CCAO-F Practice Questions 2 — 50 Questions

Question 1

A developer is building an application that uses Claude to summarize news articles. They notice that Claude sometimes refuses to summarize articles involving violent crime, citing safety concerns. What is the best way for the developer to address this while maintaining responsible use?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Refine the prompt to specify the journalistic context and requested summary length.. Safety filters can sometimes be overly sensitive (false positives). The developer should refine the prompt to clarify the educational or journalistic purpose of the request. This helps the model understand that the goal is information summarization rather than the promotion or glorification of violence, which aligns with the intended use of the safety guardrails.

Answer

Use a jailbreak prompt to force the model to ignore its safety training.

Answer

Contact Anthropic support to have all safety filters disabled for the account.

Answer

Switch to a smaller model version that has fewer safety features.

Question 2

An enterprise legal team needs to analyze a 150,000-token collection of merger and acquisition documents to identify conflicting indemnity clauses. Which feature of the Claude 3 model family is most critical for ensuring the entire dataset is processed in a single inference pass without losing context?

Accepted Answer

200,000-token context window. The context window determines the amount of information the model can hold in its active memory during a single request. For legal analysis involving massive document sets, a 200,000-token context window allows Claude to 'see' all relevant clauses simultaneously. This enables the model to identify cross-document contradictions and nuances that would be missed if the data were fragmented. (70 words)

Answer

Multimodal Vision capabilities

Answer

System Prompts

Answer

Temperature settings

Question 3

Which of the following describes the purpose of 'Role' assignment in the Messages API?

Accepted Answer

To differentiate between the user's input and the model's past responses.. Assigning roles ('user' or 'assistant') allows the API to maintain conversational context and structure. The model needs to identify which inputs are the user's queries and which are its own prior outputs to maintain logical flow. This is fundamental to Claude's ability to engage in multi-turn dialogues where the model references previous context to generate coherent, relevant, and context-aware responses in ongoing sessions.

Answer

To define the administrative access level of the API user.

Answer

To specify the persona the model should adopt for the entire request.

Answer

To allow the model to rewrite the user's prompt for better accuracy.

Question 4

Refer to the exhibit. Why is the use of the and tags considered a best practice for Claude prompting?

Accepted Answer

It improves the model's ability to distinguish context from instructions.. Claude is specifically trained to recognize and utilize XML tags for structural organization. These tags help the model delineate between instructions, metadata, and actual content. In complex prompts, this separation reduces the likelihood of the model misinterpreting data as instructions, thereby increasing the reliability and accuracy of the generated responses.

Answer

It is a requirement of the JSON schema for the Messages API.

Answer

It enables Claude to parse the content as a valid XML object.

Answer

It automatically bypasses the model's safety filters for large data.

Question 5

A user wants to improve the quality of Claude's creative writing. Which TWO prompting techniques are likely to produce more vivid and stylistically consistent results?

Accepted Answer

Using a system prompt to assign a specific authorial persona to the model.. Creative writing benefits from both clear persona definition and illustrative examples. Role prompting sets the 'voice,' while few-shot examples provide a concrete reference for the level of vividness and style expected. Together, these techniques ground the model's creative output in a way that simple instructions cannot.

Answer

Increasing the 'max_tokens' to allow the model to write longer descriptions.

Answer

Using only zero-shot prompts to allow the model's 'natural' creativity to shine.

Answer

Repeating the phrase 'be very vivid' five times throughout the prompt.

Question 6

A startup is building a Claude-powered assistant for a children's tutoring app. During red-team testing, a prompt is found that makes Claude role-play as a character who encourages a minor to keep a harmful secret from parents. The startup wants to prevent this without blocking legitimate tutoring conversations. Which approach best aligns with Anthropic's safety guidance for handling such edge cases?

Accepted Answer

Implement input and output classifiers that detect and block prompts or responses involving harmful secrets with minors, and regularly red-team the system to find new bypasses.. The correct approach combines input/output classifiers with continuous red-teaming, as recommended by Anthropic for high-risk applications involving minors. Classifiers act as a safety net even if the model fails to refuse, and red-teaming uncovers new attack patterns. This layered defense protects users while preserving legitimate tutoring functionality, aligning with Anthropic's principle of balancing safety and helpfulness.

