CCAR-F Multiple Select — 50 Questions

Question 1

An architect is defining a 'System Prompt' for a legal analysis tool. Which TWO practices are considered best for ensuring the model maintains a reliable persona and adheres to safety constraints throughout a long conversation?

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

Accepted Answer

Using XML tags like and within the system prompt. The system prompt is the most powerful way to define Claude's behavior. By clearly stating the persona and using XML tags within the system prompt to separate different types of instructions (like tone vs. constraints), architects can create a more stable and reliable foundation for the model's performance over long sessions.

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Repeating the system prompt in every user message for emphasis

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Restricting the system prompt to under 50 tokens for better focus

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Using the system prompt to provide the user's specific query

Question 2

An organization is transitioning from individual, hard-coded tool integrations to a Model Context Protocol (MCP) architecture. Which TWO benefits will they most likely realize from this change?

Accepted Answer

Improved interoperability, allowing the same tool server to be used across different host applications.. Transitioning to MCP offers significant architectural advantages over traditional custom tool implementations. It standardizes how models interact with external data and services, promoting modularity and reducing the maintenance burden. Architects must understand these benefits to justify the adoption of MCP in complex enterprise environments involving multiple data sources.

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Reduced latency for all model inferences by bypassing the need for JSON schema validation.

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Automatic translation of model outputs into multiple programming languages for direct execution.

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Elimination of the need for API keys or authentication when connecting to external web services.

Question 3

A financial services firm is using Claude 3.5 Sonnet to analyze quarterly earnings reports that exceed 150,000 tokens. Which TWO strategies are most effective for maintaining high reliability when the model must extract specific data points from the middle of this large context?

Accepted Answer

Encapsulating documents in XML tags like and . Long-context models like Claude 3.5 Sonnet are highly capable, but performance can still vary based on data placement. Using XML tags helps the model distinguish between different sections of the input, while placing the specific question or 'call to action' at the very end of the prompt ensures the model focuses on the task after processing all context.

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Using markdown headers exclusively for sectioning

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Placing the user query at the beginning of the prompt

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Disabling the system prompt to save token space

Question 4

A developer is building a structured output pipeline where Claude must return a list of support tickets, each with 'id', 'priority', and 'category'. The pipeline must be robust against malformed responses. Which TWO practices most directly improve the reliability of this structured output? (Choose two.)

Accepted Answer

Validate the parsed output against the schema in application code and retry with a corrective prompt on failure.. Reliability comes from structural enforcement plus defensive validation. Defining a tool 'input_schema' with required ticket fields and forcing tool use guarantees a structured tool call, while validating the parsed result in application code and retrying with corrective feedback handles residual edge cases. Together they make the pipeline robust against malformed or invalid responses.

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Set 'temperature' to 1.0 to encourage diverse ticket categorizations.

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Ask Claude to 'be careful' and 'double-check' the output before responding.

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Append a stop sequence of '}' to end the response as soon as the JSON closes.

Question 5

You are building a document-processing pipeline with the Anthropic Messages API. Claude must extract a fixed set of fields from each document and return them as JSON. In production, you observe two problems: (1) some responses include explanatory prose before the JSON, and (2) some responses omit required fields when the document is ambiguous. You need to make the pipeline more reliable. (Choose two.)

Accepted Answer

Prefill the assistant turn with `{` to force the response to begin as a JSON object.. The two problems are a formatting issue and a completeness issue. Prefilling the assistant turn with `{` structurally prevents prose before the JSON, and specifying required fields with a null fallback ensures keys are always present even when the document is ambiguous. Raising max_tokens, lowering temperature, or adding a stop sequence do not enforce format or completeness and can even truncate valid output.

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Add a stop sequence of '

' so Claude stops as soon as it finishes the JSON object.

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Set `temperature` to 0 to make the output deterministic and therefore always complete.

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Increase `max_tokens` to the model's maximum so the response has room for all fields.

Question 6

Which THREE strategies are effective for reducing hallucinations in RAG (Retrieval-Augmented Generation) systems?

