| name | structured-extraction |
| description | Extract structured data from web pages using browser snapshot and text tools, then process it into tables, comparisons, or summaries using Python.
|
| requires | {"bins":["agent-browser"]} |
Structured web data extraction skill.
When to activate
Use this skill when you need to:
- Extract specific data points from a web page (prices, features, specs)
- Build a comparison table from multiple pages or sites
- Scrape a list of items from a page (search results, product listings)
- Extract tabular data from a web page into a structured format
Methodology
1. Plan the extraction
Use the think tool to identify:
- What data points to extract (columns in your target table)
- Which pages contain the data (URLs or navigation paths)
- Whether the data is on one page or spread across multiple pages
- Whether pagination or interaction is needed to reveal the data
2. Navigate to the data
Open the target URL and confirm you landed on the right page:
open_url("https://example.com/pricing")
Check the title and URL in the response to verify.
3. Snapshot the page
Take a snapshot to understand the page structure:
snapshot()
Look for:
- Data containers (tables, cards, lists)
- Interactive elements that reveal more data (tabs, accordions,
"Show more" buttons)
- Pagination controls
If the page has distinct sections, use a CSS selector to scope
the snapshot:
