Build Excel financial models with formulas, scenario analysis, and automated validation.
npx skills add https://github.com/JFrangel/agents --skill xlsx-jfrangel
Please help me install this Agent Skill. Skill: xlsx Source: https://github.com/JFrangel/agents/tree/main/skills/xlsx Command: npx skills add https://github.com/JFrangel/agents --skill xlsx-jfrangel
Excel-based financial modeling often suffers from brittle formulas, inconsistent inputs, and manual edits that lead to errors. This Skill creates robust, auditable spreadsheets by separating inputs, calculations, and outputs, applying professional color-coding, and validating formulas automatically.
Provide input data on the Inputs sheet and run the model builder to generate an error-free, color-coded financial model.
High-intent search queries and answers about installing and using this skill.
Building an error-free Excel financial model involves separating inputs, calculations, and outputs, applying professional color-coding, and running automated validation to detect #REF!, #DIV/0!, and #VALUE! issues.
You can run Monte Carlo simulations in an xlsx spreadsheet to test scenarios. This integrates probabilistic modeling into Revenue, Expenses, and Cash Flow calculations for robust financial forecasting.
Apply color-coding for auditable traceability by using blue for inputs, black for formulas, green for cross-sheet links, and red for errors. This visual separation ensures calculations and balance checks remain verifiable.
Pandas supports reading and writing xlsx files, but building advanced formulas like XNPV, XIRR, and XLOOKUP requires integrating openpyxl. This combination enables deterministic recalculation and scenario analysis.
The best way to automate scenario analysis across .xlsm and .csv formats is to use a recalc-validate workflow. This ensures deterministic recalculation and zero formula errors across all generated outputs.
Excel financial models show #N/A errors after recalculation due to missing cross-sheet links or invalid XLOOKUP queries. Running an automated validation script detects these formula issues before finalizing outputs.
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