excel-author

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Build auditable Excel workbooks headless with openpyxl — blue/black/green cell conventions, formulas over hardcodes, named ranges, balance checks, sensitivity tables. Use for financial models, audit outputs, reconciliations.

AI & Automation 191,515 stars 33299 forks Updated today MIT

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Skill Content

# excel-author Produce an .xlsx file on disk using `openpyxl`. Follow the banker-grade conventions below so the model is auditable, flexible, and reviewable by someone other than the person who built it. Adapted from Anthropic's `xlsx-author` and `audit-xls` skills in the [anthropics/financial-services](https://github.com/anthropics/financial-services) repo. The MCP / Office-JS / Cowork-specific branches of the originals are dropped — this skill assumes headless Python. ## Output contract - Write to `./out/<name>.xlsx`. Create `./out/` if it does not exist. - Return the relative path in your final message so downstream tools can pick it up. - One logical model per file. Do not append to an existing workbook unless explicitly asked. ## Setup ```bash pip install "openpyxl>=3.0" ``` ## Core conventions (non-negotiable) ### Blue / black / green cell color - **Blue** (`Font(color="0000FF")`) — hardcoded input a human entered. Revenue drivers, WACC inputs, terminal growth, market data. - **Black** (default) — formula. Every derived cell is a live Excel formula. - **Green** (`Font(color="006100")`) — link to another sheet or external file. A reviewer can then scan the sheet and immediately see what's an assumption vs. what's computed. ### Formulas over hardcodes Every calculation cell MUST be a formula string, never a number computed in Python and pasted as a value. ```python # WRONG — silent bug waiting to happen ws["D20"] = revenue_prior_year * (1 + growth) # CORRECT —...

Details

Author
NousResearch
Repository
NousResearch/hermes-agent
Created
10 months ago
Last Updated
today
Language
Python
License
MIT

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