Squashed 'vendor/ruvector/' content from commit b64c2172
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
This commit is contained in:
ruv
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.claude/skills/flow-nexus-swarm/SKILL.md
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.claude/skills/flow-nexus-swarm/SKILL.md
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---
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name: flow-nexus-swarm
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description: Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
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category: orchestration
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tags: [swarm, workflow, cloud, agents, automation, message-queue]
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version: 1.0.0
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requires:
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- flow-nexus MCP server
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- Active Flow Nexus account (register at flow-nexus.ruv.io)
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hooks:
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pre: |
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echo "🧠 Flow Nexus Swarm activated"
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if [ -d "/workspaces/ruvector/.claude/intelligence" ]; then
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cd /workspaces/ruvector/.claude/intelligence
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INTELLIGENCE_MODE=treatment node cli.js pre-edit "$FILE" 2>/dev/null || true
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fi
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post: |
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echo "✅ Flow Nexus Swarm complete"
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if [ -d "/workspaces/ruvector/.claude/intelligence" ]; then
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cd /workspaces/ruvector/.claude/intelligence
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INTELLIGENCE_MODE=treatment node cli.js post-edit "$FILE" "true" 2>/dev/null || true
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fi
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---
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# Flow Nexus Swarm & Workflow Orchestration
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Deploy and manage cloud-based AI agent swarms with event-driven workflow automation, message queue processing, and intelligent agent coordination.
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## Self-Learning Intelligence
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Integrates with RuVector's Q-learning and vector memory for improved performance.
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CLI: `node .claude/intelligence/cli.js stats`
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## 📋 Table of Contents
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1. [Overview](#overview)
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2. [Swarm Management](#swarm-management)
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3. [Workflow Automation](#workflow-automation)
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||||
4. [Agent Orchestration](#agent-orchestration)
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||||
5. [Templates & Patterns](#templates--patterns)
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6. [Advanced Features](#advanced-features)
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7. [Best Practices](#best-practices)
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## Overview
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Flow Nexus provides cloud-based orchestration for AI agent swarms with:
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- **Multi-topology Support**: Hierarchical, mesh, ring, and star architectures
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- **Event-driven Workflows**: Message queue processing with async execution
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- **Template Library**: Pre-built swarm configurations for common use cases
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- **Intelligent Agent Assignment**: Vector similarity matching for optimal agent selection
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- **Real-time Monitoring**: Comprehensive metrics and audit trails
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- **Scalable Infrastructure**: Cloud-based execution with auto-scaling
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## Swarm Management
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### Initialize Swarm
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Create a new swarm with specified topology and configuration:
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||||
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||||
```javascript
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mcp__flow-nexus__swarm_init({
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topology: "hierarchical", // Options: mesh, ring, star, hierarchical
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maxAgents: 8,
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strategy: "balanced" // Options: balanced, specialized, adaptive
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})
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```
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**Topology Guide:**
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- **Hierarchical**: Tree structure with coordinator nodes (best for complex projects)
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- **Mesh**: Peer-to-peer collaboration (best for research and analysis)
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- **Ring**: Circular coordination (best for sequential workflows)
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- **Star**: Centralized hub (best for simple delegation)
