consult

Coordinates simultaneous multi-agent knowledge sharing via a filesystem-based protocol with structured reporting.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/justinmoon/configs --skill consult-justinmoon
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: consult
Source: https://github.com/justinmoon/configs/tree/main/home/skills-disabled/consult
Command: npx skills add https://github.com/justinmoon/configs --skill consult-justinmoon

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill streamlines multi-agent collaboration by enabling efficient knowledge sharing, preventing duplicated efforts on the same tasks.

Core Features & Use Cases

  • Simultaneous Consultation: Agents can consult about a topic and share findings concurrently.
  • Equal Participation: All agents are treated equally, with no single agent dictating the direction.
  • Structured Reporting: Agents post their progress, findings, and next steps in a standardized format.
  • Use Case: When multiple agents are debugging a complex issue, they can use this Skill to share their individual investigations, hypotheses, and code changes, quickly converging on a solution.

Quick Start

Consult about the 'authentication bug' at '/path/to/project' with 3 agents.

Frequently Asked Questions about consult

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

FAQPage Schema
How do I share debugging findings across multiple AI agents to prevent duplicate work?

Multi-agent knowledge sharing is facilitated through a filesystem-based protocol where agents post progress, investigations, and hypotheses to a common path, ensuring a shared understanding and avoiding redundant debugging efforts.

What is the best way to coordinate simultaneous investigations among autonomous agents?

Simultaneous consultation is coordinated by allowing agents to equally participate and report structured findings at a specified path, ensuring no single agent dictates the direction while converging on a solution.

How does filesystem-based multi-agent collaboration work for complex software engineering tasks?

Filesystem-based collaboration works by enabling agents to consult about a topic at a specified path, structuring their reports of progress and next steps to guarantee all agents maintain a common understanding before proceeding.

Can I use this knowledge sharing protocol if my agents have no central orchestrator?

Yes, the protocol supports equal participation by treating all agents equally without a central orchestrator, allowing them to share findings and hypotheses autonomously through the filesystem.

When do I need a structured reporting protocol for multi-agent teamwork?

A structured reporting protocol is needed when multiple agents debug a complex issue concurrently, requiring them to share individual code changes and hypotheses to quickly converge on a solution without duplicated effort.