Q4 of 60 — CCA Practice Exam

Multi-Agent Research System

Your multi-agent research system synthesizes findings from 12 legal subagents, each summarizing a different regulatory document. After three weeks in production, legal reviewers flag that 18% of the final reports contain conclusions that are technically accurate but use inconsistent terminology — one section calls the same regulation a "safe harbor provision" while another calls it an "exemption clause," and downstream legal analysis tools reject these reports. Logs confirm each subagent produces clean, accurate output independently. What is the most effective prompt engineering fix for this consistency problem?

A. Add a post-processing validation pass that uses sentiment analysis to detect and flag terminological inconsistencies before the report reaches legal reviewers for final sign-off.

B. Define a shared controlled vocabulary and structural output template in each subagent's system prompt, requiring all summaries to use standardized terminology and a common section schema.

C. Increase the synthesis agent's context window so it can compare all 12 subagent outputs simultaneously and resolve any terminological inconsistencies during the final assembly step.

D. Instruct each subagent to flag terminology it is uncertain about, then route those flags to a human reviewer who normalizes the vocabulary across all 12 summaries before synthesis begins.