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Srajangpt1
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extract-data

Extract structured data from web pages into CSV, JSON, or markdown tables.

Updated Apr 12, 2026
Search Tags:#json#csv#pagination#data-extraction#web-scraping#browser-automation#parallel-processing
One-click install
npx skills add https://github.com/Srajangpt1/dataeye --skill extract-data-srajangpt1
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: extract-data
Source: https://github.com/Srajangpt1/dataeye/tree/main/packages/browseros-agent/apps/server/src/skills/defaults/extract-data
Command: npx skills add https://github.com/Srajangpt1/dataeye --skill extract-data-srajangpt1

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the time-consuming and error-prone task of scraping and structuring repeating data from web pages, ensuring results are saved incrementally, traceable to source URLs, and ready for analysis without exhausting memory.

Core Features & Use Cases

  • Incremental per-page saves: Writes each page's extracted output immediately to disk so large crawls never accumulate in memory.
  • Parallel multi-source extraction: Uses a hidden window with up to 10 concurrent tabs to process batches of URLs efficiently.
  • Pagination and merging: Handles paginated content, merges consistent headers, deduplicates records, and produces merged CSV/JSON/Markdown plus a self-contained HTML report.
  • Use Case: Collect product listings, pricing, contact directories, or table data from search results and export a merged, source-attributed dataset.

Quick Start

Provide the list of URLs or a single page, choose CSV, JSON, or Markdown as the output format, specify the target folder, and run the extract-data workflow to save results and open the generated report.

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 a single CSV or JSON file?▼

You can extract data from paginated web pages by running a workflow that processes paginated content, merges consistent headers, deduplicates records, and outputs a merged CSV or JSON file. It also generates a self-contained HTML report for review.

Can I scrape large product listings without running out of memory?▼

Scraping large product listings is memory-safe because the extraction performs incremental per-page saves. Each page's output is written immediately to disk, preventing large datasets from accumulating in memory and causing crashes.

What is the best way to automate batch data extraction across many URLs?▼

The best way to automate batch data extraction across many URLs is using parallel browser automation with up to 10 hidden tabs. This approach processes batches concurrently, records source URLs for traceability, and handles multi-URL extractions efficiently.

Does web scraping with browser automation support markdown table outputs?▼

Yes, browser automation web scraping supports exporting extracted data into markdown tables alongside CSV and JSON formats. You specify the target output format before running the extraction workflow to generate the desired file type.

How do I handle web scraping for paginated search results and leaderboards?▼

Handling web scraping for paginated search results and leaderboards involves processing paginated views, merging outputs with consistent keys, and deduplicating records. This ensures clean, structured datasets ready for analysis from multi-page sources.

How do I extract table data from web pages and trace it back to source URLs?▼

Extracting table data with source traceability involves recording the source URL for every record during the crawl and generating a self-contained HTML report. This ensures every extracted data point is traceable to its original web page.

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