You are building a multi-agent research system using the Claude Agent SDK.

Option C preserves the information structure that makes each source useful. Financial metrics share comparable fields and therefore benefit from rows, columns, aligned units, and reporting periods. News findings require connected prose to preserve chronology and causal relationships, while patent technology areas are naturally represented as categorized lists. Anthropic’s output-consistency guidance recommends specifying the exact output format needed for the task rather than relying on an unspecified default. Anthropic’s discussion of its multi-agent research system also recognizes specialized output stages for reports, structured data, and visualizations because specialist prompts can produce better results than generic coordinator processing. Option A destroys the comparative structure of numerical data. Option D can provide a useful provenance contract internally but does not determine how the executive briefing should present heterogeneous content. Option B risks creating a lowest-common-denominator representation that discards source-specific advantages. The synthesis contract should preserve normalized facts and provenance internally while directing the report generator to select presentation forms according to the content’s semantic structure and the executive reader’s needs.

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