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parallel-cli

Runs vendor-specific web search and extraction workflows with JSON outputs.

2|Updated Mar 26, 2026
Search Tags:#automation#research#cli#json#web-search#enrichment
One-click install
npx skills add https://github.com/CUexter/hermes-agent --skill parallel-cli-cuexter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: parallel-cli
Source: https://github.com/CUexter/hermes-agent/tree/main/skills/research/parallel-cli
Command: npx skills add https://github.com/CUexter/hermes-agent --skill parallel-cli-cuexter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Parallel CLI provides a vendor-specific workflow for web search, extraction, deep research, enrichment, and monitoring with JSON-first outputs that integrate into agent pipelines, enabling robust, structured data collection.

Core Features & Use Cases

  • Vendor-specific web search, extraction, deep research, enrichment, and monitoring workflows.
  • JSON-first outputs for machine-readable results and easy integration into automations.
  • Async long-running tasks with status/poll, context chaining, and multi-step pipelines.

Quick Start

Ask the agent to run a vendor-specific web search and return structured results in JSON for immediate processing.

Frequently Asked Questions about parallel-cli

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

FAQPage Schema
How do I get structured JSON output from automated web search for agent workflows?▼

Automated web search for agent workflows can return structured JSON output by enforcing a JSON-first response format, ensuring machine-readable results for immediate processing in non-interactive pipelines. This enables robust data collection without manual parsing.

Can I run async long-running research tasks and check their status later?▼

Yes, async long-running research tasks are supported through a status and polling mechanism. You can initiate a search or extraction task non-interactively and retrieve its results later, enabling deep research across multiple sources without blocking execution.

How do I enrich extracted web data and chain context across multiple steps?▼

You can enrich extracted web data and chain context using a previous-interaction-id. This allows modular workflows to pass context between search, extract, and enrich steps, building multi-step pipelines for comprehensive research and monitoring.

Does this structured web search tool work without user interaction by default?▼

Yes, this structured web search tool operates in a non-interactive mode by default. It is designed for agent-driven environments, allowing automated extraction and monitoring to run without requiring manual user input during execution.

What is the best way to monitor multiple web sources for changes automatically?▼

Monitoring multiple web sources for changes is handled through dedicated monitor workflows that poll asynchronously and return JSON. This approach provides structured updates suitable for automated tracking and agent-driven data collection pipelines.

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