foxctl-agent-coordination

Name: foxctl-agent-coordination
Availability: InStock
Author: joshka0

Coordinate multi-agent task allocation and data exchange through foxctl rooms.

3|Updated Apr 14, 2026

Search Tags:#task management #workflow orchestration #pipes #multi-agent coordination #room tasks #flow dag #context broadcasting

Ready to run

npx skills add https://github.com/joshka0/foxctl --skill foxctl-agent-coordination

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: foxctl-agent-coordination
Source: https://github.com/joshka0/foxctl/tree/main/configs/skills-pack/foxctl-agent-coordination
Command: npx skills add https://github.com/joshka0/foxctl --skill foxctl-agent-coordination

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Multi-agent development quickly becomes chaotic when agents need to split work, share structured updates, and avoid duplicating effort inside the same room.

Core Features & Use Cases

Room task coordination: Create, claim, complete, block, or abandon shared work items so only one agent executes each task.
Structured agent-to-agent data transfer (pipes): Send payloads to specific agents or broadcast to all participants via consistent pipe subjects.
Multi-step orchestration (flow DAGs): Build and run higher-level pipelines and fan-out workflows for complex coordination across agent roles.

Quick Start

Use the skill to run a claim→execute→report workflow by adding a room task, claiming it when available, and then emitting results to a handoff pipe for the next agent.

Frequently Asked Questions about foxctl-agent-coordination

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

FAQPage Schema

How do I coordinate multiple agents working on the same task backlog?▼

Multi-agent coordination requires structured task allocation using shared room tasks, allowing agents to claim pending items, execute them, and transition states to completed or blocked to prevent duplicated effort.

How do agents share structured data and findings during multi-agent workflows?▼

Agents share structured data by emitting and consuming pipe messages, sending targeted payloads to specific agents or broadcasting context to all participants via consistent pipe subjects for durable data exchange.

Can I build multi-stage pipelines for complex agent orchestration?▼

Yes, you can build multi-stage pipelines using flow DAGs to orchestrate complex coordination across agent roles, enabling higher-level fan-out workflows and structured handoffs for distributed development tasks.

What is the task lifecycle state model for shared room tasks?▼

Shared room tasks follow a structured lifecycle state model with pending, claimed, completed, blocked, and abandoned states, ensuring only one agent executes each task and tracking progress across the coordination workflow.

What's the best way to start a claim execute report workflow across agents?▼

Start a claim execute report workflow by creating a room task, claiming it when available, executing the work, and emitting results to a handoff pipe for the next agent to consume and continue the pipeline.

When do I need flow DAGs for multi-agent coordination instead of simple pipes?▼

Flow DAGs are needed when multi-agent coordination requires complex multi-stage orchestration with fan-out graphs, rather than simple point-to-point pipe data exchange between individual agents.