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CCA-F Practice Questions — Page 1

Question 1

Open question ↗

Scenario: Multi-agent Research System

A document analysis agent discovers that two credible sources contain directly contradictory statistics for a key metric: a government report states 40% growth, while an industry analysis states 12%. Both sources look credible, and the discrepancy could materially affect the research conclusions. How should the document analysis agent handle this situation most effectively?

Which approach is most effective?

  • A.Apply credibility heuristics to pick the most likely correct number, finish analysis with that value, and add a footnote mentioning the discrepancy.
  • B.Include both numbers in the analysis output without marking them as conflicting, letting the synthesis agent decide which to use based on broader context.
  • C.Stop analysis and immediately escalate to the coordinator, asking it to decide which source is more authoritative before continuing.
  • D.Complete analysis with both numbers, explicitly annotate the conflict with source attribution, and let the coordinator decide how to reconcile the data before passing to synthesis.

Question 2

Open question ↗

Scenario: Multi-agent Research System

The web-search and document-analysis agents have completed their tasks and returned results to the coordinator. What is the next step for creating an integrated research report?

Which next step is most appropriate?

  • A.Each agent sends its results directly to the report-writing agent, bypassing the coordinator.
  • B.The document analysis agent requests web-search results and merges them internally.
  • C.The coordinator passes both sets of results to the synthesis agent for a unified integration.
  • D.The coordinator concatenates the raw outputs from both agents and returns them as the final result.

Question 3

Open question ↗

Scenario: Multi-agent Research System

A document analysis subagent frequently fails when processing PDF files: some have corrupted sections that trigger parsing exceptions, others are password-protected, and sometimes the parsing library hangs on large files. Currently, any exception immediately terminates the subagent and returns an error to the coordinator, which must decide whether to retry, skip, or fail the whole task. This causes excessive coordinator involvement in routine error handling. What architectural improvement is most effective?

Which improvement is most effective?

  • A.Create a dedicated error-handling agent that monitors all failures via a shared queue and decides recovery actions, sending restart commands directly to subagents.
  • B.Configure the subagent to always return partial results with a success status, embedding error details in metadata; the coordinator treats all responses as successful.
  • C.Make the coordinator validate all documents before sending them to the subagent, rejecting documents that might cause failures.
  • D.Implement local recovery in the subagent for transient failures and escalate to the coordinator only errors it cannot resolve, including attempted steps and partial results.

Question 4

Open question ↗

Scenario: Multi-agent Research System

After running the system on “AI impact on creative industries,” you observe that every subagent completes successfully: the web-search agent finds relevant articles, the document analysis agent summarizes them correctly, and the synthesis agent produces coherent text. However, final reports cover only visual art and completely miss music, literature, and film. In the coordinator logs, you see it decomposed the topic into three subtasks: “AI in digital art,” “AI in graphic design,” and “AI in photography.” What is the most likely root cause?

What is the most likely root cause?

  • A.The synthesis agent lacks instructions to detect coverage gaps.
  • B.The document analysis agent filters out non-visual sources due to overly strict relevance criteria.
  • C.The coordinator’s task decomposition is too narrow, assigning subagents work that does not cover all relevant areas.
  • D.The web-search agent’s queries are insufficient and should be broadened to cover more sectors.

Question 5

Open question ↗

Scenario: Multi-agent Research System

The web-search subagent returns results for only 3 of 5 requested source categories (competitor sites and industry reports succeed, but news archives and social feeds time out). The document analysis subagent successfully processes all provided documents. The synthesis subagent must produce a summary from mixed-quality upstream inputs. Which error-propagation strategy is most effective?

Which error-propagation strategy is most effective?

  • A.Continue synthesis using only successful sources and produce an output without mentioning which data was unavailable.
  • B.The synthesis subagent returns an error to the coordinator, triggering a full retry or task failure due to incomplete data.
  • C.The synthesis subagent asks the coordinator to retry timed-out sources with a longer timeout before starting synthesis.
  • D.Structure the synthesis output with coverage annotations that indicate which conclusions are well-supported and where gaps exist due to unavailable sources.

