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parallel-cli

Execute Parallel CLI web search, extraction, and research jobs with JSON output.

Updated May 14, 2026
Search Tags:#monitoring#web search#data enrichment#deep research#entity discovery#parallel-cli
One-click install
npx skills add https://github.com/SethyPagna/Secretary-Jarvis --skill parallel-cli-sethypagna
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: parallel-cli
Source: https://github.com/SethyPagna/Secretary-Jarvis/tree/main/src/capabilities/optional-skills/research/parallel-cli
Command: npx skills add https://github.com/SethyPagna/Secretary-Jarvis --skill parallel-cli-sethypagna

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Parallel CLI removes the friction of doing web search, page extraction, enrichment, and long-running research from the terminal, especially when you need structured output and repeatable workflows.

Core Features & Use Cases

  • Web Search and Extraction: Quickly retrieve current information from the web and pull clean content from specific URLs.
  • Deep Research Workflows: Launch async research jobs, poll for completion, and chain follow-up questions without losing context.
  • Enrichment, FindAll, and Monitoring: Build datasets from tabular inputs, discover entities at scale, and track sources for ongoing changes.
  • Use Case: A researcher can search for a topic, extract relevant source pages, run a deeper report, and then monitor the most important pages for updates.

Quick Start

Ask the assistant to use parallel-cli to research your topic, return a JSON summary, and include only URLs that came from the tool output.

Frequently Asked Questions about parallel-cli

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

FAQPage Schema
How do I run parallel web searches and extract page content from the terminal?▼

Parallel web searches and URL content extraction are executed through non-interactive, JSON-first commands. This approach retrieves current results and clean page content for agent workflows without manual browser interaction.

What is the best way to automate deep research workflows with async polling?▼

Deep research workflows are automated by launching asynchronous jobs, polling for completion, and chaining follow-up questions. This maintains context throughout the research cycle and returns structured outputs directly.

Can I build datasets from tabular inputs for data enrichment and entity discovery?▼

Data enrichment and entity discovery at scale are supported through specific CLI tasks. You can build structured datasets from tabular inputs and discover entities across one-shot and asynchronous execution jobs.

How do I monitor web sources for ongoing changes after extracting page content?▼

Source monitoring tracks extracted pages for ongoing changes after initial research. It runs as an asynchronous job, polling periodically and returning structured JSON outputs with citation-safe URLs from the CLI.

Do I need to handle authentication separately for CLI research and extraction tasks?▼

Auth handling is required for non-interactive, JSON-first execution of research and extraction tasks. The workflow manages authentication internally to fetch current web search results and structured outputs.

Why use a JSON-first approach for web search and research workflows?▼

A JSON-first approach ensures structured, repeatable outputs for agent workflows. It allows seamless chaining of search, extraction, and deep research tasks while maintaining citation-safe URLs returned by the CLI.

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