ReddRadar
Agent skill
swarm-orchestration
Multi-agent swarm formation and coordinated execution with topology-aware agent deployment, consensus protocols, and anti-drift enforcement.
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/methodologies/ruflo/skills/swarm-orchestration
SKILL.md
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
- Topology Selection - Analyze task and agent pool to select optimal topology
- Agent Assignment - Assign Queen (Strategic/Tactical/Adaptive) and Worker roles
- Consensus Init - Initialize Raft/Byzantine/Gossip/CRDT protocol
- Parallel Execution - Distribute subtasks with shared memory
- Anti-Drift Checkpoints - Validate alignment every N subtasks
- 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 swarmsagents/tactical-queen/- Execution coordination swarmsagents/adaptive-queen/- Real-time optimization swarmsagents/swarm-coordinator/- Topology management
Tool Use
Invoke via babysitter process: methodologies/ruflo/ruflo-swarm-coordination
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