Answer

Set a low temperature and a max token limit to reduce the chance of creative harmful outputs, and monitor logs for any violations.

Answer

Add a system prompt instructing Claude to never discuss secrets and rely on the model's built-in safety training to refuse any related requests.

Answer

Fine-tune Claude on a dataset of safe tutoring conversations so it learns to avoid harmful secrets, then deploy without additional filters.

Question 7

A developer maintains a long-running support session and wants to keep the conversation coherent without exceeding the model's context window. They currently resend the entire transcript on every turn. Which approach best addresses the context limit while preserving conversational continuity?

Accepted Answer

Summarize or truncate older turns and send only the relevant recent messages plus a summary.. The context window limits the combined tokens of input and output. Because the developer resends the full transcript each turn, the payload grows until it overflows. Condensing older turns into a summary or trimming stale messages, while keeping recent exchanges intact, preserves continuity and keeps each request within the token budget.

Answer

Increase 'max_tokens' so the model can hold more of the transcript in memory.

Answer

Set a higher 'temperature' so the model compresses prior context automatically.

Answer

Switch the conversation to a single user message that concatenates all prior turns into one string.

Question 8

A team is instrumenting its Claude Messages API integration to monitor usage and cost. Which TWO response fields should the developer log to track token consumption per request? (Choose two.)

Accepted Answer

usage.output_tokens. The usage object in a Messages API response exposes input_tokens and output_tokens, which together quantify consumption for each call. Because input and output tokens are priced separately, both must be logged for accurate cost attribution. Other fields like stop_reason, id, and model provide context or tracing value but do not measure token usage.

Answer

stop_reason

Answer

model

Answer

id

Question 9

A developer is building an internal tool that lets employees query Claude about pending layoffs, performance reviews, and salary bands using scraped HR documents. The company's legal team has not reviewed the data handling. Which responsible-use concern is most significant before this tool goes live?

Accepted Answer

Sensitive personal and confidential employment data is being processed without legal review, creating privacy and confidentiality risk.. When an internal tool exposes layoff plans, performance reviews, and salary bands through Claude, the dominant risk is unauthorized processing of sensitive and confidential data without legal or privacy review. Addressing data governance, access controls, and regulatory obligations before launch is the responsible-use priority; output quality and rate limits are secondary operational matters.

Answer

The scraped documents may contain outdated formatting that confuses the model's retrieval step.

Answer

Employees might use the tool more often than the license tier allows, causing unexpected API rate limits.

Answer

The model may produce grammatically inconsistent answers across sessions, reducing employee trust in the tool.

Question 10

A developer is building an internal Claude-based tool that helps employees draft performance reviews. During testing, a reviewer notices that when the tool is asked to summarize a manager's notes about a female employee, it tends to soften critical feedback, while notes about a male employee produce more direct criticism. The developer wants to address this behavioral difference before rollout. Which action is most appropriate?

Accepted Answer

Collect evaluation data across gender and other demographic groups, test prompt and fine-tuning mitigations, and monitor outputs after deployment.. The appropriate response is a structured bias-mitigation cycle: measure disparities with disaggregated evaluations, test interventions such as prompt changes or fine-tuning, and monitor after launch. Performance reviews are high-impact, so unverified fixes or exclusionary workarounds are inadequate. Evidence-based iteration is the responsible path to reducing gendered tone differences.

Answer

Restrict the tool to male employees only until a future model version resolves the bias, to avoid producing unfair reviews.

Answer

Ignore the difference because performance reviews naturally vary by individual and the model is only reflecting the manager's original notes.

Answer

Add a system prompt instructing Claude to be equally critical for all employees, then ship the tool without further evaluation.

Question 11

A developer writes a Python script that calls the Claude Messages API. The script currently reads the API key from a hardcoded string in the source file and the file is committed to a public repository. Which change best addresses the security concern while keeping the script functional?

Accepted Answer

Move the key into an environment variable and read it at runtime with os.environ, keeping the key out of source control.. Credentials must never live in source control. Reading the API key from an environment variable at runtime removes it from the codebase and repository history, so the exposure is eliminated while the script continues to authenticate normally. Any key that has already been committed should also be rotated.

