ExcelJS
Read and write Excel files in Node.js. Full support for styles, formulas, images, and streaming.
Best use case
ExcelJS is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Read and write Excel files in Node.js. Full support for styles, formulas, images, and streaming.
Teams using ExcelJS should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/exceljs/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ExcelJS Compares
| Feature / Agent | ExcelJS | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Read and write Excel files in Node.js. Full support for styles, formulas, images, and streaming.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# ExcelJS
Read and write Excel files in Node.js. Full support for styles, formulas, images, and streaming.
## Setup
```bash
# Install ExcelJS for spreadsheet generation and parsing.
npm install exceljs
```
## Creating a Workbook
```typescript
// src/excel/create.ts — Create an Excel workbook with a styled header row and data.
import ExcelJS from "exceljs";
const workbook = new ExcelJS.Workbook();
workbook.creator = "Report System";
workbook.created = new Date();
const sheet = workbook.addWorksheet("Sales Data", {
properties: { tabColor: { argb: "FF3498DB" } },
});
// Define columns
sheet.columns = [
{ header: "Product", key: "product", width: 25 },
{ header: "Revenue", key: "revenue", width: 15 },
{ header: "Units Sold", key: "units", width: 12 },
{ header: "Growth", key: "growth", width: 12 },
];
// Style header row
sheet.getRow(1).font = { bold: true, color: { argb: "FFFFFFFF" } };
sheet.getRow(1).fill = {
type: "pattern",
pattern: "solid",
fgColor: { argb: "FF3498DB" },
};
// Add data
const data = [
{ product: "Widget Pro", revenue: 45000, units: 1200, growth: 0.12 },
{ product: "Gadget Plus", revenue: 32000, units: 800, growth: 0.08 },
{ product: "Tool Basic", revenue: 18000, units: 2400, growth: -0.03 },
];
data.forEach((row) => sheet.addRow(row));
// Format numbers
sheet.getColumn("revenue").numFmt = "$#,##0";
sheet.getColumn("growth").numFmt = "0.0%";
await workbook.xlsx.writeFile("sales-report.xlsx");
```
## Formulas
```typescript
// src/excel/formulas.ts — Add formulas for totals, averages, and derived values.
import ExcelJS from "exceljs";
const workbook = new ExcelJS.Workbook();
const sheet = workbook.addWorksheet("Financials");
sheet.columns = [
{ header: "Item", key: "item", width: 20 },
{ header: "Q1", key: "q1", width: 12 },
{ header: "Q2", key: "q2", width: 12 },
{ header: "Total", key: "total", width: 12 },
];
sheet.addRow({ item: "Revenue", q1: 100000, q2: 120000 });
sheet.addRow({ item: "Expenses", q1: 80000, q2: 85000 });
sheet.addRow({ item: "Profit" });
// Formula references
sheet.getCell("D2").value = { formula: "B2+C2" } as any;
sheet.getCell("D3").value = { formula: "B3+C3" } as any;
sheet.getCell("B4").value = { formula: "B2-B3" } as any;
sheet.getCell("C4").value = { formula: "C2-C3" } as any;
sheet.getCell("D4").value = { formula: "D2-D3" } as any;
await workbook.xlsx.writeFile("financials.xlsx");
```
## Conditional Formatting
```typescript
// src/excel/conditional.ts — Highlight cells based on value thresholds.
import ExcelJS from "exceljs";
const workbook = new ExcelJS.Workbook();
const sheet = workbook.addWorksheet("KPIs");
sheet.columns = [
{ header: "Metric", key: "metric", width: 20 },
{ header: "Value", key: "value", width: 15 },
];
sheet.addRows([
{ metric: "Uptime", value: 99.9 },
{ metric: "Error Rate", value: 2.3 },
{ metric: "Response Time (ms)", value: 450 },
]);
// Green for values above target, red for below
sheet.addConditionalFormatting({
ref: "B2:B4",
rules: [
{
type: "cellIs",
operator: "greaterThan",
formulae: [95],
style: { fill: { type: "pattern", pattern: "solid", bgColor: { argb: "FF27AE60" } } },
priority: 1,
},
],
});
await workbook.xlsx.writeFile("kpis.xlsx");
```
## Reading Excel Files
```typescript
// src/excel/read.ts — Parse an uploaded Excel file and extract data as objects.
import ExcelJS from "exceljs";
export async function parseExcel(filePath: string) {
const workbook = new ExcelJS.Workbook();
await workbook.xlsx.readFile(filePath);
const sheet = workbook.getWorksheet(1)!;
const headers: string[] = [];
const rows: Record<string, any>[] = [];
sheet.eachRow((row, rowNumber) => {
if (rowNumber === 1) {
row.eachCell((cell) => headers.push(String(cell.value)));
} else {
const obj: Record<string, any> = {};
row.eachCell((cell, colNumber) => {
obj[headers[colNumber - 1]] = cell.value;
});
rows.push(obj);
}
});
return rows;
}
```
## Streaming Large Files
```typescript
// src/excel/stream.ts — Write large datasets without holding everything in memory.
// Uses ExcelJS streaming writer for millions of rows.
import ExcelJS from "exceljs";
import fs from "fs";
export async function streamLargeExport(data: AsyncIterable<any[]>, outputPath: string) {
const workbook = new ExcelJS.stream.xlsx.WorkbookWriter({
stream: fs.createWriteStream(outputPath),
useStyles: true,
});
const sheet = workbook.addWorksheet("Data");
sheet.columns = [
{ header: "ID", key: "id", width: 10 },
{ header: "Name", key: "name", width: 30 },
{ header: "Value", key: "value", width: 15 },
];
for await (const batch of data) {
for (const row of batch) {
sheet.addRow(row).commit();
}
}
sheet.commit();
await workbook.commit();
}
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