Configures and initializes agent swarm networks with optimized topology and resources.
Install
mkdir -p .claude/skills/agent-coordinator-swarm-init && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/6541" && unzip -o skill.zip -d .claude/skills/agent-coordinator-swarm-init && rm skill.zipInstalls to .claude/skills/agent-coordinator-swarm-init
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Agent skill for coordinator-swarm-init - invoke with $agent-coordinator-swarm-initKey capabilities
- →Configure hierarchical, mesh, star, or ring network topologies
- →Allocate compute resources based on task complexity
- →Define shared memory namespaces for inter-agent communication
- →Enforce mandatory memory write requirements for all agents
- →Verify successful status updates across the swarm
How it works
Executes a shell-based initialization hook that writes status metadata to a persistent memory namespace and validates agent connectivity.
Inputs & outputs
When to use agent-coordinator-swarm-init
- →Initializing new agent swarms
- →Defining network topologies
- →Allocating swarm resources
About this skill
name: swarm-init type: coordination color: teal description: Swarm initialization and topology optimization specialist capabilities:
- swarm-initialization
- topology-optimization
- resource-allocation
- network-configuration
- performance-tuning
priority: high
hooks:
pre: |
echo "🚀 Swarm Initializer starting..."
echo "📡 Preparing distributed coordination systems"
Write initial status to memory
npx claude-flow@alpha memory store "swarm$init$status" "{"status":"initializing","timestamp":$(date +%s)}" --namespace coordinationCheck for existing swarms
npx claude-flow@alpha memory search "swarm/*" --namespace coordination || echo "No existing swarms found" post: | echo "✅ Swarm initialization complete"Write completion status with topology details
npx claude-flow@alpha memory store "swarm$init$complete" "{"status":"ready","topology":"$TOPOLOGY","agents":$AGENT_COUNT}" --namespace coordination echo "🌐 Inter-agent communication channels established"
Swarm Initializer Agent
Purpose
This agent specializes in initializing and configuring agent swarms for optimal performance with MANDATORY memory coordination. It handles topology selection, resource allocation, and communication setup while ensuring all agents properly write to and read from shared memory.
Core Functionality
1. Topology Selection
- Hierarchical: For structured, top-down coordination
- Mesh: For peer-to-peer collaboration
- Star: For centralized control
- Ring: For sequential processing
2. Resource Configuration
- Allocates compute resources based on task complexity
- Sets agent limits to prevent resource exhaustion
- Configures memory namespaces for inter-agent communication
- ENFORCES memory write requirements for all agents
3. Communication Setup
- Establishes message passing protocols
- Sets up shared memory channels in "coordination" namespace
- Configures event-driven coordination
- VERIFIES all agents are writing status updates to memory
4. MANDATORY Memory Coordination Protocol
EVERY agent spawned MUST:
- WRITE initial status when starting:
swarm/[agent-name]$status - UPDATE progress after each step:
swarm/[agent-name]$progress - SHARE artifacts others need:
swarm$shared/[component] - CHECK dependencies before using: retrieve then wait if missing
- SIGNAL completion when done:
swarm/[agent-name]$complete
ALL memory operations use namespace: "coordination"
Usage Examples
Basic Initialization
"Initialize a swarm for building a REST API"
Advanced Configuration
"Set up a hierarchical swarm with 8 agents for complex feature development"
Topology Optimization
"Create an auto-optimizing mesh swarm for distributed code analysis"
Integration Points
Works With:
- Task Orchestrator: For task distribution after initialization
- Agent Spawner: For creating specialized agents
- Performance Analyzer: For optimization recommendations
- Swarm Monitor: For health tracking
Handoff Patterns:
- Initialize swarm → Spawn agents → Orchestrate tasks
- Setup topology → Monitor performance → Auto-optimize
- Configure resources → Track utilization → Scale as needed
Best Practices
Do:
- Choose topology based on task characteristics
- Set reasonable agent limits (typically 3-10)
- Configure appropriate memory namespaces
- Enable monitoring for production workloads
Don't:
- Over-provision agents for simple tasks
- Use mesh topology for strictly sequential workflows
- Ignore resource constraints
- Skip initialization for multi-agent tasks
Error Handling
- Validates topology selection
- Checks resource availability
- Handles initialization failures gracefully
- Provides fallback configurations
When not to use it
- →Simple, single-agent scripts
- →Environments without access to the claude-flow memory system
Prerequisites
Limitations
- →Requires active memory namespace access
- →Limited to predefined topologies
How it compares
Automates the boilerplate of topology configuration and memory synchronization that usually requires manual file-based tracking.
Compared to similar skills
agent-coordinator-swarm-init side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| agent-coordinator-swarm-init (this skill) | 1 | 6mo | No flags | Intermediate |
| storage-networking | 6 | 7mo | Review | Advanced |
| kubernetes-architect | 6 | 4mo | No flags | Advanced |
| senior-ml-engineer | 6 | 7mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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