CCAR-F Practice Test 12 — 15 Questions

Question 1

An agent must classify incoming support tickets and then route each to one of four specialized sub-agents. The architect notices the router sometimes dispatches the same ticket to two sub-agents. Which design change most directly prevents duplicate dispatch?

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

Accepted Answer

Give the router a single `route_ticket` tool whose input schema requires one category, and have the orchestrator execute only the first matching tool_use.. Exactly-once routing is an orchestration invariant. Encode the intent in a single tool with an enumerated category, and enforce it in the host by executing at most one routing tool_use per turn. This combination gives the model a clear decision surface while making duplicate dispatch structurally impossible, regardless of sampling behavior.

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Lower the router's temperature to reduce randomness in classification.

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Add a system-prompt sentence telling the router to select exactly one category.

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Increase the number of categories so each ticket has an obvious best match.

Question 2

A team is using Claude to generate a structured incident report from raw log excerpts. The report must contain a 'summary' paragraph, a 'root_cause' field, and a 'remediation' list. During review, engineers find that remediation steps sometimes appear inside the summary paragraph, and summaries sometimes contain root-cause speculation. Which technique most reliably keeps each piece of content in its designated section?

Accepted Answer

Define each section with XML tags and include a one-line description of what belongs in each tag, then instruct Claude to place content only within the matching tag.. Content stays in its designated section when each section is a named container with an explicit description of its contents. XML tags provide those containers and the descriptions disambiguate which material belongs where, so remediation steps have their own list and root-cause analysis has its own field. Narrative formats, generic guidance, and randomized ordering do not create the structural boundaries the task requires.

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Ask Claude to write the report as a single flowing narrative and let reviewers sort the content into the three sections afterward.

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Randomize the order of the three sections on each invocation so the model learns to keep them separate.

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Increase the length of the prompt by adding several paragraphs of general guidance about good report writing.

Question 3

A financial analyst wants Claude to extract the total amount due from each invoice in a batch of 300 PDF-extracted text blobs, returning results as JSON with fields "invoice_id", "amount_due", and "currency". Some invoices list multiple line items and a subtotal, while others show only a single grand total. Which prompt design most reliably produces consistent, machine-parseable extraction across all invoices?

Accepted Answer

Provide a strict JSON schema with the three required fields, instruct Claude to output only valid JSON, and include two worked examples covering both single-total and multi-line-item invoices.. Reliable batch extraction requires a fixed schema, an explicit instruction to emit only JSON, and few-shot examples that cover every structural variant in the input set. Combining a named-field schema with instruction and examples constrains the model's output shape so a parser can consume it without manual intervention. Free-text, high-temperature, or echo approaches all fail to yield consistent, machine-readable fields.

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Ask Claude to 'summarize the key financial figures' and parse whatever numbers appear in the free-text response.

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Ask Claude to return the entire invoice text unchanged so the analyst can manually locate the amount due in each document.

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Set the temperature to 1.0 so Claude produces varied outputs, then use a fuzzy regex to catch any dollar amounts in the response.

Question 4

An architect is designing a Claude agent that must autonomously handle customer disputes end to end. The agent may issue refunds up to $200, but any refund above that amount must be approved by a human reviewer. The system must not block the entire workflow while waiting for approval. Which orchestration pattern best satisfies these constraints?

Accepted Answer

Model the refund as a tool that returns a pending status plus a case identifier, persist the agent state, and resume the conversation when the human decision arrives.. Human-in-the-loop patterns work best when the agent yields rather than blocks. A refund tool that returns a pending status with a case identifier lets the orchestrator persist the conversation and resume it when the reviewer decides. This keeps the workflow responsive, avoids tying up connections, and cleanly injects the approval or denial back into the agentic loop as a new tool_result.

Answer

Have the agent call a refund tool that internally pauses the HTTP request until a human approves, then returns the result in the same tool_result.

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Route all disputes to a queue processed only by humans, removing the agent from the approval path entirely.

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Instruct the agent in the system prompt to always ask the customer to wait while it internally polls the approval service every few seconds.

Question 5

A developer is extracting line items from invoices. The prompt includes a schema and examples, yet Claude occasionally invents field names not in the schema. Which change most directly prevents hallucinated field names?

Accepted Answer

Define the extraction schema as a tool 'input_schema' and force tool use.. Expressing the extraction schema as a tool 'input_schema' and forcing tool use constrains Claude's output to the defined fields. Because the API validates the tool call input against the schema, invented field names are structurally prevented. This is stronger than examples, temperature tuning, or negative instructions, which only influence behavior probabilistically.