Accepted Answer

Instruct the model to say 'I don't know' if the context does not contain the answer.. To reduce hallucinations in RAG, you must constrain the model to the provided context, encourage it to admit ignorance if the answer is missing, and verify its reasoning. These techniques transform the model from a creative writer into a grounded processor of provided facts. Architects must build these guardrails into the prompt to ensure the output is factually tethered to the retrieved source material, which is critical for trustworthy systems.

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Increase the temperature to 1.5 to allow for more creative exploration.

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Use a complex system prompt that describes the model as an 'Omniscient Expert'.

Question 7

An architect is optimizing a multi-agent system for a legal firm. The system uses a 'Router' agent followed by several 'Specialist' agents. Which THREE techniques will most effectively minimize latency in this specific architecture?

Accepted Answer

Implement prompt caching for the specialist agents' long system prompts. Latency is a primary concern in multi-agent systems due to the sequential nature of LLM calls. Prompt caching significantly reduces time-to-first-token for large system instructions, while selecting faster models like Claude 3.5 Haiku for routing tasks and executing independent specialist tasks in parallel ensures the overall workflow remains responsive and efficient for the end-user.

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Set 'max_tokens' to 1 for the specialist agents' responses

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Force the model to use the 'computer_20241022' beta tool for all lookups

Question 8

You are designing a code-migration assistant that converts legacy COBOL modules to a modern language. Stakeholders require high reliability and verifiable output. Which TWO architectural practices best support this requirement? (Choose two.)

Accepted Answer

Add an automated test harness that compiles and executes the generated code against representative legacy inputs and compares outputs.. Verifiable migration needs machine-checkable artifacts and empirical proof of behavior. A fixed schema plus structured report makes each response auditable, while a compile-and-execute harness compares generated behavior against known legacy outputs. Together they catch both structural and semantic defects. Creativity, monolithic responses, and silent omission of edge cases all reduce verifiability rather than strengthen it.

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Request the entire migration in a single response to preserve the model's global understanding of the module.

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Maximize the model's creativity by raising temperature so it can find novel modernization opportunities.

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Allow the model to omit edge-case handling when the legacy code is ambiguous, to keep outputs concise.

Question 9

An architect is standardizing Claude Code usage across a large engineering organization. They want to ensure that every developer's sessions automatically inherit a curated set of project conventions and that destructive shell commands are blocked unless explicitly approved. Which TWO configurations should the architect implement? (Choose two.)

Accepted Answer

Commit a CLAUDE.md file at the repository root containing the shared coding conventions and architectural notes. A committed CLAUDE.md at the repository root distributes shared conventions automatically to every session, and deny rules in the project's .claude/settings.json enforce hard blocks on destructive commands organization-wide. Manual per-developer setup and README-based expectations lack reliability and auditability, while blanket Bash auto-approval undermines the safety objective.

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Instruct each developer to run /config and manually set the desired conventions on first launch

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Enable auto-approval for all Bash commands to reduce interruptions during long sessions

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Place convention notes in a README.md and expect Claude to infer them from repository files

Question 10

An architect is designing an MCP server that exposes tools for a customer relationship management (CRM) system. The tools include 'get_customer', 'update_customer', and 'delete_customer'. The architect wants to ensure that tool invocations are properly authorized and audited. Which two design elements should be included in the MCP server implementation? (Choose two.)

Accepted Answer

Validate the caller's OAuth 2.0 access token on every tool invocation before executing the operation.. The two correct elements are validating the caller's OAuth 2.0 access token on every invocation and logging full tool inputs/outputs with authenticated user ID and timestamp. Together they enforce authorization at the server and provide an audit trail. Token validation ensures only authorized callers can execute tools, while logging enables traceability and detection of misuse.

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Rely on the model's system prompt to instruct it to only call tools when the user is authorized.

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Embed the caller's identity and permissions in the tool input schema as required parameters.

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Store a static API key in the MCP server configuration and use it for all tool calls regardless of caller.

Question 11

An architect is designing a Claude-based contract review tool. Because contract clauses are long and interdependent, the team plans to use extended thinking to improve reasoning quality. Which TWO practices should the architect follow to use this capability correctly? (Choose two.)

