excel-author

Generate auditable Excel financial models with openpyxl using banker-grade formula and color conventions.

Updated Jun 7, 2026
One-click install
npx skills add https://github.com/Chensihakniroth/ANAKOT-AGENT --skill excel-author-chensihakniroth
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: excel-author
Source: https://github.com/Chensihakniroth/ANAKOT-AGENT/tree/main/optional-skills/finance/excel-author
Command: npx skills add https://github.com/Chensihakniroth/ANAKOT-AGENT --skill excel-author-chensihakniroth

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openpyxl, and includes scripts (resource) components.

What problem does it solve? Building financial models in Excel by hand leads to silent errors: hardcoded values pasted where formulas belong, undocumented assumptions, and no way for a reviewer to audit the work. This Skill produces .xlsx workbooks headless with openpyxl that follow strict banker-grade conventions so every model is auditable, flexible, and reviewable. ## Core Features & Use Cases - Blue/Black/Green Cell Conventions: Hardcoded inputs are blue, live formulas are black, and cross-sheet links are green, so reviewers instantly see assumptions versus calculations. - Formulas Over Hardcodes: Every derived cell is written as a live Excel formula string, with named ranges for cross-sheet references and cell comments documenting the source of every hardcoded input. - Balance Checks & Sensitivity Tables: Includes a Checks tab that ties balance sheets and cash flows with TRUE/FALSE flags, plus properly centered 5x5 or 7x7 sensitivity tables with the base case highlighted. - Use Case: An analyst needs a DCF model for a client deliverable. The Skill writes an Inputs tab with sourced assumptions, a DCF tab of live formulas, a Checks tab validating the model, and a WACC/terminal-growth sensitivity table, then recalculates the workbook with LibreOffice before delivery. ## Quick Start Use the excel-author skill to build a DCF model for a company with FY2024 revenue of 1.25 billion and 12 percent growth, saved to ./out/model.xlsx.

Frequently Asked Questions about excel-author

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create an Excel financial model with openpyxl in Python?▼

Install openpyxl and write formula strings directly into cells rather than computed Python values, so the model flexes when assumptions change. Use named ranges for cross-sheet references and add a Checks tab with TRUE/FALSE validation formulas.

What are the blue black green cell color conventions in financial modeling?▼

Blue font marks hardcoded inputs a human entered, black marks live formulas, and green marks links to other sheets or external files. This lets reviewers instantly distinguish assumptions from calculations when auditing a model.

Why do openpyxl formulas show as None when reading with data_only?▼

openpyxl writes formula strings but never computes them, so data_only reads return None until something calculates the workbook. Recalculate with LibreOffice headless using the included recalc.py script before downstream scripts consume the file.

How do I build a WACC sensitivity table in Excel with Python?▼

Use an odd-sized grid like 5x5 so the center cell equals the base case, with WACC on rows and terminal growth on columns. Populate every cell with a full recalculation formula and highlight the center cell to confirm it matches the base-case valuation.

When should I not use openpyxl for Excel automation?▼

Avoid it when a user has a live Excel session with an Office MCP available, when exporting pure tabular data without formulas where pandas.to_excel is simpler, or when building interactive dashboards better suited to BI tools.