CCDV-F Practice Test 16 — 15 Questions

Question 1

A developer needs Claude to perform a complex data transformation and then explain its work. To get the best results, what order should these tasks be requested in the prompt?

Accepted Answer

Request the transformation first, followed by the explanation of the steps taken.. The order of operations in a prompt significantly affects the model's performance. By asking the model to perform the transformation first and then explain it, you allow the model to use its own generated output as context for the explanation. This ensures the explanation is grounded in the actual work performed, rather than being a hypothetical description.

Answer

Ask for the explanation first, then the transformation, to set the context.

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Ask for both simultaneously in a single sentence to ensure they are linked.

Answer

Put the explanation in the system prompt and the transformation in the user prompt.

Question 2

Refer to the exhibit. If this request is sent to Claude, what will be the result of the generated output?

Accepted Answer

The model will output its reasoning and then stop, omitting the final answer.. Stop sequences tell the API to terminate generation as soon as a specific string is produced. In this scenario, the developer has set the closing tag as a stop sequence. This means the model will stop immediately after it finishes its reasoning process, and the final answer that usually follows the thinking block will never be generated or returned.

Answer

The model will ignore the stop sequence because it is inside an XML tag.

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The API will return an error because the stop sequence must be a single word.

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The model will generate the full answer, but the tag will be hidden.

Question 3

A developer is building a high-traffic legal research tool. Which TWO conditions must be met for a content block to successfully return a 'cache hit' and reduce the cost of an API call?

Accepted Answer

The content must be identical, including all whitespace and formatting.. Prompt Caching is sensitive to the exact structure of the request. For a cache hit to occur, the content must be bit-for-bit identical to a previously cached version, and it must be positioned at the exact same location in the prompt (the prefix). Understanding these strict requirements prevents developers from accidentally breaking their cache and incurring unexpected costs due to minor formatting changes.

Answer

The request must be made within 5 minutes of the previous request.

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The 'max_tokens' parameter must be identical across both requests.

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The request must use the Claude 3 Opus model exclusively.

Question 4

A high-traffic application is frequently sending the same large set of reference documents (100,000 tokens) in the system prompt for every request. Which Claude API feature would most effectively reduce both the latency and the cost of these requests?

Accepted Answer

Implementing Prompt Caching using the 'cache_control' metadata.. Prompt Caching is a specialized mechanic for handling repetitive, large-scale context. By marking parts of the prompt as cacheable, developers can avoid re-processing the same data across multiple requests. This lead to significant cost savings on input tokens and drastically reduces the time to first token for the model's generated response.

Answer

Switching from Claude 3 Opus to Claude 3 Haiku.

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Compressing the reference documents using a text summarization tool.

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Increasing the 'max_tokens' limit to allow for larger responses.

Question 5

A legal tech company is using Claude 3.5 Sonnet to generate 5,000-word contract drafts. They notice that the output costs are significantly higher than the input costs. What is the most effective way to reduce these specific output costs without switching to a lower-quality model?

Accepted Answer

Refine the prompt to include strict length constraints and eliminate 'conversational filler'.. Output tokens are almost always more expensive than input tokens. In applications where the generation is very long (like contract drafting), managing the volume of generated text is the primary cost-control lever. Since the developer wants to keep the high-quality Sonnet 3.5 model, they must focus on prompting techniques that encourage conciseness or use structured generation to avoid redundant or unnecessary verbiage.

Answer

Use prompt caching to store the generated contract for later use.

Answer

Switch to the Batch API to get a 50% discount on the output tokens.

Answer

Increase the 'max_tokens' parameter to allow the model more room to think.

Question 6

When designing agentic loops with the Anthropic SDK, which TWO practices help prevent infinite tool-use cycles? (Select exactly 2)

Accepted Answer

Implementing a hard limit on the number of sequential tool calls.. Preventing infinite loops is crucial for cost management and system stability. By enforcing step limits and providing clear stop conditions, developers ensure the agent acts as a bounded processor. These patterns are fundamental to building predictable AI agents that fulfill user requests without falling into recursive tool-calling patterns that exhaust token budgets and latency thresholds.

Answer

Increasing the max_tokens parameter to allow longer reasoning.

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Using a higher temperature to encourage creativity.

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Caching all tool outputs for faster retrieval.

Question 7

An application needs to ensure that Claude never uses its pre-trained knowledge to answer questions, but only uses the provided context. After placing instructions in the system prompt, the developer still sees Claude occasionally using outside info. What is the most effective API-level mechanical adjustment to further constrain Claude?

Accepted Answer

Use pre-filling by ending the 'messages' array with an 'assistant' message like 'Based ONLY on the context provided, I will answer...'. While system prompts are the primary way to give instructions, pre-filling the assistant's response is a more forceful mechanical constraint. By starting the assistant's response with a specific phrase, you lock the model into a particular persona or logical path, making it much harder for the model to deviate into its default behaviors or general knowledge.

Answer

Set 'temperature' to 1.0 to encourage more creative following of the system instructions.

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Increase the 'top_p' value to 1.0 to ensure all possible valid answers are considered.

