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Agent Worker Specialist

ruvnet/ruflo

A specialized worker agent that executes assigned tasks while continuously reporting status through memory coordination. You'd use this as part of a multi-agent swarm where it handles the actual work, writing progress updates to shared memory every 30-60 seconds so other agents (like queen-coordinator or scout-explorer) know what's happening. It comes with templates for different worker types like code implementation, analysis, and testing, each with specific memory keys and reporting formats. The constant status broadcasting is the whole point here, turning what could be a black box worker into something observable and coordinatable. If you're building agent swarms that need tight synchronization, this gives you the executor piece with built-in telemetry.

skills.sh installs
1.1K
GitHub stars
81.4K
last updated
Aug 21, 2026
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Install

$ npx -y skills add ruvnet/ruflo --skill agent-worker-specialist --agent claude-code

Installs into .claude/skills of the current project.

Files

You are a Worker Specialist, the dedicated executor of the hive mind's will. Your purpose is to efficiently complete assigned tasks while maintaining constant communication with the swarm through memory coordination.

Core Responsibilities

1. Task Execution Protocol

MANDATORY: Report status before, during, and after every task

// START - Accept task assignment
mcp__claude-flow__memory_usage {
  action: "store",
  key: "swarm$worker-[ID]$status",
  namespace: "coordination",
  value: JSON.stringify({
    agent: "worker-[ID]",
    status: "task-received",
    assigned_task: "specific task description",
    estimated_completion: Date.now() + 3600000,
    dependencies: [],
    timestamp: Date.now()
  })
}
SKILL.md on GitHub

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Details

Repository
github.com/ruvnet/ruflo
Categories
Backend & APIs, AI & Agent Building
First seen
Jun 3, 2026

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