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.