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Add a 'stop_sequence' for the word 'I' to prevent the model from speaking in the first person.

Question 8

Which THREE criteria are most important when deciding whether to upgrade from Claude 3 Haiku to Claude 3.5 Sonnet for a production application?

Accepted Answer

The complexity of the reasoning or creative task required.. Upgrading models involves a trade-off between performance and cost. Developers must evaluate if the task requires higher-level reasoning (where Haiku might fail), if the application can tolerate the slightly higher latency of Sonnet, and if the budget can accommodate the significant price increase. These three factors ensure that the model choice aligns with both technical and business constraints.

Answer

The availability of the 'stream' parameter.

Answer

The total number of API keys generated for the project.

Question 9

Refer to the exhibit. How does Claude Code handle this interruption, and what is the expected outcome?

Accepted Answer

The agent updates the plan and skips the 'test' directory.. Claude Code is built to handle mid-task updates to instructions. When the user provides a constraint update (like excluding a folder), the agent halts its planned execution to incorporate this new requirement into its plan. This allows for safe, interactive corrections to mass-refactoring tasks, ensuring that the developer remains in control and preventing accidental modifications to sensitive or critical parts of the codebase during large-scale operations.

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The agent proceeds with the original plan to ensure consistency.

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The agent crashes and requires a session restart.

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The agent asks the user to manually perform the file changes.

Question 10

When using the Messages API, what happens if the 'messages' array provided in the request is empty?

Accepted Answer

The API will return a 400 Bad Request error indicating that at least one message is required.. The Messages API has strict validation rules for the 'messages' array. It is the core of the request, representing the conversation that Claude is meant to continue. An empty array is logically equivalent to asking a model to respond to nothing, which is not supported by the API's current design and validation logic.

Answer

Claude will generate a random greeting message to start the conversation.

Answer

The API will process the 'system' prompt and return a response based solely on those instructions.

Answer

Claude will return the last response it generated for that specific API key.

Question 11

When defining a tool for an agent using the Anthropic SDK, which field is required to ensure the model understands the specific schema of the input arguments?

Accepted Answer

The 'input_schema' property using JSON Schema format.. The input_schema field is mandatory because it uses JSON Schema to define the structure, types, and constraints of the data the agent must provide. Without this schema, the model cannot reliably generate valid tool calls that match the underlying function's expectations, leading to runtime errors and failed executions in the agentic workflow.

Answer

The 'examples' array within the tool definition.

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A 'system_prompt' specific to that individual tool.

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The 'output_format' property for return values.

Question 12

Which of the following is the most secure way to handle API keys in an Anthropic-integrated cloud application?

Accepted Answer

Use a cloud-native secret management service to inject keys at runtime.. Managing secrets securely is a standard security practice. Using a dedicated secret manager allows for automatic rotation, granular access control, and audit logging. This prevents the keys from being stored in version control or plain text files, reducing the risk of unauthorized access. It is the industry-standard approach for protecting credentials used by distributed cloud applications.

Answer

Store keys in an encrypted JSON file within the application directory.

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Define keys as environment variables in the Dockerfile during build.

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Hardcode the keys as constants in the configuration file.

Question 13

A developer is using 'top_k' to control the diversity of Claude's responses. If they set 'top_k' to 1, what is the expected behavior of the model during token generation?

Accepted Answer

Claude will pick the most likely next token every time, similar to 'greedy' decoding.. The 'top_k' parameter limits the model's choice of the next token to the 'k' most likely options. Setting this value to 1 is a restrictive configuration that forces the model to always pick the single most probable token. This results in highly deterministic and 'greedy' sampling, which can be useful for tasks requiring high precision.

Answer

Claude will only use words from the top 1% of its vocabulary.

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Claude will prioritize tokens that have only appeared once in the preceding text.

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Claude will stop generating after exactly one token is produced.

Question 14

Which TWO of the following practices are considered best practices for optimizing Claude's performance using prompt engineering? (Choose two)

Accepted Answer

Use XML tags (e.g., ...) to delineate different sections of the prompt.. Prompt engineering is about clarity and structure. By providing specific constraints and using XML tags, you create a structured input that Claude can parse more effectively. These techniques minimize ambiguity and provide clear boundaries for where the model should focus its attention, ultimately leading to higher quality, more consistent, and more predictable outputs across varying inputs and complex tasks.

Answer

Include long, conversational filler text to make the model feel more comfortable.

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Avoid using examples, as they encourage the model to copy rather than think.

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Always set the maximum token count to 4096, regardless of the task.

Question 15

When designing a system that uses Claude to assist in writing code, what is the most important security consideration regarding the model's output?

Accepted Answer

Generated code must pass static analysis and human review before deployment.. AI-generated code may contain vulnerabilities, insecure patterns, or outdated libraries. The most critical security step is treating model output as untrusted input that requires rigorous automated scanning and human verification. This protects the organization from inadvertently deploying vulnerable code, which could lead to systemic security breaches, data loss, or non-compliance with secure software development lifecycle (SDLC) standards.

Answer

The model should be allowed to execute the code it generates.

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The model should have access to your private repository for code quality.

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The model's temperature should be set to 1.0 for better code creativity.