Answer

Base64-encode the hardcoded key so it is not readable as plain text in the repository.

Answer

Obfuscate the key by splitting it across several string concatenations in the code before passing it to the client.

Answer

Add the source file to a .gitignore entry so future commits exclude it, leaving the existing key in the file.

Question 12

A developer is writing a prompt for Claude to classify support tickets into categories. They want to reduce ambiguous or inconsistent labels. Which TWO techniques should they apply? (Choose two.)

Accepted Answer

Define each category with clear criteria and include boundary examples.. Consistent classification depends on unambiguous category definitions and deliberate reasoning. Clear criteria with boundary examples give Claude explicit rules, while asking for reasoning before the label encourages careful evaluation of the ticket. Together they reduce arbitrary or inconsistent assignments without relying on sampling changes.

Answer

Set the temperature to 1 to encourage diverse labeling.

Answer

Provide only the category names without descriptions to keep the prompt short.

Answer

Ask Claude to output multiple labels for each ticket to cover all possibilities.

Question 13

A financial analyst is building a Claude-powered assistant that must extract the total amount due from scanned invoices. The invoices vary widely in layout and wording, and the extracted value is later used to trigger payments. The analyst wants to maximize accuracy and avoid plausible but incorrect numbers. Which prompting approach is most appropriate?

Accepted Answer

Use a prompt that instructs Claude to extract the total only from the provided invoice text, and to respond with 'Not found' if the total is not explicitly stated.. Extraction tasks that feed downstream actions like payments require the model to stay strictly within the provided source text and to signal when the requested value is absent. Allowing a 'Not found' response prevents fabrication and supports human review. Approaches that encourage guessing, raise randomness, or force pattern application regardless of source content all increase the risk of plausible but incorrect values, which is exactly what the analyst must avoid.

Answer

Set the temperature to a high value so Claude explores multiple interpretations of the invoice and selects the most consistent total across them.

Answer

Provide a few-shot example showing a correctly extracted total, then ask Claude to apply the same pattern to any invoice regardless of whether the total is present.

Answer

Instruct Claude to return its best guess for the total, and if uncertain, to generate the most likely amount based on typical invoice patterns.

Question 14

A developer is using the Messages API and wants Claude to adopt a strict persona as a compliance reviewer for every request in a long conversation, without repeating the persona instructions in each user turn. The persona must apply to all messages and should take precedence over casual instructions the user might add later. Where should the developer place these persona instructions?

Accepted Answer

In the system prompt parameter, which is applied across all turns of the conversation.. The system prompt is the correct location for instructions that must frame every turn and carry higher priority than user turns. It persists across the conversation without being repeated, and Claude is trained to respect system-level guidance over casual user instructions, which satisfies the compliance persona requirement.

Answer

As a trailing assistant message that restates the persona before each user reply.

Answer

In the first user message of the conversation, before the actual task.

Answer

In the metadata field attached to the request for logging and traceability.

Question 15

A developer is implementing a retrieval-augmented generation pipeline with the Claude Messages API. Retrieved documents are inserted into the user turn, and the developer wants the model to cite which document supports each claim. Which technique most directly improves the model's ability to attribute statements to specific source documents?

Accepted Answer

Number or tag each retrieved document in the prompt and instruct the model to reference those identifiers in its answer.. Attribution improves when the prompt makes source boundaries explicit. Labeling each retrieved document with a stable identifier and instructing the model to cite that identifier gives it a concrete token to attach to each claim, and gives the application something to validate. Sampling settings and output length do not create source-to-claim mappings, and removing document separators actively destroys the structure needed for citation.

Answer

Increase max_tokens so the model has room to quote each source document verbatim in the answer.

Answer

Concatenate all retrieved documents into one continuous block with no separators to keep the prompt compact.

Answer

Raise the temperature so the model explores more of the retrieved context before answering.

Question 16

A developer is building a document-summarization service that sends very large PDFs to Claude. The first request returns a 413 error with a message indicating the request entity is too large. The developer wants to keep using the Messages API directly. Which change best resolves the error while preserving the ability to summarize the full document?