Accepted Answer

Allocate a thinking budget that scales with task complexity and leave sufficient max_tokens for the final answer.. Extended thinking requires sizing the thinking budget to task complexity while preserving room for the final answer, and it requires not recycling prior thinking blocks into later turns. Together these keep reasoning thorough, cost proportionate, and multi-turn dialogues clean. Exposing thinking traces, maxing budgets unconditionally, and returning only thinking output all misuse the capability.

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Disable the final answer and return only the thinking output as the contract review result.

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Set the thinking budget to the maximum on every request to guarantee the best possible clause analysis.

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Expose the raw thinking blocks to end users so they can audit the model's reasoning trace.

Question 12

An architect is reviewing an MCP server's tool catalog before release. The team wants to reduce the chance that Claude selects the wrong tool when several tools have overlapping purposes, and to make failures easier to diagnose. Which two changes best support those goals? (Choose two.)

Accepted Answer

Return errors from tools as structured objects with a stable code and a human-readable message.. Tool selection quality comes from clear, distinct names and descriptions, while diagnosis quality comes from structured, coded errors. Together they reduce wrong-tool calls and make remaining failures easy to trace. Merging tools, expanding the catalog, or relying on implicit reasoning all move in the wrong direction for these two goals.

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Merge all overlapping tools into one function with a `mode` parameter that selects behavior internally.

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Rely on the model's general reasoning to disambiguate similar tools without changing names or descriptions.

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Increase the number of tools in the catalog so the model has a fallback for every conceivable case.

Question 13

You are designing a long-running analytical assistant that must operate over a corpus far larger than any single context window, spanning many sessions. Which TWO architectural practices best preserve reliability across sessions? (Choose two.)

Accepted Answer

Persist a structured, curated summary of prior findings and decisions externally, and re-inject only the relevant portions at the start of each new session.. Durable long-horizon assistants need two complementary mechanisms: an external store of curated findings that carries decisions forward without unbounded prompt growth, and a retrieval index that surfaces only the corpus passages relevant to the current question. Together they keep every request within the context window while preserving continuity and grounding, whereas implicit memory, verbatim accumulation, and higher temperature each fail a core requirement.

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Append every prior session transcript verbatim to each new request so nothing is ever lost.

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Increase the temperature so the assistant explores a broader range of interpretations across sessions.

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Rely on the model to recall earlier sessions implicitly, since Claude retains state between separate API calls.

Question 14

A document-processing agent extracts structured fields from scanned contracts and must return a JSON object matching a strict schema. The agent also calls an OCR tool when text is unreadable. Which TWO design choices best ensure reliable, schema-valid output? (Choose two.)

Accepted Answer

Validate the tool input against the JSON Schema in the orchestrator and return a corrective `tool_result` when validation fails.. Reliability comes from constraining generation and validating the result. A tool whose input schema matches the target structure forces the model to produce conforming arguments, and orchestrator-side JSON Schema validation with corrective `tool_result` feedback lets the agent fix violations in-loop. Together they replace free-form guessing with a validated, self-correcting extraction step.

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Ask the agent to output the JSON twice and compare the two strings for equality.

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Set the model temperature to its maximum so the agent explores multiple extraction interpretations.

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Remove the OCR tool so the agent relies solely on the model's vision capability.

Question 15

A team is configuring Claude Code for a new project. They want to enforce specific tool permissions to prevent Claude Code from executing potentially dangerous shell commands without approval. Which two configuration approaches should they use? (Choose two.)

Accepted Answer

Define allowed and disallowed tools in the project's .claude/settings.json file.. Tool permissions in Claude Code are configured via settings.json files, either at the project level (.claude/settings.json) or user level (~/.claude/settings.json). Project settings allow team-wide enforcement and can be version-controlled. Global settings provide a fallback but are user-specific. Together, they can restrict tools like shell execution. Interactive commands and environment variables are not persistent configuration methods.

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Add a .claudeignore file listing tools to exclude.

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Set the CLAUDE_TOOL_POLICY environment variable to 'restricted'.

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Use the /permissions command during a session to interactively adjust tool access.

Question 16

You are architecting a system that uses Claude to answer legal questions based on a corpus of case law. To maximize reliability and minimize hallucinations, which TWO practices should you implement? (Choose two.)

