polymer-pay-riveter

Automate web search, scraping, and data extraction through a Polymer Pay proxy.

1|2|Updated Mar 2, 2026
One-click install
npx skills add https://github.com/polymerdao/pay-apis --skill polymer-pay-riveter
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: polymer-pay-riveter
Source: https://github.com/polymerdao/pay-apis/tree/main/skills/polymer-pay-riveter
Command: npx skills add https://github.com/polymerdao/pay-apis --skill polymer-pay-riveter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Riveter automates web search, scraping, and data extraction through the Polymer Pay proxy, delivering structured results to power data-driven decisions.

Core Features & Use Cases

  • Web search and data discovery across multiple domains
  • Page scraping with proxy infrastructure for reliability and privacy
  • Structured output definitions and extraction workflows for multi-page projects

Quick Start

Provide a list of target URLs and an output schema to start a Riveter run.

Frequently Asked Questions about polymer-pay-riveter

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

FAQPage Schema
How do I extract structured data from web pages using a proxy?

Web data extraction through a proxy automates scraping across multiple domains while maintaining privacy. You provide target URLs and an output schema, and the tool returns structured results formatted for downstream processing.

What's the best way to automate batch data gathering for competitive intelligence?

Batch data gathering automation uses a proxy infrastructure to scrape multiple domains reliably. By defining an output schema upfront, you receive structured data suitable for research automation and competitive intelligence workflows.

Do I need an API key to run scraping automation through a proxy?

Yes, scraping automation through the Polymer Pay proxy requires a Polymer Pay API key. This proxy infrastructure provides the reliability and privacy needed to extract structured data across multiple domains.

How does schema-driven web scraping work for multi-page projects?

Schema-driven web scraping works by defining a target output format before extraction begins. You provide a list of URLs and the desired schema, and the tool returns structured data matching that definition for multi-page projects.

Can I use this for research automation across multiple domains?

Yes, research automation across multiple domains is a core use case. The proxy infrastructure handles web search and page scraping, returning structured outputs that power data-driven decisions and downstream processing.

Why use a proxy for web data extraction instead of direct scraping?

Using a proxy for web data extraction ensures reliability and privacy during scraping. It prevents IP blocking across multiple domains, allowing consistent batch data gathering and structured output generation for research automation.