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extract-data

Extract structured data from web pages into CSV, JSON, or Markdown files.

50|37|Updated Oct 8, 2025
Search Tags:#markdown#data#json#parallel#csv#web#extract
One-click install
npx skills add https://github.com/browseros-ai/BrowserOS-agent --skill extract-data-browseros-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: extract-data
Source: https://github.com/browseros-ai/BrowserOS-agent/tree/main/apps/server/src/skills/defaults/extract-data
Command: npx skills add https://github.com/browseros-ai/BrowserOS-agent --skill extract-data-browseros-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually extracting structured data from web pages is time-consuming and error-prone, especially when working across multiple sources and formats.

Core Features & Use Cases

  • End-to-end web data extraction from one or more pages into CSV, JSON, or Markdown tables with incremental saves to disk.
  • Parallel processing across multiple sources using hidden tabs to speed up scraping while preserving data provenance by including source_url in outputs.
  • Output flexibility and traceability: maintain raw per-page files and a merged dataset with consistent schema and optional deduplication.

Quick Start

Extract structured data from one or more web pages and save results incrementally to disk in CSV, JSON, or Markdown formats.

Frequently Asked Questions about extract-data

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

FAQPage Schema
How do I extract structured data from multiple web pages into CSV or JSON?▼

Web data extraction handles repeating patterns like tables and product listings by processing multiple sources in parallel, saving raw per-page files incrementally, and merging them into a deduplicated dataset with source_url tracking.

Can I extract product listings and pricing data from web pages and save as Markdown?▼

Web data extraction supports saving scraped product listings and pricing data as Markdown tables, alongside CSV and JSON formats, with incremental disk writes and optional deduplication.

What is the best way to scrape repeating patterns across multiple sources without losing data provenance?▼

Parallel web extraction across hidden tabs preserves data provenance by automatically appending a source_url field to every row in the merged output dataset, ensuring you can trace extracted records back to their original pages.

Does web data extraction support deduplication when scraping tables from multiple pages?▼

Web data extraction offers optional deduplication when scraping tables from multiple pages, combining results into a merged dataset with a consistent schema while preserving raw per-page files for traceability.

How does parallel processing work when extracting data from multiple web sources?▼

Parallel processing during web extraction uses hidden tabs to scrape multiple sources concurrently, significantly speeding up data collection while merging results into a single traceable dataset with source_url fields.

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