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