Anthropic Updated CCAR-F Exam Questions and Answers by cory

Option A corrects the missing tool contract that permits Claude to guess a required parameter. The process_refund description should state its prerequisite explicitly: invoke lookup_order, use only the exact order_id returned by that successful call, and ask for additional identifying information when lookup cannot resolve an order. An input example can demonstrate the correct two-tool sequence.

Anthropic’s tool-definition guidance identifies detailed descriptions as the most important factor in tool performance. Descriptions should explain when a tool should and should not be used, what every parameter means, and all important limitations. The tool-use overview confirms that Claude selects and populates tools based on the request and their descriptions.

Option B forces some tool call but does not tell Claude which tool must run first or where the identifier originates. Option C is an essential defence-in-depth control, but it detects the fabricated value after Claude has already made the incorrect decision. Option D works only when the customer supplies an identifier and does not cover “recent purchase.” Explicit prerequisite and provenance instructions directly prevent the model from inventing the required argument.

MCP prompts are exposed as user-invoked commands rather than autonomous tools or permanently loaded system instructions. Claude Code dynamically discovers prompts from connected MCP servers and displays them in the command list using the naming convention /mcp__servername__promptname .

Arguments are supplied as space-separated values after the command. When executed, the MCP server resolves the prompt and its returned content is injected into the active conversation. Anthropic’s official documentation provides examples such as /mcp__github__list_prs and /mcp__jira__create_issue " Bug in login flow " high . ( https://code.claude.com/docs/en/mcp )

Option A would consume context continuously and incorrectly treat optional workflow templates as mandatory system instructions. Option B confuses MCP prompts with MCP tools: tools are model-callable operations, while prompts are reusable prompt templates invoked as commands. Option C describes MCP resources, which can be referenced and attached but are a distinct MCP capability.

For the stated server, the team could invoke commands such as /mcp__devops__deploy_checklist or /mcp__devops__incident_response service-name . The exact server segment is derived from the configured server name, with normalization applied where necessary.

Official references/topics: MCP Prompts; Dynamic Prompt Discovery; MCP Slash-Command Naming; Prompt Arguments.

Option B follows the Claude Agent SDK’s default context-isolation model. A newly spawned subagent receives a fresh context window and does not automatically inherit the parent’s conversation history or previous tool results. The coordinator must therefore include the information required for synthesis directly in the spawning prompt, preferably using clearly separated structured sections for web findings, document findings, source metadata, conflicts, and unresolved questions.

Anthropic’s official SDK subagent documentation states that the Agent tool’s prompt string is the content passed from the parent to the new subagent. It specifically advises including required file paths, errors, and decisions in that prompt because parent context is not inherited.

Option A could work only if the application had deliberately implemented and authorized such a shared-memory architecture. The question establishes no such mechanism, and reference identifiers alone provide no evidence to the subagent. Option C introduces a callback protocol that is unnecessary for a normal handoff. Option D is incorrect because subagent isolation expressly prevents automatic inheritance. “Complete findings” means the complete evidence needed for synthesis, not every intermediate search trace or irrelevant tool result.

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The error response must explicitly communicate both control semantics and user-facing meaning. Setting " retriable " : false tells the agent that repeating the same operation cannot change the outcome. Providing a customer-friendly explanation allows Claude to respond accurately without exposing internal implementation details or inventing its own interpretation of the business rule.

Anthropic recommends returning failed tool operations with an error indicator and sufficiently informative content so Claude can decide whether to retry, request another input, or explain the limitation. Tool interfaces should provide detailed descriptions and structured parameters rather than forcing Claude to infer operational behavior from ambiguous text. ( https://platform.claude.com/docs/en/agents-and-tools/tool-use/build-a-tool-using-agent?utm_source=chatgpt.com )

Option A appropriately limits automatic retries to technical failures, but it does not solve the stated customer-response problem unless business failures also carry clear semantics. Option B relies on fragile parsing of human-readable messages. Option C adds latency and another tool dependency, and eligibility may still change or fail for reasons not covered by the preliminary check.

A complete schema should identify the error code, category, retryability, customer-safe explanation, and permitted next actions. Technical errors can similarly return " retriable " : true with retry guidance and a maximum-attempt policy.

Official references/topics: Structured tool errors, retryability classification, customer-safe explanations, resilient MCP contracts.