Accepted Answer

Split the document into smaller chunks and send them in multiple Messages API calls, then combine the partial summaries.. An HTTP 413 signals that the request body exceeds the API's permitted size. The Messages API does not accept arbitrarily large inputs, so the developer must reduce each request's payload. Chunking the document into smaller pieces and summarizing each, then combining results, keeps every request within limits and still covers the whole document. Output-length parameters, streaming flags, and sampling settings do not influence request size limits.

Answer

Set the stream parameter to true so the API streams the request body and bypasses the size limit.

Answer

Lower the temperature to 0 so the model processes the input more efficiently and accepts the larger payload.

Answer

Increase the max_tokens value in the request to allow the API to accept more input.

Question 17

An engineering team wants Claude to classify thousands of support tickets into categories. They need the model to always return one of five exact category labels. Which approach most reliably constrains the output to those labels?

Accepted Answer

List the five allowed labels in the system prompt and instruct the model to output only one of them.. To force output into a closed set of labels, the prompt must enumerate the allowed values and instruct the model to return exactly one. Placing this in the system prompt ensures the constraint applies to every classification request. Vague instructions, high temperature, or downstream keyword matching all allow invalid or ambiguous outputs that break automated pipelines.

Answer

Use a high temperature so the model explores all categories evenly.

Answer

Post-process the model's free-text output with a keyword search for category names.

Answer

Ask the model to 'pick the best category' in the user message.

Question 18

A developer is building a document Q&A service on the Claude API. Each request sends the full 180-page PDF as base64 in a single text content block, and most calls now fail with a 400 error stating the request exceeds the maximum allowed size. The developer wants to keep using the same model and continue asking questions about the whole document. Which approach should the developer take?

Accepted Answer

Upload the PDF with the Files API, then reference the returned file identifier in the message content instead of embedding base64.. Large documents should be ingested once through the Files API and then referenced by identifier in subsequent Messages calls, which keeps each request's inline payload small while preserving full-document context. Re-sending base64, relocating it to the system prompt, or compressing it all leave the oversized or unreadable payload inside the request, so the size rejection or loss of usable content persists.

Answer

Split the document into chunks, send each chunk in its own request, and merge the returned answers inside the application.

Answer

Move the PDF into the system prompt so that the document bytes are not counted against the user message size.

Answer

Compress the base64 string with gzip and place the compressed value in the text content block.

Question 19

A data engineer is using Amazon Bedrock to invoke Claude 3 Haiku for classifying customer feedback into categories. They notice that the model sometimes returns categories that are not in the predefined list. Which change to the prompt is most likely to improve adherence to the allowed categories?

Accepted Answer

Provide a few-shot examples in the prompt showing correct classifications for similar feedback, including the exact category labels.. Few-shot examples in the prompt show Claude the exact category labels and the expected format, which significantly improves adherence to a predefined set. By demonstrating correct classifications, the model learns the pattern and is less likely to invent new categories. Other parameters like temperature, stop sequences, and max_tokens affect randomness, truncation, and length, but do not teach the model which labels are valid.

Answer

Increase the temperature to 1.0 so Claude explores more creative category assignments.

Answer

Add a stop sequence that matches the first invalid category so Claude stops generating when it deviates.

Answer

Reduce the max_tokens parameter so Claude has less room to generate invalid categories.

Question 20

A support-engineering team is designing a Claude prompt to triage incoming bug reports into one of five severity levels. They observe that when the report is ambiguous, Claude sometimes invents a justification for a severity that is not actually supported by the text. They want the prompt to make uncertainty explicit rather than forcing a confident label. Which TWO changes should they make to the prompt? (Choose two.)

Accepted Answer

Add an explicit 'unknown' or 'needs_review' option to the allowed severity set and instruct Claude to choose it when the report lacks sufficient detail.. Grounding each severity in a verbatim evidence quote forces the model to anchor claims in the report text, and offering an explicit needs_review category gives it a legitimate way to express uncertainty instead of inventing support. Together these two changes convert an overconfident classifier into one that surfaces ambiguity for human follow-up.

Answer

Raise the temperature so Claude explores a wider range of possible severity interpretations for each report.

Answer

Ask Claude to think step by step silently and return only the final severity label with no supporting text.

Answer

Provide ten few-shot examples in which every report is confidently assigned one of the five severities.