swarm-orchestration

Solid

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

AI & Automation 814 stars 53 forks Updated today MIT

Install

View on GitHub

Quality Score: 93/100

Stars 20%
97
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
78
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# 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 b...

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

Related Skills