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**Strategy Guide:**
|
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- **Balanced**: Equal distribution of workload across agents
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- **Specialized**: Agents focus on specific expertise areas
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- **Adaptive**: Dynamic adjustment based on task complexity
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### Spawn Agents
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Add specialized agents to the swarm:
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||||
|
||||
```javascript
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mcp__flow-nexus__agent_spawn({
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||||
type: "researcher", // Options: researcher, coder, analyst, optimizer, coordinator
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||||
name: "Lead Researcher",
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||||
capabilities: ["web_search", "analysis", "summarization"]
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})
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```
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|
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**Agent Types:**
|
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- **Researcher**: Information gathering, web search, analysis
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- **Coder**: Code generation, refactoring, implementation
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- **Analyst**: Data analysis, pattern recognition, insights
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- **Optimizer**: Performance tuning, resource optimization
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- **Coordinator**: Task delegation, progress tracking, integration
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### Orchestrate Tasks
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||||
Distribute tasks across the swarm:
|
||||
|
||||
```javascript
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mcp__flow-nexus__task_orchestrate({
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||||
task: "Build a REST API with authentication and database integration",
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strategy: "parallel", // Options: parallel, sequential, adaptive
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||||
maxAgents: 5,
|
||||
priority: "high" // Options: low, medium, high, critical
|
||||
})
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||||
```
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|
||||
**Execution Strategies:**
|
||||
- **Parallel**: Maximum concurrency for independent subtasks
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- **Sequential**: Step-by-step execution with dependencies
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- **Adaptive**: AI-powered strategy selection based on task analysis
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||||
|
||||
### Monitor & Scale Swarms
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|
||||
```javascript
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// Get detailed swarm status
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mcp__flow-nexus__swarm_status({
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swarm_id: "optional-id" // Uses active swarm if not provided
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})
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// List all active swarms
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mcp__flow-nexus__swarm_list({
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status: "active" // Options: active, destroyed, all
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})
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// Scale swarm up or down
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mcp__flow-nexus__swarm_scale({
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target_agents: 10,
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swarm_id: "optional-id"
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})
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// Gracefully destroy swarm
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mcp__flow-nexus__swarm_destroy({
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swarm_id: "optional-id"
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})
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```
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|
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## Workflow Automation
|
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|
||||
### Create Workflow
|
||||
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||||
Define event-driven workflows with message queue processing:
|
||||
|
||||
```javascript
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mcp__flow-nexus__workflow_create({
|
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name: "CI/CD Pipeline",
|
||||
description: "Automated testing, building, and deployment",
|
||||
steps: [
|
||||
{
|
||||
id: "test",
|
||||
action: "run_tests",
|
||||
agent: "tester",
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||||
parallel: true
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||||
},
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||||
{
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||||
id: "build",
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||||
action: "build_app",
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||||
agent: "builder",
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||||
depends_on: ["test"]
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},
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{
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id: "deploy",
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action: "deploy_prod",
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||||
agent: "deployer",
