parallel-agents

Orchestrate multi-agent collaboration with shared context and synthesis reports.

8|Updated Feb 4, 2026
One-click install
npx skills add https://github.com/MisonL/Ling --skill parallel-agents-misonl
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: parallel-agents
Source: https://github.com/MisonL/Ling/tree/main/.agents/skills/parallel-agents
Command: npx skills add https://github.com/MisonL/Ling --skill parallel-agents-misonl

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coordinating multiple specialized agents to orchestrate cross-domain tasks that require diverse expertise, enabling structured collaboration and faster outcomes.

Core Features & Use Cases

  • Native multi-agent orchestration for cross-domain tasks.
  • Deterministic sequencing and context sharing among agents.
  • Comprehensive synthesis reports summarizing findings and recommendations. Practical use cases include security reviews, architecture assessments, and end-to-end codebase analyses requiring multiple perspectives.

Quick Start

Run a cross-domain task through parallel-agents to produce a final synthesis report.

Frequently Asked Questions about parallel-agents

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

FAQPage Schema
How do I coordinate multiple AI agents to complete cross-domain tasks?

Multi-agent orchestration coordinates specialized agents to execute cross-domain tasks by applying deterministic sequencing and context sharing. This enables structured collaboration across diverse expertise areas for faster outcomes.

What is the best way to run a security review that requires multiple perspectives?

Run a security review through multi-agent orchestration to coordinate specialized agents analyzing different aspects. It propagates shared context across agents and synthesizes their findings into a comprehensive report.

Can I use multi-agent orchestration for architecture assessments?

Yes, multi-agent orchestration supports architecture assessments by coordinating sequential and parallel agent interactions. Agents share context to evaluate complex systems and produce a final synthesis deliverable with recommendations.

How does context sharing work among multiple agents during complex task automation?

Context sharing propagates intermediate findings and state across agents during complex task automation. Deterministic orchestration logic ensures each agent receives relevant context sequentially or in parallel for accurate synthesis.

When do I need deterministic orchestration logic for agent coordination?

Deterministic orchestration logic is needed for agent coordination when tasks require predictable sequencing, explicit context propagation, and a structured final synthesis report rather than unstructured autonomous agent interactions.