skills.rest
JigsawStack
JigsawStackOFFICIAL
Explore all skills by this author →
GitHub

web-scraping

Extract structured data from web pages into schema-constrained JSON output.

4|Updated Mar 10, 2026
Search Tags:#web scraping#data pipelines#URL parsing#product listings#schema output#structured extraction#price extraction
One-click install
npx skills add https://github.com/JigsawStack/interfaze-skills --skill web-scraping-jigsawstack
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: web-scraping
Source: https://github.com/JigsawStack/interfaze-skills/tree/main/skills/web-scraping
Command: npx skills add https://github.com/JigsawStack/interfaze-skills --skill web-scraping-jigsawstack

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill solves the problem of manually copying and organizing information from specific web pages by extracting it into structured, machine-readable data.

Core Features & Use Cases

  • URL-driven structured extraction: Pull products, listings, prices, profiles, and other structured fields directly from a provided webpage URL.
  • Schema-constrained outputs: Define a Zod (TypeScript) or Pydantic (Python) schema so the result matches the fields you need.
  • Fallback raw scraping mode: Use a scraper task directive to fetch page content in a fixed structure for faster, schema-free extraction.

Use case: Extract all product titles, prices, and URLs from a retail listing page into a typed JSON array suitable for downstream analysis or importing.

Quick Start

Ask it to extract product listings and prices from the URL you provide and return the results in a JSON schema you define.

Frequently Asked Questions about web-scraping

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

FAQPage Schema
How do I extract product listings and prices from a URL into structured data?▼

Web scraping product listings involves supplying a target URL inline and defining an output schema like Zod or Pydantic to capture specific fields such as titles and prices into a typed JSON array.

Can I scrape web pages into structured data without defining a schema?▼

Yes, raw web scraping is possible by using a scraper task directive to fetch page content in a fixed structure, bypassing the need for a Zod or Pydantic schema definition.

Does structured extraction work with Zod and Pydantic schemas?▼

Yes, structured web scraping supports both Zod for TypeScript and Pydantic for Python, constraining the extracted output object to match the exact fields defined in your schema.

What is the best way to scrape user profiles and job postings into a JSON format?▼

The best way to scrape field-based content like user profiles and job postings is to provide the target URL inline and specify a schema-constrained output object, ensuring the extracted data is formatted as structured, machine-readable JSON.

What type of web content can I parse using URL-driven structured extraction?▼

URL-driven structured extraction applies to scraping field-based web content including product listings, prices, user profiles, job postings, and tables, converting them into a schema-constrained output object.

Related Skills

Explore More Data & Analytics Skills→
JigsawStackJigsawStack
4

structured-output

Convert prompts into schema-constrained JSON objects using Zod or Pydantic.

Official
Intermediate
promptrankspromptranks

prk-psv-export

Export validated PSV samples to SQL or JSON for database import.

Official
Intermediate
musingfoxmusingfox
2

Apple Podcasts Fetch

Resolve Apple Podcasts episode audio URLs via HTTP APIs and RSS feeds.

Community
Advanced
ovachieverovachiever
52

guidance

Constrain LLM outputs to valid JSON, XML, and code using regex and grammar constraints.

Community
Advanced