Accepted Answer

Implement a retrieval-augmented generation (RAG) pipeline that fetches relevant case law excerpts and includes them in the prompt.. The two most effective practices are using a system prompt that constrains Claude to provided excerpts and requires citations, and implementing a RAG pipeline to supply relevant case law. Together, they ensure the model's answers are grounded in actual sources, reducing hallucinations. Other options like high temperature or fine-tuning do not directly address grounding.

Answer

Ask Claude to generate a confidence score for each answer.

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Fine-tune Claude on the entire corpus of case law.

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Set the temperature to 1.0 to encourage diverse legal interpretations.

Question 17

A platform team ships a Claude-based service that classifies incoming tickets into one of eight categories and returns a JSON object with category and confidence. In production they observe two failure modes: the model sometimes returns a category outside the eight allowed values, and occasionally returns confidence as the string "high" instead of a number. Which TWO changes most directly reduce these failures while keeping the pipeline automated? (Choose two.)

Accepted Answer

Add a validation step that parses the JSON, checks category against the allowed list and confidence against a numeric range, and re-prompts with the specific error when either check fails.. Schema-constrained tool input directly prevents out-of-set categories and non-numeric confidence by enumerating and typing the fields, while a validating re-prompt loop catches any residual drift and feeds the exact error back for correction. Together they address both failure modes structurally. Sampling and length parameters do not constrain vocabulary or type, and unverified prose instructions are too weak for production.

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Ask the model in the prompt to 'be careful and always use one of the eight categories', and trust the instruction without further checks.

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

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Raise the temperature to 0.7 so the model explores more phrasing and is less likely to repeat a bad category.

Question 18

An architect is reviewing an MCP server that exposes a tool to create support tickets. The tool currently returns a plain text confirmation. The architect wants to improve how the model and client application consume the result. Which two changes should the architect make? (Choose two.)

Accepted Answer

Return a structured JSON object containing the ticket ID, status, and canonical URL, and declare an output schema for the tool.. Tool results should be structured so the model can reference precise fields and the client can act on them, and an output schema makes that contract explicit. Pairing machine-readable fields with a concise summary field gives the model a safe phrase to relay to the user. Together these changes improve reliability, reduce token waste, and support downstream automation.

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Return the result as a Markdown table embedded in a text block so it renders nicely in chat clients.

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Add a boolean success field and omit all other data to keep the response as small as possible.

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Return the full HTTP response from the ticketing backend, including headers and trace IDs, so the model has maximum information.

Question 19

A platform team is building a Claude-powered service that returns structured records to a downstream database. During testing, roughly 4% of responses include a friendly sentence before the JSON, and another 3% omit a required field entirely. Which TWO changes most directly reduce these failure modes? (Choose two.)

Accepted Answer

List every required field with its type and a short description, and instruct the model to include all fields even when a value is unknown.. The two observed defects have distinct causes: conversational framing produces leading sentences, and unstated field requirements produce omissions. An instruction forbidding any text outside the JSON object fixes the first, while enumerating every field with its type and a rule for unknown values fixes the second. Token budget, temperature, and format changes do not target either root cause and would leave both failure rates essentially unchanged.

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Switch the output format from JSON to a comma-separated list to simplify parsing.

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Lower the temperature to 0 and rely on that alone to eliminate both the preamble and the missing fields.

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Increase max_tokens substantially so the model has room to complete every field.

Question 20

An architect is hardening an agent that uses tools to read internal wikis and send Slack messages. Which TWO practices most directly reduce the risk that untrusted wiki content causes the agent to take unauthorized actions? (Choose two.)

Accepted Answer

Wrap retrieved wiki content in a clearly delimited block and instruct the model in the system prompt to treat that block as data, never as instructions.. Two complementary controls break indirect prompt injection: treating retrieved content strictly as data via delimiters and system-prompt framing, and inserting a human approval gate before irreversible actions that were influenced by that content. Together they reduce both the chance of manipulation and the blast radius if manipulation occurs.

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Raise the model's temperature so the agent explores alternative interpretations of the wiki text.

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Give the agent a single credential with read access to wikis and write access to Slack so it can complete tasks without switching identities.

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Rely on the wiki's own content moderation to strip malicious instructions before retrieval.