CCDV-F Practice Questions 1 — 50 Questions

Question 1

Refer to the exhibit. A developer provides this tool definition to Claude. If a user asks 'What is the tax on $100?', how will Claude likely behave based on the provided JSON schema?

Accepted Answer

Claude will likely ask the user which state they are in before calling the tool.. The JSON schema defines the contract between the model and the tool. In this exhibit, 'amount' is required, but 'state_code' is not. However, the description implies 'state_code' is necessary for an accurate calculation. Claude will attempt to follow the schema first, but if it identifies that a critical piece of information for the logic is missing, it may ask for clarification.

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Claude will trigger an API error because the state_code is missing from the required list.

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Claude will call the tool with a default state_code of 'CA'.

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Claude will automatically extract the state from the user's IP address.

Question 2

Which field in the tool definition is primarily responsible for helping Claude determine when a specific tool is appropriate to use for a given user query?

Accepted Answer

description. The 'description' field is the primary source of information for Claude's reasoning. It provides the semantic context that the model uses to match user intent to the available functions. A well-written description is crucial for accurate tool selection and helps the model understand the utility and limitations of each tool.

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name

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input_schema

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tool_choice

Question 3

When Claude Code is asked to perform a complex task that might take a long time, how does the agent manage the execution flow to ensure task completion?

Accepted Answer

It breaks the goal into smaller, verifiable steps.. Claude Code utilizes a sub-tasking strategy for complex requests. It breaks down large goals into smaller, manageable steps, executing them sequentially or in parallel when appropriate. This modular approach allows the agent to maintain focus, track progress across multiple files, and verify results at each step, significantly increasing the probability of successful task completion compared to attempting large, atomic changes without validation.

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It executes the entire task as a single, atomic operation.

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It prompts the user to verify every single line of code generated.

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It pauses and requests human assistance for every file change.

Question 4

An AI engineering team is auditing an expensive Claude API integration processing millions of customer support queries daily. Which TWO strategies should they implement to effectively reduce token expenditure without sacrificing core model intelligence? (Choose two)

Accepted Answer

Implement Anthropic prompt caching for large, recurring system prompts and reference knowledge bases.. Optimizing context management and leveraging prompt caching are cornerstone strategies for cost reduction in high-volume Anthropic integrations. Caching static system prompts drastically lowers input token charges across repeated requests, while concise prompts eliminate redundant verbiage. Together, these practices protect infrastructure budgets while sustaining the semantic fidelity required by enterprise-grade support workflows.

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Switch every production workload immediately from Claude 3.5 Sonnet to Claude 3 Opus to maximize parallel processing.

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Disable response streaming to batch full payloads and reduce HTTP connection overhead.

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Hardcode maximum output tokens to five thousand across all API calls regardless of task complexity.

Question 5

When evaluating LLM performance, why is it critical to use a 'hold-out' test set of prompts that the model was not trained on?

Accepted Answer

To prevent overfitting the prompt engineering to a specific set of inputs.. Using a hold-out test set is essential for measuring generalization. If you evaluate a model using the same prompts used during development, you are testing for 'memorization' rather than true reasoning ability. A hold-out set ensures that the prompt engineering patterns you've developed are robust enough to work on unseen, novel inputs, providing a realistic prediction of performance in the production environment.

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To increase the token limit for the evaluation process.

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To ensure the model receives different system instructions every time.

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To reduce the cost of API calls during the testing phase.

Question 6

Refer to the exhibit. Claude Code has encountered a test failure while implementing a feature. How should the developer effectively guide the agent to resolve this error using the agent's internal capabilities?

Accepted Answer

Instruct the agent to read the logs and apply a fix based on the stack trace.. Claude Code excels at iterative debugging by leveraging its ability to read execution logs and apply fixes directly to code. The most efficient approach involves instructing the agent to analyze the stack trace, locate the undefined function call, and propose a corrective patch. This leverages the agent's autonomous capability to reason about project architecture rather than requiring manual intervention, keeping the development loop self-contained and highly efficient.

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Manually apply the fix to the code and restart the Claude Code session.

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Disable the agent's ability to run commands to prevent further errors.

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Run 'npm install' to ensure all dependencies are resolved before proceeding.

Question 7

A large-scale deployment of Claude is causing intermittent spikes in latency. Which security-related monitoring practice helps differentiate between a DDoS attack and legitimate heavy usage?

Accepted Answer

Analyze the request frequency and prompt diversity from specific origin IPs.. Differentiating between DDoS attacks and high legitimate load requires deep visibility into API request patterns. By tracking the distribution of source IPs, request frequency per token, and the complexity of prompts, security teams can identify anomalous patterns that signify an attack. This is crucial for maintaining availability without blocking legitimate users, ensuring that security measures are proportionate to the threat, rather than causing self-inflicted denial of service.

