<modeling_standards>
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Zero Formula Errors: Models MUST have zero #REF!, #DIV/0!, or #VALUE! errors.
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Dynamic Logic: You MUST NOT hardcode derived values. You MUST use Excel formulas for all calculations.
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Assumptions: You MUST place all inputs in dedicated assumption cells. </modeling_standards>
<professional_formatting>
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Standards: Specify units in headers ("Revenue ($mm)"). Format zeros as "-".
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Color Coding: The agent SHOULD follow the project's branding skill for color choices. If not defined, the agent SHOULD default to professional standards (e.g., Blue for hardcoded inputs, Black for formulas).
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Visuals: You SHOULD use artifact_tool to render sheets and verify layout. Reference: references/artifact_tool_spreadsheets_api.md . </professional_formatting>
<technical_workflows>
- Data Analysis (Pandas)
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You SHOULD use Pandas for heavy lifting and aggregation.
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You SHOULD convert to Openpyxl for final professional formatting and formula insertion.
- Verification Loop (MANDATORY)
Before delivery, you MUST run the audit script:
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python scripts/recalc.py output.xlsx
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You MUST fix all errors identified in the resulting JSON summary. </technical_workflows>
<citation_logic>
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Citations: You SHOULD cite sources for hardcoded data in cell comments.
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Best Practices: See references/spreadsheet.md for guidance on cross-sheet references and complex formula construction. </citation_logic>
</excel_professional_suite>