Question 6

Open question ↗

Scenario: Multi-agent Research System

The document analysis subagent encounters a corrupted PDF file that it cannot parse. When designing the system’s error handling, what is the most effective way to handle this failure?

Which approach is most effective?

  • A.Return an error with context to the coordinator agent, allowing it to decide how to proceed.
  • B.Silently skip the corrupted document and continue processing the remaining files to avoid interrupting the workflow.
  • C.Automatically retry parsing the document three times with exponential backoff before reporting a failure.
  • D.Throw an exception that terminates the entire research workflow.

Question 7

Open question ↗

Scenario: Multi-agent Research System

Production logs show a persistent pattern: requests like “analyze the uploaded quarterly report” are routed to the web-search agent 45% of the time instead of the document analysis agent. Reviewing tool definitions, you find that the web-search agent has a tool `analyze_content` described as “analyzes content and extracts key information,” while the document analysis agent has a tool `analyze_document` described as “analyzes documents and extracts key information.” How should you fix the misrouting problem?

How should you fix the misrouting problem?

  • A.Add a pre-routing classifier that detects whether the user refers to uploaded files or web content before the coordinator decides on delegation.
  • B.Rename the web-search tool to `extract_web_results` and update its description to “processes and returns information retrieved from web search and URLs.”
  • C.Add few-shot examples to the coordinator prompt showing correct routing: “User uploads a quarterly report → document analysis agent” and “User asks about a web page → web-search agent.”
  • D.Expand the document analysis tool description with usage examples like “Use for uploaded PDFs, Word docs, and spreadsheets,” leaving the web-search tool unchanged.

Question 8

Open question ↗

Scenario: Multi-agent Research System

A colleague proposes that the document analysis agent should send its results directly to the synthesis agent, bypassing the coordinator. What is the main advantage of keeping the coordinator as the central hub for all communication between subagents?

What is the main advantage of keeping the coordinator as the central hub?

  • A.The coordinator can observe all interactions, handle errors uniformly, and decide what information each subagent should receive.
  • B.The coordinator batches multiple requests to subagents, reducing total API calls and overall latency.
  • C.Routing through the coordinator enables automatic retry logic that direct inter-agent calls cannot support.
  • D.Subagents use isolated memory, and direct communication would require complex serialization that only the coordinator can perform.

Question 9

Open question ↗

Scenario: Multi-agent Research System

The web-search subagent times out while researching a complex topic. You need to design how information about this failure is returned to the coordinator. Which error-propagation approach best enables intelligent recovery?

Which error-propagation approach best enables intelligent recovery?

  • A.Return structured error context to the coordinator including the failure type, the query executed, any partial results, and potential alternative approaches.
  • B.Catch the timeout within the subagent and return an empty result set marked as successful.
  • C.Implement automatic exponential-backoff retries inside the subagent, only returning a generic “search unavailable” status after exhausting retries.
  • D.Propagate the timeout exception directly to the top-level handler, terminating the entire research workflow.

Question 10

Open question ↗

Scenario: Multi-agent Research System

In your system design, you gave the document analysis agent access to a general-purpose tool `fetch_url` so it could download documents by URL. Production logs show this agent now frequently downloads search engine results pages to perform ad hoc web search—behavior that should be routed through the web-search agent—causing inconsistent results. Which fix is most effective?

Which fix is most effective?

  • A.Replace `fetch_url` with a `load_document` tool that validates that URLs point to document formats.
  • B.Remove `fetch_url` from the document analysis agent and route all URL fetching through the coordinator to the web-search agent.
  • C.Implement filtering that blocks `fetch_url` calls to known search engine domains while allowing other URLs.
  • D.Add instructions to the document analysis agent prompt that `fetch_url` should only be used to download document URLs, not to search.