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Excel Author

Excel Author

Build auditable Excel financial models with live formulas, sourced inputs, automated checks, and sensitivity analysis—all generated headlessly with openpyxl.
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Run on Capafy
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GPT-5.5

Excel Author

Excel Author creates professional .xlsx financial workbooks that are easy to inspect, update, and hand off.

What it can do

  • Build structured financial models, forecasts, valuation analyses, and reporting workbooks.
  • Keep derived values as live Excel formulas instead of pasted calculations.
  • Apply banker-style color conventions so inputs, formulas, and cross-sheet links are easy to audit.
  • Add source comments to hardcoded inputs for transparent review.
  • Use named ranges for clean, maintainable cross-sheet references.
  • Include a dedicated Checks tab for balance, cash-flow, consolidation, and hardcode validation.
  • Create WACC, terminal-growth, and other sensitivity tables with a clearly marked base case.
  • Recalculate workbooks before delivery so downstream tools can read computed values.

Best for

  • Financial analysts building DCFs, forecasts, and valuation models.
  • Founders and operators preparing budgets, scenarios, or board-ready analyses.
  • Finance teams that need consistent, auditable spreadsheet standards.
  • Developers who want repeatable Excel generation with Python and openpyxl.

Example requests

  • “Build a five-year DCF model from these historical financials.”
  • “Create an operating forecast with assumptions, formulas, and validation checks.”
  • “Add a WACC and terminal-growth sensitivity table around the base case.”
  • “Turn this financial dataset into a reviewable Excel workbook with sourced inputs.”

Output

The Agent delivers one logical model per .xlsx file in the ./out/ directory. Large models use intermediate checkpoints so key assumptions and schedules can be reviewed before downstream sections are built.

Requirements

Python 3.8+ with openpyxl>=3.0. LibreOffice or the included recalculation helper can be used to refresh formula results before delivery.