Answer

Lower the temperature to 0 to reduce randomness in field name selection.

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Add more few-shot examples showing correct field names.

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Instruct Claude in the system prompt to 'never add fields not in the schema'.

Question 6

A new engineer on a team wants to see every slash command currently available in their Claude Code session, including custom commands the team has added, before starting a large refactor. Which action should they take?

Accepted Answer

Type `/help` at the prompt to display the list of available slash commands, including custom ones.. Claude Code exposes slash-command discovery through `/help`, which lists both built-in commands and any custom commands defined for the project or user. Because the engineer needs a complete, current view before starting a refactor, invoking `/help` inside the session is the direct and authoritative way to get that list.

Answer

Run `claude --list-commands` from the shell before launching the interactive session.

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Open the `~/.claude/commands` directory and read every Markdown file to reconstruct the command list manually.

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Press `Ctrl+R` to open the command history and infer the available commands from prior sessions.

Question 7

A developer is using Claude to classify customer feedback into categories: 'bug', 'feature request', or 'complaint'. The developer wants to ensure consistent output format that can be easily parsed by a downstream system. Which approach is most appropriate?

Accepted Answer

Ask Claude to respond with a single word from the list of categories.. For consistent, parsable output, the simplest and most effective method is to instruct Claude to respond with a single word from a predefined list. This constrains the output format directly. High temperature, explanations, or fine-tuning are unnecessary and may introduce variability or complexity.

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Ask Claude to explain its reasoning before providing the category.

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Use a high temperature to allow Claude to choose the most appropriate category.

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Fine-tune Claude on a dataset of labeled customer feedback.

Question 8

A security-conscious architect is standardizing how Claude Code is configured across a large engineering organization. Which TWO practices best reduce the risk introduced by project-level configuration that arrives with cloned repositories? (Choose two.)

Accepted Answer

Use enterprise-managed policy settings to constrain what project-level configuration is permitted to do.. The risk is that cloning a repository imports configuration capable of executing commands. The two complementary controls are inspection and constraint: review what a project declares before trusting it, and use managed policy to cap what project scope can do regardless of its contents. Blanket hook bans remove useful capability without targeting the threat, storing secrets in shared files worsens exposure, and depending solely on model judgment leaves no enforceable boundary.

Answer

Store credentials and API keys directly in the project settings file so every session authenticates consistently.

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Ask developers to disable all hooks globally on their machines.

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Rely on the model to refuse to run any command that looks dangerous, without additional configuration.

Question 9

A nightly job uses Claude to classify 500,000 support tickets into categories. The job runs for several hours and results are consumed the next morning; nobody is waiting on individual responses. Which approach is most appropriate for controlling cost and rate-limit pressure?

Accepted Answer

Submit the classifications through the Message Batches API, which processes requests asynchronously at reduced cost.. Offline, high-volume, latency-tolerant workloads are the canonical fit for the Message Batches API. It provides asynchronous processing with a substantial cost discount and avoids the throttling that concurrent synchronous calls would trigger, while the overnight window means the extended turnaround harms nothing. The other approaches either pay full price, degrade accuracy, or reimplement pacing that the batches endpoint already handles.

Answer

Reduce the model size and classify with a single-token response, accepting lower accuracy to save money.

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Send all 500,000 requests concurrently with the synchronous Messages API to finish the job as fast as possible.

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Implement client-side request queuing with exponential backoff against the synchronous Messages API.

Question 10

A financial analyst uses Claude to generate quarterly earnings summaries from raw financial data. The summaries must include precise numerical figures. The analyst notices that Claude occasionally transposes digits when copying numbers from the input. Which architectural change is most effective for reducing this error?

Accepted Answer

Use a chain-of-thought prompt that asks Claude to first extract all numbers into a structured list, then generate the summary using that list.. Digit transposition often occurs when the model must simultaneously extract and synthesize information. By using a chain-of-thought prompt to first extract numbers into a structured list, you isolate the extraction task, reducing errors. This also enables programmatic verification. Other options either increase randomness, require costly fine-tuning, or reduce context without targeting the error.

Answer

Increase the temperature parameter to encourage more creative output.

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Fine-tune Claude on a dataset of financial summaries with correct numbers.

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Reduce the context window by providing only the most recent quarter's data.

