agent-coordinator-swarm-init
Skill1 starsChanged 7 months agoMITView on GitHub
Agent skill for coordinator-swarm-init - invoke with $agent-coordinator-swarm-init
5 other projects use a version of this, 5 of them edited.
Adopted by
Most recently taken up by
- ruvnet/rufloedited, first seen Oct 21, 2026
- ruvnet/claude-flowedited, first seen Oct 8, 2026
- Soulcynics404/AgentForgeedited, first seen Aug 24, 2026
- jpoindexter/theft-kitedited, first seen May 20, 2026
- Zekiog/rufloedited, first seen Apr 8, 2026
Other versions5 projects use a version of this.
Word for word · 0
None found.
Edited · 5
- ruvnet/claude-flow★ 80k97% same
- ruvnet/ruflo★ 79k97% same
- Zekiog/ruflo★ 297% same
- jpoindexter/theft-kit★ 197% same
- Soulcynics404/AgentForge★ 197% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository175 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/commands/monitoring/agents.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- v2/CLAUDE.mdCLAUDE.md
- v3/CLAUDE.mdCLAUDE.md
- agent-adaptive-coordinatorSkill
- agent-agentic-paymentsSkill
- agent-agentSkill
- agent-analyze-code-qualitySkill
- agent-app-storeSkill
- agent-architectureSkill
- agent-arch-system-designSkill
- agent-authenticationSkill
- agent-automation-smart-agentSkill
- agent-base-template-generatorSkill
- agent-benchmark-suiteSkill
- agent-byzantine-coordinatorSkill
- agent-challengesSkill
- agent-code-analyzerSkill
- agent-code-goal-plannerSkill
- agent-code-review-swarmSkill
- agent-coderSkill
- agent-collective-intelligence-coordinatorSkill
- agent-consensus-coordinatorSkill
- agent-coordinationSkill
- agent-crdt-synchronizerSkill
- agent-data-ml-modelSkill
- AgentDB Advanced FeaturesSkill
- AgentDB Learning PluginsSkill
- AgentDB Memory PatternsSkill
- AgentDB Performance OptimizationSkill
- AgentDB Vector SearchSkill
- agent-dev-backend-apiSkill
- agent-docs-api-openapiSkill
- agent-github-modesSkill
- agent-github-pr-managerSkill
- agent-goal-plannerSkill
- agent-gossip-coordinatorSkill
- agent-hierarchical-coordinatorSkill
- agentic-jujutsuSkill
- agent-implementer-sparc-coderSkill
- agent-issue-trackerSkill
- agent-load-balancerSkill
- agent-matrix-optimizerSkill
- agent-memory-coordinatorSkill
- agent-mesh-coordinatorSkill
- agent-migration-planSkill
- agent-multi-repo-swarmSkill
- agent-neural-networkSkill
- agent-ops-cicd-githubSkill
- agent-orchestrator-taskSkill
- agent-pagerank-analyzerSkill
- agent-paymentsSkill
- agent-performance-analyzerSkill
- agent-performance-benchmarkerSkill
- agent-performance-monitorSkill
- agent-performance-optimizerSkill
- agent-plannerSkill
- agent-pr-managerSkill
- agent-production-validatorSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
5 rules. 2 are common, 0 are distinctive, and 3 are very specific to this project.
2
Common
Most of the 5 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 60
WRITE initial status: when starting: swarm/[agent-name]$status
- Very specific: line 61
UPDATE progress: after each step: swarm/[agent-name]$progress
- Common: line 63
CHECK dependencies: before using: retrieve then wait if missing
- Very specific: line 64
SIGNAL completion: when done: swarm/[agent-name]$complete
- Common: line 102
Use mesh topology for strictly sequential workflows
“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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 fidgetflo@alpha memory store "swarm$init$status" "{"status":"initializing","timestamp":$(date +%s)}" --namespace coordinationCheck for existing swarms
npx fidgetflo@alpha memory search "swarm/*" --namespace coordination || echo "No existing swarms found" post: | echo "✅ Swarm initialization complete"Write completion status with topology details
npx fidgetflo@alpha memory store "swarm$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
Does it work?
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