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parallel-cli

Search and extract web content with Parallel CLI in JSON output.

3|Updated Apr 4, 2026
Search Tags:#monitoring#web search#deep research#enrichment#entity discovery#web extraction#parallel-cli
One-click install
npx skills add https://github.com/twjarviszyra-web/hermes-unbound --skill parallel-cli-twjarviszyra-web
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: parallel-cli
Source: https://github.com/twjarviszyra-web/hermes-unbound/tree/main/optional-skills/research/parallel-cli
Command: npx skills add https://github.com/twjarviszyra-web/hermes-unbound --skill parallel-cli-twjarviszyra-web

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It removes the friction of doing structured web search, extraction, enrichment, and monitoring from the command line when you need reliable, machine-readable research workflows.

Core Features & Use Cases

  • Search and extraction: Run targeted lookups and pull clean page content for fast fact gathering.
  • Deep research workflows: Launch longer research jobs, poll for completion, and chain follow-up queries for multi-step analysis.
  • Enrichment and discovery: Enrich tabular data, discover entities at scale, and track sources over time with monitoring.
  • Use case: A researcher can investigate a market question, extract supporting pages, enrich a company list, and monitor a source set without leaving the terminal.

Quick Start

Ask the assistant to use parallel-cli to research your topic and return the results in JSON.

Frequently Asked Questions about parallel-cli

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

FAQPage Schema
How do I extract structured web content from the terminal for research workflows?▼

To extract structured web content from the terminal, you can use a command-line interface to run targeted lookups and pull clean page content. This approach returns reliable JSON output for fast fact gathering.

What is the best way to run long-running web intelligence jobs and monitor sources over time?▼

Running long-running web intelligence jobs requires launching research tasks, polling for completion, and reusing job context. This non-interactive execution method enables continuous monitoring and tracks sources over time.

How do I enrich tabular data and discover web entities at scale without leaving the command line?▼

To enrich tabular data and discover web entities at scale via the command line, you launch automated extraction jobs. This process systematically identifies entities and augments your existing datasets with machine-readable JSON.

Does this command-line research method require authenticated access and non-interactive execution?▼

Yes, performing deep research and web extraction from the command line requires authenticated access and non-interactive execution. These prerequisites ensure reliable, automated workflows for launching and polling multi-step research jobs.

Can I chain follow-up queries for multi-step analysis when doing deep research from the terminal?▼

Yes, you can chain follow-up queries for multi-step analysis during deep research workflows. The system supports launching longer research jobs, polling for completion, and reusing job context to build complex intelligence.

When should I not use terminal-based web extraction for my research tasks?▼

Terminal-based web extraction is not suitable when your task requires interactive browsing or does not need machine-readable JSON output. It is designed for structured, non-interactive execution rather than manual web navigation.

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