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Check the total cost of API usage in the Anthropic dashboard.

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Limit all users to one request per minute.

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Disable all external access to the API immediately.

Question 8

When using the Messages API, a developer wants to ensure that Claude does not use any tools and only provides a standard text response, even if tools are defined in the request. Which configuration should they use?

Accepted Answer

Set the 'tool_choice' parameter to {"type": "none"}.. The tool_choice parameter provides granular control over when and how Claude uses the tools provided in the tools array. Setting it to 'none' is the definitive way to disable tool use for a specific request. This is useful for debugging or for scenarios where you want to provide tool definitions but decide dynamically to ignore them.

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Omit the 'tools' parameter from the request entirely.

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Set the 'tool_choice' parameter to {"type": "auto"}.

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Include a system prompt that says 'Do not use any tools in this conversation'.

Question 9

Which object in the Claude API response body provides the exact count of tokens consumed by the prompt and the generated completion for billing and usage monitoring?

Accepted Answer

usage. Tracking token usage is essential for managing API costs and understanding the scale of data being processed. The Messages API returns a usage object that provides transparent metrics for every request. Developers use this data to implement internal billing, monitor for spikes in usage, and optimize their prompts to fit within budget and rate limit constraints.

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metadata

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token_details

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consumption

Question 10

An MCP Server is connected to a Host using the Stdio transport. If the server process crashes, how does the MCP architecture generally handle the reconnection logic?

Accepted Answer

The Host application detects the closed stream and must manage the restart.. The Stdio transport relies on standard input and output streams for communication between the host and the server. Because this is a process-level connection, a crash usually results in the termination of the stream. The responsibility for detecting this failure and initiating a recovery or restart lies with the MCP Host application.

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The MCP Client sends a 'heartbeat' signal to automatically restart the server.

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The MCP Server uses a sidecar process to monitor its own health and restart.

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The Model will identify the crash and suggest a fix to the developer.

Question 11

Refer to the exhibit. A developer is configuring an MCP server to provide an agent with database access. What is the primary purpose of the 'args' field in this configuration block?

Accepted Answer

It specifies the command-line flags and parameters used to initialize the server.. The 'args' field provides the necessary runtime parameters for the MCP server process. In this specific exhibit, it tells the 'uvx' command which package to run and which specific database file to mount. Correct configuration of these arguments is vital for the agent to successfully connect to the intended external resource.

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It defines the JSON Schema for the tools provided by the SQLite server.

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It lists the specific SQL queries the agent is permitted to execute.

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It acts as a whitelist for authorized users of the SQLite server.

Question 12

When using tool use with streaming enabled in the Anthropic API, how does the client receive the tool arguments?

Accepted Answer

Through incremental 'input_json' deltas within content block events.. Streaming tool use involves receiving the tool call in parts. The client receives a 'content_block_start' for the tool_use, followed by multiple 'content_block_delta' events containing fragments of the JSON in the 'input_json' field. The client must accumulate these fragments and parse the final JSON string only after the 'content_block_stop' event.

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As a single, complete JSON object in the first stream event.

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Via a separate WebSocket channel dedicated to tool execution.

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As a Base64 encoded string at the end of the message stream.

Question 13

When using Claude to process multiple independent documents in a single prompt, what is the best way to ensure Claude can refer to each document accurately in its response?

Accepted Answer

Wrap each document in tags like and .. Giving each document a unique identifier within XML tags is the most effective way to help Claude disambiguate between multiple sources. By using attributes or specific tag names like , you provide a clear reference system that the model can use in its reasoning and output, preventing it from mixing up details between different texts.

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Separate the documents with simple newline characters and horizontal rules.

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Provide each document in a separate user message within a single API call.

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Bold the title of each document at the start of its respective section.

Question 14

When constructing a request for the Messages API, where should instructions that guide Claude's personality, tone, and global constraints be placed for optimal performance and architectural clarity?

Accepted Answer

In the system top-level parameter outside of the messages array.. The Messages API distinguishes between the conversational flow and the operational constraints of the model. Placing instructions in the system parameter allows the model to separate the 'how' of the response from the 'what' of the user query. This structural separation is a core mechanic for building robust, steerable applications that behave consistently across different sessions.

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As the first message in the messages array with the role set to 'user'.

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As a hidden field within each individual content block of the user role.

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Appended to the end of the last message with the role set to 'assistant'.

Question 15

In the context of MCP, what is the primary purpose of the 'List Resources' capability of a server?

Accepted Answer

To allow the client to discover data sources that can be read by the model.. Resources in MCP are a way for servers to expose data that is not necessarily an executable tool. The 'List Resources' capability allows the client to see what data sources are available—such as log files, database tables, or documentation—so the model can then 'read' those resources to gain context for its tasks.

