obul-parallel

Provides web search, extraction, and ML task automation via API endpoints.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates complex web research, content extraction, and entity discovery tasks, providing AI agents with purpose-built APIs to access and process information from the web efficiently.

Core Features & Use Cases

  • Web Search: Perform intelligent web searches to gather information.
  • Content Extraction: Extract specific content from given URLs.
  • Chat Completions: Utilize an OpenAI-compatible chat API for research-oriented conversations.
  • Entity Discovery (FindAll): Discover and extract entities from the web based on defined criteria.
  • Task Execution: Run predefined tasks for data processing.
  • Use Case: An AI agent needs to research the latest trends in renewable energy. It can use the web search and content extraction features to gather articles and reports, then use chat completions to summarize the findings and identify key companies in the sector using FindAll.

Quick Start

Use the obul-parallel skill to search the web for 'latest AI agent developments'.

Frequently Asked Questions about obul-parallel

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

FAQPage Schema
How do I extract specific content from web URLs for AI research?

You can extract specific content from web URLs by using the content extraction APIs to retrieve targeted information from given web pages. This provides AI agents with structured data necessary for subsequent research and summarization tasks.

What is entity discovery and how does it work for web scraping?

Entity discovery, or FindAll, is a web scraping feature that discovers and extracts entities from the web based on defined criteria. It works by querying the web to identify specific data points matching your parameters and returning structured results.

Can I use an OpenAI-compatible chat API to summarize web research?

Yes, you can use an OpenAI-compatible chat completions API to summarize web research. It facilitates research-oriented conversations, allowing AI agents to process extracted web data and generate concise summaries of the findings.

Does this web scraping approach support pay-per-use access for AI agents?

Yes, this approach supports pay-per-use access for AI agents by integrating with the Obul proxy. This integration provides seamless access to web data and AI processing capabilities without requiring upfront bulk payment commitments.

What is the best way to research companies in a specific sector using web data?

The best way to research companies in a specific sector is to combine intelligent web search to gather articles, content extraction for reports, and the FindAll feature to identify key entities. This workflow yields comprehensive structured data about the sector.

When should I not use an AI agent for web research and data extraction?

You should not use an AI agent for web research when you need static, one-time data extraction without task execution capabilities or when your project requires zero proxy dependencies. It is designed for dynamic, automated, pay-per-use web scraping workflows.