Question 11

A developer is building a contract-analysis pipeline. The prompt instructs Claude to return JSON with fields 'party_a', 'party_b', and 'effective_date'. In testing, Claude sometimes wraps the JSON in a Markdown code fence or adds a trailing comment, causing json.loads to fail. Which approach best ensures the response can be parsed directly as JSON?

Accepted Answer

Use a tool definition with a JSON schema for the contract fields and require the model to call that tool.. Tool use with a JSON schema is the most reliable way to force structured output. The API validates the model's arguments against the schema and returns them as structured data, so the developer receives fields that match party_a, party_b, and effective_date without Markdown. Prompt-level requests and temperature changes do not guarantee parseable JSON in the same way.

Answer

Increase the model's max_tokens so the full JSON object fits in one response.

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Add 'Please do not use Markdown' to the end of the prompt.

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Instruct Claude to wrap the JSON in triple backticks so it is easy to find.

Question 12

A claims-processing agent must extract structured fields from scanned documents, then decide whether to auto-approve, request more evidence, or escalate to a human. The architect wants deterministic, auditable control over which branch executes rather than letting Claude narrate the decision. Which TWO design choices best achieve that? (Choose two.)

Accepted Answer

Have Claude return a JSON object with a decision field and validate it against a schema before acting on it.. Deterministic, auditable branching comes from making the decision an explicit structured signal the orchestrator can inspect and validate before acting. Either a small set of named tools or a schema-validated decision field turns the model's choice into a typed, loggable value, whereas text conventions, temperature tuning, and unmediated API access all leave the branch implicit or uncontrolled.

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Allow Claude to call any of the organization's internal APIs directly so it can decide the branch at execution time without orchestrator involvement.

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Instruct Claude in the system prompt to begin every response with the word APPROVE, EVIDENCE, or ESCALATE, then parse that prefix in application code.

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Set temperature to its maximum so the agent explores all possible decision branches before committing to one.

Question 13

An architect is defining an MCP tool that returns weather data for a given city. The tool's output schema currently returns a free-text string. The architect wants to improve the model's ability to use the data in subsequent reasoning. What is the best change to the tool's output definition?

Accepted Answer

Return a structured JSON object with fields for temperature, humidity, and conditions.. Returning a structured JSON object with explicit fields like temperature, humidity, and conditions gives the model a clear, machine-readable format. This reduces ambiguity, supports reliable extraction of values, and integrates well with downstream reasoning or tool calls. Structured output is a best practice for MCP tools that provide data used in further steps.

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Return a base64-encoded binary blob representing the weather data.

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Return a list of key-value pairs as a single concatenated string.

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Return a natural language sentence that includes all relevant weather details.

Question 14

A retrieval-augmented pipeline answers questions about internal policies. Retrieved chunks are inserted into the prompt, but the model sometimes blends facts from two similar policies into one incorrect answer. Evaluation shows retrieval precision is high and the correct chunk is always present. Which architectural change most directly reduces this blending?

Accepted Answer

Instruct Claude to cite the source document and section for every factual claim, and to answer only from the cited passage.. When the right evidence is present but answers still fuse details from similar documents, the defect lies in synthesis, not retrieval. Mandating per-claim citations constrains the model to ground each statement in a named passage, which both prevents silent merging and exposes genuine conflicts between policies so a human or downstream rule can resolve them.

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Lower the temperature to zero so the model produces more deterministic and factual responses.

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Move the retrieved chunks into the system prompt and keep the user question in the user turn.

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Increase the retrieval top-k so more chunks are included, giving the model additional context about each policy.

Question 15

An architect is building an MCP server that exposes a tool for querying a customer relationship management (CRM) system. The tool accepts a free-form text parameter called 'query' and returns matching customer records. During testing, the model frequently sends malformed queries that cause the CRM API to return errors, and the model then hallucinates customer data. Which change to the MCP tool definition is the most effective way to constrain the model's input and reduce these errors?

Accepted Answer

Add a JSON Schema with an enum that lists the exact CRM API query operators the tool supports, and require the model to select from that list.. The core issue is that the tool accepts unconstrained free-form text, allowing malformed queries that the CRM API rejects. Adding a JSON Schema with an enum for the query operator enforces valid input at the protocol level, preventing errors before they reach the API. This is the most direct and reliable fix for the described failure mode.

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Remove the 'query' parameter and replace it with a single numeric 'customer_id' parameter, forcing the model to always look up a specific record.

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Add a system prompt instructing the model to only send well-formed queries and to apologize if the CRM API returns an error.

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Increase the model's temperature to encourage more creative query formulation so it can recover from API errors.