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To provide a directory of available functions the model can execute.

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To enumerate the hardware specifications of the host machine.

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To list the active connections currently handled by the MCP Client.

Question 16

A developer is designing a subagent architecture with the Claude Agent SDK. The main agent delegates a codebase audit to a specialized subagent to keep the primary conversation focused. Which TWO practices help ensure the delegation works correctly? (Choose two.)

Accepted Answer

Give the subagent a narrowly scoped task description and only the tools it needs for the audit.. Effective delegation depends on isolation and distillation. Scoping the subagent's task and tools keeps it focused and safe, while returning a concise structured summary preserves the main agent's context budget and attention. Sharing full history, granting broad tools, or dumping raw logs all reintroduce the noise that subagents are meant to filter out.

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Configure the subagent with the same broad toolset as the main agent to maximize flexibility.

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Have the subagent write its raw logs directly into the main agent's message history for transparency.

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Share the main agent's entire conversation history with the subagent so it has maximum context.

Question 17

A developer is building a Claude-powered agent that calls an internal `search_customer_notes` tool. The agent runs with a system prompt that includes a user-supplied `account_id`. A security review finds that an attacker can craft a prompt injection that convinces Claude to call the tool with a different `account_id` than the one in the system prompt. Which control most directly prevents this privilege escalation while keeping the agent functional?

Accepted Answer

Pass the authenticated `account_id` from the server-side session into the tool implementation and ignore any `account_id` Claude supplies in tool arguments.. Authorization decisions must be enforced outside the model. Because Claude can be manipulated by prompt injection, any parameter that determines which records are accessible must come from a trusted server-side session rather than from model output. Binding the account_id server-side keeps the agent useful while ensuring it cannot be tricked into reading another customer's notes.

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Increase the tool's rate limit so that mass enumeration of account IDs is impractical.

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Use a more capable Claude model with stronger instruction-following to reduce injection success.

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Add a sentence to the system prompt instructing Claude to never change the `account_id` value.

Question 18

A developer is building a pipeline that summarizes a 200-page technical manual with Claude Sonnet. The manual is too long for a single request, so the developer splits it into 40 chunks and summarizes each chunk independently. The final summaries must remain factually consistent with one another and with the source, and the developer has a fixed token budget. Which two techniques should the developer apply to keep the chunk summaries consistent and grounded? (Choose two.)

Accepted Answer

Carry a running 'state' summary of key entities, definitions, and decisions forward into each subsequent chunk request.. Cross-chunk consistency requires either shared context or a reconciliation step. Carrying a running state forward gives each request the key facts established earlier, while a verification pass that reconciles adjacent summaries catches contradictions before they propagate. Together they maintain grounding and consistency within a bounded token budget, unlike duplicating output or resending all prior text.

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Include the full text of all previously processed chunks in every new request.

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Ask the model to summarize each chunk twice and concatenate both outputs to increase coverage.

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Lower the temperature to zero and rely on deterministic sampling to guarantee identical facts across chunks.

Question 19

A developer is architecting a system where Claude must interact with a proprietary internal database. According to the Model Context Protocol (MCP) architecture, which component is responsible for surfacing the database schemas and handling the actual execution of the SQL queries?

Accepted Answer

MCP Server. In the Model Context Protocol architecture, the MCP Server is the specific component designed to host tools and resources. It acts as the interface to local or remote data sources, providing the necessary context and execution environment. Understanding this separation of concerns is vital for developers to ensure that security boundaries and data access are managed correctly within the MCP ecosystem.

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MCP Client

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MCP Transport

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MCP Host

Question 20

A developer is building a pipeline that uses Claude to convert free-text incident reports into a strict JSON object with fields severity, services, and summary. During testing, roughly 8 percent of outputs include a friendly preamble such as 'Sure, here is the JSON:' or wrap the object in markdown code fences, which breaks the downstream parser. The developer has already described the schema precisely in the prompt. What is the most reliable next step to eliminate the malformed outputs?

Accepted Answer

Add a few-shot example showing the exact JSON output with no preamble, and pre-fill the assistant turn with an opening curly brace so Claude must continue the object.. Pre-filling the assistant turn with an opening curly brace forces the model to begin inside the object, making a preamble or code fence structurally impossible. Pairing that constraint with a few-shot example that shows the exact no-preamble form teaches the desired surface pattern and covers cases where the schema itself is ambiguous.

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Lower the temperature to zero and add the sentence 'Respond only with JSON' to the end of the user message.

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Wrap the schema description in <json_schema> tags and instruct Claude to output only what matches the schema.

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Increase max_tokens so the model has room to finish the JSON object without truncation.