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swarm-orchestration

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

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a5c-ai/babysitter
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Files included (2)

  • SKILL.md1.8 KB
  • README.md233 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

  • 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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