excel-pipeline

Name: excel-pipeline
Availability: InStock
Author: duylamle

Consolidate Excel, CSV, and Markdown sources into a JSONL pipeline and export to Excel.

2|Updated Apr 5, 2026

Search Tags:#audit #formulas #excel #jsonl #data-pipeline #lookup #data-automation

Ready to run

npx skills add https://github.com/duylamle/product-collection --skill excel-pipeline

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: excel-pipeline
Source: https://github.com/duylamle/product-collection/tree/main/skills/excel-pipeline
Command: npx skills add https://github.com/duylamle/product-collection --skill excel-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Excel data often exists in multiple formats and sources, making consolidation, validation, and reporting error-prone and time-consuming.

Core Features & Use Cases

Parse Excel (flat and matrix), CSV, and Markdown tables into a single JSONL stream.
Merge, audit, and diff JSONL records to maintain data quality and traceability.
Export to a formatted Excel workbook with formulas, lookups, highlights, and an issues sheet. Use Case: A data team consolidates quarterly metrics from multiple sources into a reproducible, auditable Excel dashboard.

Quick Start

Say "Parse this dataset into JSONL" to begin the pipeline, then run merge, audit, and export steps to produce a ready-to-share Excel workbook.

Frequently Asked Questions about excel-pipeline

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

FAQPage Schema

How do I consolidate multiple Excel and CSV files into a single dataset?▼

You can consolidate Excel and CSV files by parsing them into a single JSONL stream, then merging and exporting them into a formatted Excel workbook with formulas, lookups, and an issues sheet for auditing.

What is a JSONL data pipeline and when do I need it for Excel reporting?▼

A JSONL data pipeline standardizes multi-source records into a structured stream for reliable merging and auditing. You need it when consolidating varied formats like flat Excel, CSV, or Markdown into a reproducible Excel dashboard.

Can I track data provenance and audit differences when merging Excel sources?▼

Yes, you can track provenance and audit differences. The pipeline includes dedicated audit and diff steps for JSONL records to maintain data quality and traceability before the final Excel export.

Does this data pipeline support Markdown tables and matrix Excel formats?▼

Yes, the data pipeline supports Markdown tables and matrix Excel formats. It parses flat Excel, matrix Excel, CSV, and Markdown sources into a unified JSONL stream for downstream processing.

How do I add formulas and lookups to an exported Excel workbook automatically?▼

You add formulas and lookups automatically during the export step. The pipeline processes the merged JSONL stream to generate a polished Excel workbook with calculations, lookups, and highlights.

Do I need Python and openpyxl to run this Excel export pipeline?▼

Yes, you need Python and the openpyxl library. The pipeline executes parse, merge, audit, and export steps via Python scripts that rely on openpyxl to generate the final formatted Excel workbook.