extract-data

name	extract-data
description	Extract structured data from web pages — tables, lists, product info, pricing — into clean CSV, JSON, or markdown tables. Parallelizes across hidden tabs for multi-source extraction and saves results to disk incrementally. Use when the user asks to scrape, extract, or pull data from a page.
metadata	{"display-name":"Extract Data","enabled":"true","version":"1.0"}

Extract Data

End-to-end data extraction workflow that pulls structured content from one or many web pages, saves results to disk incrementally (never accumulating everything in memory), and delivers clean output in the user's preferred format.

When to Apply

Activate when the user asks to extract, scrape, pull, or collect structured data from web pages — tables, product listings, pricing, contact info, search results, leaderboards, or any repeating data pattern.

Workflow

Phase 1 — Clarify & Plan

1. Clarify the request. Before extracting, confirm with the user:
   • Source(s): Single page, list of URLs, or search-then-extract?
   • Output format: CSV, JSON, or Markdown table? Default to CSV if not specified.
   • Output location: Where to save files. Default: extract-<topic-slug>/ in your working directory.
   • What data to extract: Column names, specific fields, or "everything in the table."
2. Create the output directory. Use evaluate_script to create the target folder:

   extract-<topic-slug>/
   ├── raw/              ← per-page extracted content
   ├── merged.<format>   ← final combined output (csv / json)
   └── extraction.log    ← progress log with source URLs
   

Phase 2 — Single-Page Extraction

For a single page (or each individual page in a batch):

Step	Tool	Detail
Navigate	navigate_page	Go to the target URL (skip if already on the page)
Read content	get_page_content	Extract the page as markdown — this captures tables, lists, and text in a structured format
Identify structure	—	Determine the data pattern: HTML table, repeated cards, key-value pairs, etc.
Extract data	evaluate_script	For complex structures (e.g., product grids, nested cards), run JavaScript to query elements and return a JSON array. For clean markdown tables from get_page_content, parse directly.
Save immediately	evaluate_script	Write the extracted data to raw/<n>-<slug>.<format> with a header comment containing the source URL and timestamp
Log progress	evaluate_script	Append the source URL, row count, and status to extraction.log

Handling Pagination

If the page has pagination (next buttons, page numbers, infinite scroll):

1. Extract the current page's data and save to raw/<n>-page-<p>.<format>
2. Use click or navigate_page to go to the next page
3. Repeat until all pages are processed or a user-specified limit is reached
4. Each page's data is saved to its own file immediately — never accumulate across pages in memory

Phase 3 — Multi-Source Parallel Extraction

When extracting from multiple URLs or sources, parallelize using a hidden window:

Step	Tool	Detail
Create workspace	create_hidden_window	Open a dedicated hidden window for extraction work — keeps the user's browsing undisturbed
Open batch of tabs	new_hidden_page	Open up to 10 tabs concurrently within the hidden window, one per source URL
Extract per tab	navigate_page → get_page_content → evaluate_script	For each tab: navigate, extract content, parse structured data
Save per tab	evaluate_script	Write each tab's results to raw/<n>-<slug>.<format> immediately after extraction
Close tab	close_page	Free the tab after its data is saved
Next batch	—	Once a batch of 10 completes, open the next batch. Continue until all sources are processed.
Close workspace	close_window	Close the hidden window after all extraction is done

Concurrency rule: Never exceed 10 open tabs at a time. Process in batches of 10, saving and closing before opening the next batch.

Phase 4 — Merge & Format

After all raw files are saved:

1. Read each raw file from raw/ using evaluate_script.
2. Merge into a single output file (merged.csv, merged.json, or merged.md) with:
   • Consistent column headers / keys across all sources
   • A source_url column so every row is traceable to its origin
   • Deduplication if the same record appears in multiple sources
3. Write the merged file to the output directory.
4. For large datasets, provide a summary: total rows, sources processed, any errors.

Output Formats

Format	File	Notes
CSV	merged.csv	Header row, comma-separated, properly escaped. Include source_url as the last column.
JSON	merged.json	Array of objects with consistent keys. Each object includes a source_url field.
Markdown	merged.md	Aligned table with headers. Source URL in the last column.

Phase 5 — HTML Report

Generate a self-contained report.html in the output directory that serves as an index for the entire extraction.

Requirement	Detail
Theme	Light background (#ffffff), clean sans-serif typography, generous whitespace
Header	Title, date, total rows extracted, number of sources processed
What was done	Brief description of the extraction: source URLs, data fields extracted, format used
File index	Table listing every file in the output directory (raw/*, merged.*, extraction.log) with file paths as clickable file:// links so the user can open them directly
Data preview	First 20 rows of the merged dataset rendered as an HTML table
Source list	All source URLs as clickable hyperlinks with the row count extracted from each
Self-contained	All styles inline or in a <style> block — no external dependencies
Footer	"Generated by BrowserOS Extract Data" with the current date

Use evaluate_script to write the HTML file to the output directory.

Phase 6 — Open & Notify

Step	Tool	Detail
Open report	new_page	Open file://<path>/report.html so the user sees the extraction summary
Notify user	—	Tell the user: extraction is complete, total rows, source count, and paths to report.html and merged.<format>

Tool Reference

Category	Tools Used
Window management	create_hidden_window, close_window
Tab management	new_hidden_page, close_page, new_page
Navigation	navigate_page
Content extraction	get_page_content
Data parsing & file I/O	evaluate_script
Interaction	click (for pagination)

Tips

• Always ask the format first. CSV, JSON, and Markdown have different strengths — let the user decide.
• Save after every page. Never hold more than one page's worth of data in memory at a time.
• 10 tabs max. More tabs degrades performance and risks timeouts. Batch in groups of 10.
• Record the source URL on every row and in every raw file so data is fully traceable.
• Clean up extracted data: trim whitespace, normalize currency symbols, remove hidden characters.
• For paginated sites, check for a total count or "showing X of Y" to estimate progress.
• If a page requires login or blocks extraction, report it to the user rather than retrying silently.