swarm-orchestration

Multi-agent swarm formation and coordinated execution with topology-aware agent deployment, consensus protocols, and anti-drift enforcement.

509 stars

Best use case

swarm-orchestration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Multi-agent swarm formation and coordinated execution with topology-aware agent deployment, consensus protocols, and anti-drift enforcement.

Teams using swarm-orchestration should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/swarm-orchestration/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/methodologies/ruflo/skills/swarm-orchestration/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/swarm-orchestration/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How swarm-orchestration Compares

Feature / Agentswarm-orchestrationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Multi-agent swarm formation and coordinated execution with topology-aware agent deployment, consensus protocols, and anti-drift enforcement.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Swarm Orchestration

## Overview

Form and coordinate multi-agent swarms with topology-aware deployment. Supports Mesh, Hierarchical, Ring, and Star topologies with automatic selection based on task complexity and agent count.

## When to Use

- Complex tasks requiring multiple specialized agents
- Tasks needing coordinated parallel execution
- When consensus among agents is required for quality
- Projects requiring anti-drift enforcement during execution

## Process

1. **Topology Selection** - Analyze task and agent pool to select optimal topology
2. **Agent Assignment** - Assign Queen (Strategic/Tactical/Adaptive) and Worker roles
3. **Consensus Init** - Initialize Raft/Byzantine/Gossip/CRDT protocol
4. **Parallel Execution** - Distribute subtasks with shared memory
5. **Anti-Drift Checkpoints** - Validate alignment every N subtasks
6. **Consensus Voting** - Weighted voting (Queen=3x) for final decision

## Topologies

- **Mesh**: All-to-all communication, best for small swarms (<8 agents)
- **Hierarchical**: Queen coordinates workers, best for large/structured tasks
- **Ring**: Sequential handoff, best for pipeline/transformation tasks
- **Star**: Central coordinator fan-out, best for independent subtasks

## Agents Used

- `agents/strategic-queen/` - Long-term planning swarms
- `agents/tactical-queen/` - Execution coordination swarms
- `agents/adaptive-queen/` - Real-time optimization swarms
- `agents/swarm-coordinator/` - Topology management

## Tool Use

Invoke via babysitter process: `methodologies/ruflo/ruflo-swarm-coordination`

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