Coordinate HexFlo swarms to manage multi-agent development tasks across adapters and lifecycle actions.
npx skills add https://github.com/gaberger/hex --skill hex-swarm
Please help me install this Agent Skill. Skill: hex-swarm Source: https://github.com/gaberger/hex/tree/main/.claude/skills/hex-swarm Command: npx skills add https://github.com/gaberger/hex --skill hex-swarm
Manage and coordinate multi-agent development tasks using HexFlo swarm orchestration to streamline collaboration across adapters and agents.
Initialize a new HexFlo swarm for a feature by providing a name and topology, then monitor its progress.
High-intent search queries and answers about installing and using this skill.
Multi-agent orchestration coordinates parallel development tasks by initiating a swarm with a defined topology, monitoring agent status via heartbeats, and reconciling task lifecycles across adapters. This centralized approach streamlines collaboration and tracks progress.
Managing a multi-agent swarm lifecycle requires executing defined actions: init to start, monitor to track progress, status to check health, recover to resume operations, and cleanup to retire agents. This structured action set ensures coordinated task reconciliation.
Swarm orchestration is needed when software features span multiple adapters and require parallel agents. It provides topology configuration, heartbeat schemas, and centralized status monitoring to manage the complexity of concurrent development tasks.
To initialize a HexFlo swarm, provide a feature name and topology configuration to spawn agents. Monitor its progress by checking agent status and heartbeat schemas to ensure coordinated task execution across the development lifecycle.
Yes, multi-agent swarm orchestration supports task recovery and cleanup through dedicated lifecycle actions. The recover action resumes stalled operations, while cleanup safely retires agents and reconciles memory schemas after feature completion.
Multi-agent task tracking supports configurable topology options that dictate how parallel agents are structured and spawned. These topologies integrate with heartbeat and memory schemas to provide defined guidance for agent coordination and status monitoring.
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