Online Access Free CCA-F Practice Test

You are building a multi-agent research system using the Claude Agent SDK. A coordinator agent delegates to specialized subagents: one searches the web, one analyzes documents, one synthesizes findings, and one generates reports. The system researches topics and produces comprehensive, cited reports.
A user is expanding the research system beyond its single web search agent by adding specialized data sources. They add a financial API agent that returns structured JSON with revenue, margins, and growth rates; a news monitoring agent that returns prose summaries of recent developments; and a patent analysis agent that returns structured lists of technology areas. The synthesis agent combines these into executive briefings. Currently, it converts everything to bullet points, causing financial comparisons to lose tabular clarity and news summaries to lose narrative flow. What change would most improve briefing quality?

• A.Standardize all subagent outputs to JSON with fields for claim, evidence, source, and confidence
• B.Standardize all subagent outputs to prose summaries with inline citations
• C.Update the synthesis agent to render each content type appropriately - financial data as tables, news as prose
• D.Add a format conversion layer between subagents and synthesis that transforms all outputs to a common intermediate representation

Your agent is handling a billing dispute. After calling get_customer and lookup_order, it identifies that the dispute involves a promotional pricing error requiring manager approval - beyond the agent's authorization level. How should the workflow handle this mid-process escalation?

• A.Call escalate_to_human passing only the customer's original message.
• B.Persist the complete conversation and tool response history to a database, then call escalate_to_human with a reference ID.
• C.Attempt the refund with process_refund anyway, escalating only if the system rejects the transaction.
• D.Compile a structured handoff with customer details, order info, and the identified issue before calling escalate_to_human.

A prompt asks Claude to produce Markdown tables. Which addition MOST increases consistency?

• A.Omit examples.
• B.Specify exact column names.
• C.Remove formatting instructions.
• D.Increase randomness.

An architect needs Claude to produce structured JSON that downstream software can parse automatically. Which prompting strategy is BEST?

• A.Ask Claude to "respond normally."
• B.Use multiple unrelated examples.
• C.Explicitly specify the required JSON schema and formatting rules.
• D.Increase maximum output tokens only.

Your product search tool queries an external catalog API and returns matching items. In production, you observe the agent frequently retries searches immediately after receiving zero results, treating "no matches found" as a failure requiring retry. The external API returns HTTP 200 with an empty results array - a valid response. How should you restructure the tool's result to help the agent correctly interpret empty result sets?

• A.Return a structured result with a success boolean and results array, reserving isError: true for actual execution failures only.
• B.Return a result object with isError: true and a message explaining no products matched.
• C.Return a natural language string describing the outcome, allowing the agent to interpret the result contextually based on the message content.
• D.Add a suggestions field containing alternative search strategies when results are empty, helping guide the agent toward more productive follow-up queries.