution.
Anthropic's published multi-agent architecture uses this orchestrator-worker approach for research workloads:
a lead agent decomposes a query, delegates work to specialized subagents, and then integrates their findings.
This is particularly useful where exploration is broad and individual subtasks benefit from independent context windows. The broader model-selection guidance also identifies orchestrator strategies as useful where work can be partitioned among worker models.
B describes storage rather than delegation. C is a context-management technique, not a decomposition pattern.
D centralizes all responsibilities in a single loop.
Relevant Claude Developer topics: Agent Patterns, orchestration, subagents, task decomposition, specialization, delegation, context isolation, and result consolidation .
NEW QUESTION # 94
You are building an agent that needs to call several internal APIs and a database in a structured, repeatable way. Your team has decided to use the Claude Agent SDK rather than build a custom loop. You are setting up the agent's tool definitions and execution loop.
How would you set up the tools and execution loop?
Answer: D
Explanation:
The supplied Claude Developer examination source selects A . The purpose of choosing an agent SDK rather than implementing a custom Messages API loop is to consume the SDK's higher-level abstractions. Re- implementing dispatch, iteration, and state handling would discard much of the value provided by the SDK.
Anthropic's current documentation distinguishes low-level tool-use loops from higher-level SDK-managed abstractions. With a manually implemented Messages API workflow, application code must inspect stop_reason, execute requested client tools, append tool_result blocks, preserve conversation history, and repeat until Claude completes the turn. Anthropic's higher-level tooling can instead encapsulate this repetitive control flow. Current migration guidance also confirms that Agent SDK @tool functions are automatically dispatched by the SDK and that agents, tools, and sessions are first-class SDK concepts.
B is incorrect because structured tool use should not be replaced with informal plain-text calls. C introduces an unnecessary custom state dependency when no external persistence requirement exists. D duplicates control-loop functionality despite the explicit decision to use the SDK.
Relevant Claude Developer topics: Agent SDK, tool definitions, dispatch, agentic loops, conversation state, tool execution, and abstraction selection .
NEW QUESTION # 95
Your team is debating how to manage the prompts used in your Claude application. Some prompts are checked into the code repository, some live in a separate configuration file, and some are constructed inline at runtime. The result is inconsistent, and a recent prompt change went out without code review.
What steps would you take?
Answer: B
Explanation:
Option D treats prompts as production configuration and executable application behavior rather than informal text. A prompt modification can change output format, tool-selection behavior, policy enforcement, downstream compatibility, token usage, or model quality just as materially as an ordinary source-code change. Consequently, prompt changes need traceability, review, testing, and rollback.
A single source of truth prevents different application paths from silently using inconsistent prompt versions.
Version control provides an immutable history showing who changed the prompt, what changed, and which application release used it. Pull-request review enables peer assessment and automated evaluation before deployment. The same configuration-as-code principle appears throughout Claude Code's project configuration model, where shared project configuration is designed to live with version-controlled project artifacts.
A removes governance and creates an uncontrolled external state. B increases hidden runtime behavior and bypasses normal review. C solves fragmentation but leaves the exact governance failure described in the scenario-the ability to ship prompt changes without review.
Therefore, D provides reproducibility and controlled change management. Relevant Study Guide topics:
prompt versioning, configuration management, source control, change review, reproducibility, regression testing, and rollback.
NEW QUESTION # 96
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