swarm-orchestration

Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.

25 stars

Best use case

swarm-orchestration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.

Teams using swarm-orchestration should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/swarm-orchestration/SKILL.md --create-dirs "https://raw.githubusercontent.com/ComeOnOliver/skillshub/main/skills/aiskillstore/marketplace/dnyoussef/swarm-orchestration/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/swarm-orchestration/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How swarm-orchestration Compares

Feature / Agentswarm-orchestrationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Swarm Orchestration

## What This Skill Does

Orchestrates multi-agent swarms using agentic-flow's advanced coordination system. Supports mesh, hierarchical, and adaptive topologies with automatic task distribution, load balancing, and fault tolerance.

## Prerequisites

- agentic-flow v1.5.11+
- Node.js 18+
- Understanding of distributed systems (helpful)

## Quick Start

```bash
# Initialize swarm
npx agentic-flow hooks swarm-init --topology mesh --max-agents 5

# Spawn agents
npx agentic-flow hooks agent-spawn --type coder
npx agentic-flow hooks agent-spawn --type tester
npx agentic-flow hooks agent-spawn --type reviewer

# Orchestrate task
npx agentic-flow hooks task-orchestrate \
  --task "Build REST API with tests" \
  --mode parallel
```

## Topology Patterns

### 1. Mesh (Peer-to-Peer)
```typescript
// Equal peers, distributed decision-making
await swarm.init({
  topology: 'mesh',
  agents: ['coder', 'tester', 'reviewer'],
  communication: 'broadcast'
});
```

### 2. Hierarchical (Queen-Worker)
```typescript
// Centralized coordination, specialized workers
await swarm.init({
  topology: 'hierarchical',
  queen: 'architect',
  workers: ['backend-dev', 'frontend-dev', 'db-designer']
});
```

### 3. Adaptive (Dynamic)
```typescript
// Automatically switches topology based on task
await swarm.init({
  topology: 'adaptive',
  optimization: 'task-complexity'
});
```

## Task Orchestration

### Parallel Execution
```typescript
// Execute tasks concurrently
const results = await swarm.execute({
  tasks: [
    { agent: 'coder', task: 'Implement API endpoints' },
    { agent: 'frontend', task: 'Build UI components' },
    { agent: 'tester', task: 'Write test suite' }
  ],
  mode: 'parallel',
  timeout: 300000 // 5 minutes
});
```

### Pipeline Execution
```typescript
// Sequential pipeline with dependencies
await swarm.pipeline([
  { stage: 'design', agent: 'architect' },
  { stage: 'implement', agent: 'coder', after: 'design' },
  { stage: 'test', agent: 'tester', after: 'implement' },
  { stage: 'review', agent: 'reviewer', after: 'test' }
]);
```

### Adaptive Execution
```typescript
// Let swarm decide execution strategy
await swarm.autoOrchestrate({
  goal: 'Build production-ready API',
  constraints: {
    maxTime: 3600,
    maxAgents: 8,
    quality: 'high'
  }
});
```

## Memory Coordination

```typescript
// Share state across swarm
await swarm.memory.store('api-schema', {
  endpoints: [...],
  models: [...]
});

// Agents read shared memory
const schema = await swarm.memory.retrieve('api-schema');
```

## Advanced Features

### Load Balancing
```typescript
// Automatic work distribution
await swarm.enableLoadBalancing({
  strategy: 'dynamic',
  metrics: ['cpu', 'memory', 'task-queue']
});
```

### Fault Tolerance
```typescript
// Handle agent failures
await swarm.setResiliency({
  retry: { maxAttempts: 3, backoff: 'exponential' },
  fallback: 'reassign-task'
});
```

### Performance Monitoring
```typescript
// Track swarm metrics
const metrics = await swarm.getMetrics();
// { throughput, latency, success_rate, agent_utilization }
```

## Integration with Hooks

```bash
# Pre-task coordination
npx agentic-flow hooks pre-task --description "Build API"

# Post-task synchronization
npx agentic-flow hooks post-task --task-id "task-123"

# Session restore
npx agentic-flow hooks session-restore --session-id "swarm-001"
```

## Best Practices

1. **Start small**: Begin with 2-3 agents, scale up
2. **Use memory**: Share context through swarm memory
3. **Monitor metrics**: Track performance and bottlenecks
4. **Enable hooks**: Automatic coordination and sync
5. **Set timeouts**: Prevent hung tasks

## Troubleshooting

### Issue: Agents not coordinating
**Solution**: Verify memory access and enable hooks

### Issue: Poor performance
**Solution**: Check topology (use adaptive) and enable load balancing

## Learn More

- Swarm Guide: docs/swarm/orchestration.md
- Topology Patterns: docs/swarm/topologies.md
- Hooks Integration: docs/hooks/coordination.md

Related Skills

oss-contributor-swarm

25
from ComeOnOliver/skillshub

Autonomous 9-agent swarm that continuously contributes to open source projects on GitHub. Finds good-first-issues, analyzes requirements, writes code/tests/docs, creates PRs, and responds to reviews - all automatically with learning.

workflow-orchestration-patterns

25
from ComeOnOliver/skillshub

Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.

saga-orchestration

25
from ComeOnOliver/skillshub

Implement saga patterns for distributed transactions and cross-aggregate workflows. Use when coordinating multi-step business processes, handling compensating transactions, or managing long-running workflows.

full-stack-orchestration-full-stack-feature

25
from ComeOnOliver/skillshub

Use when working with full stack orchestration full stack feature

design-orchestration

25
from ComeOnOliver/skillshub

Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order. Prevents premature implementation, skipped validation, and unreviewed high-risk designs.

agent-orchestration-multi-agent-optimize

25
from ComeOnOliver/skillshub

Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.

agent-orchestration-improve-agent

25
from ComeOnOliver/skillshub

Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.

swarm

25
from ComeOnOliver/skillshub

Autonomous multi-agent workflow system for complex coding tasks. Use when the user requests non-trivial changes that would benefit from autonomous execution with built-in review gates. Ideal for refactoring modules, adding major features, migrating codebases, adding comprehensive test coverage, or any multi-step development task that can run autonomously. NOT for simple fixes, typos, or single-file changes.

memory-orchestration

25
from ComeOnOliver/skillshub

Analyze context management, memory systems, and state continuity in agent frameworks. Use when (1) understanding how prompts are assembled, (2) evaluating eviction policies for context overflow, (3) mapping memory tiers (short-term/long-term), (4) analyzing token budget management, or (5) comparing context strategies across frameworks.

when-using-advanced-swarm-use-swarm-advanced

25
from ComeOnOliver/skillshub

Advanced swarm patterns with dynamic topology switching and self-organizing behaviors for complex multi-agent coordination

when-orchestrating-swarm-use-swarm-orchestration

25
from ComeOnOliver/skillshub

Complex multi-agent swarm orchestration with task decomposition, distributed execution, and result synthesis

when-deploying-cloud-swarm-use-flow-nexus-swarm

25
from ComeOnOliver/skillshub

Deploy cloud-based AI agent swarms with event-driven workflow automation using Flow Nexus platform. Supports hierarchical, mesh, ring, and star topologies with E2B sandbox distribution.