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depends_on: ["build"]
|
||||
}
|
||||
],
|
||||
triggers: ["push_to_main", "manual_trigger"],
|
||||
metadata: {
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||||
priority: 10,
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||||
retry_policy: "exponential_backoff"
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||||
}
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||||
})
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||||
```
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||||
|
||||
**Workflow Features:**
|
||||
- **Dependency Management**: Define step dependencies with `depends_on`
|
||||
- **Parallel Execution**: Set `parallel: true` for concurrent steps
|
||||
- **Event Triggers**: GitHub events, schedules, manual triggers
|
||||
- **Retry Policies**: Automatic retry on transient failures
|
||||
- **Priority Queuing**: High-priority workflows execute first
|
||||
|
||||
### Execute Workflow
|
||||
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||||
Run workflows synchronously or asynchronously:
|
||||
|
||||
```javascript
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mcp__flow-nexus__workflow_execute({
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||||
workflow_id: "workflow_id",
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||||
input_data: {
|
||||
branch: "main",
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||||
commit: "abc123",
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||||
environment: "production"
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||||
},
|
||||
async: true // Queue-based execution for long-running workflows
|
||||
})
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||||
```
|
||||
|
||||
**Execution Modes:**
|
||||
- **Sync (async: false)**: Immediate execution, wait for completion
|
||||
- **Async (async: true)**: Message queue processing, non-blocking
|
||||
|
||||
### Monitor Workflows
|
||||
|
||||
```javascript
|
||||
// Get workflow status and metrics
|
||||
mcp__flow-nexus__workflow_status({
|
||||
workflow_id: "id",
|
||||
execution_id: "specific-run-id", // Optional
|
||||
include_metrics: true
|
||||
})
|
||||
|
||||
// List workflows with filters
|
||||
mcp__flow-nexus__workflow_list({
|
||||
status: "running", // Options: running, completed, failed, pending
|
||||
limit: 10,
|
||||
offset: 0
|
||||
})
|
||||
|
||||
// Get complete audit trail
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||||
mcp__flow-nexus__workflow_audit_trail({
|
||||
workflow_id: "id",
|
||||
limit: 50,
|
||||
start_time: "2025-01-01T00:00:00Z"
|
||||
})
|
||||
```
|
||||
|
||||
### Agent Assignment
|
||||
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||||
Intelligently assign agents to workflow tasks:
|
||||
|
||||
```javascript
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||||
mcp__flow-nexus__workflow_agent_assign({
|
||||
task_id: "task_id",
|
||||
agent_type: "coder", // Preferred agent type
|
||||
use_vector_similarity: true // AI-powered capability matching
|
||||
})
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||||
```
|
||||
|
||||
**Vector Similarity Matching:**
|
||||
- Analyzes task requirements and agent capabilities
|
||||
- Finds optimal agent based on past performance
|
||||
- Considers workload and availability
|
||||
|
||||
### Queue Management
|
||||
|
||||
Monitor and manage message queues:
|
||||
|
||||
```javascript
|
||||
mcp__flow-nexus__workflow_queue_status({
|
||||
queue_name: "optional-specific-queue",
|
||||
include_messages: true // Show pending messages
|
||||
})
|
||||
```
|
||||
|
||||
## Agent Orchestration
|
||||
|
||||
### Full-Stack Development Pattern
|
||||
|
||||
```javascript
|
||||
// 1. Initialize swarm with hierarchical topology
|
||||
mcp__flow-nexus__swarm_init({
|
||||
topology: "hierarchical",
|
||||
maxAgents: 8,
|
||||
strategy: "specialized"
|
||||
})
|
||||
|
||||
// 2. Spawn specialized agents
|
||||
mcp__flow-nexus__agent_spawn({ type: "coordinator", name: "Project Manager" })
|
||||
mcp__flow-nexus__agent_spawn({ type: "coder", name: "Backend Developer" })
|
||||
mcp__flow-nexus__agent_spawn({ type: "coder", name: "Frontend Developer" })
|
||||
mcp__flow-nexus__agent_spawn({ type: "coder", name: "Database Architect" })
|
||||
mcp__flow-nexus__agent_spawn({ type: "analyst", name: "QA Engineer" })
|
||||
|
||||
// 3. Create development workflow
|
||||
mcp__flow-nexus__workflow_create({
|
||||
name: "Full-Stack Development",
|
||||
steps: [
|
||||
{ id: "requirements", action: "analyze_requirements", agent: "coordinator" },
|
||||
{ id: "db_design", action: "design_schema", agent: "Database Architect" },
|
||||
{ id: "backend", action: "build_api", agent: "Backend Developer", depends_on: ["db_design"] },
|
||||
{ id: "frontend", action: "build_ui", agent: "Frontend Developer", depends_on: ["requirements"] },
|
||||
{ id: "integration", action: "integrate", agent: "Backend Developer", depends_on: ["backend", "frontend"] },
|
||||
{ id: "testing", action: "qa_testing", agent: "QA Engineer", depends_on: ["integration"] }
|
||||
]
|
||||
})
|
||||
|
||||
// 4. Execute workflow
|
||||
mcp__flow-nexus__workflow_execute({
|
||||
workflow_id: "workflow_id",
|
||||
input_data: {
|
||||
project: "E-commerce Platform",
|
||||
tech_stack: ["Node.js", "React", "PostgreSQL"]
|
||||
}
|
||||
})
|
||||
```
|
||||
|
||||
### Research & Analysis Pattern
|
||||
|
||||
```javascript
|
||||
// 1. Initialize mesh topology for collaborative research
|
||||
mcp__flow-nexus__swarm_init({
|
||||
topology: "mesh",
|
||||
maxAgents: 5,
|
||||
strategy: "balanced"
|
||||
})
|
||||
|
||||
// 2. Spawn research agents
|
||||
mcp__flow-nexus__agent_spawn({ type: "researcher", name: "Primary Researcher" })
|
||||
mcp__flow-nexus__agent_spawn({ type: "researcher", name: "Secondary Researcher" })
|
||||
mcp__flow-nexus__agent_spawn({ type: "analyst", name: "Data Analyst" })
|
||||
mcp__flow-nexus__agent_spawn({ type: "analyst", name: "Insights Analyst" })
|
||||
|
||||
// 3. Orchestrate research task
|
||||
mcp__flow-nexus__task_orchestrate({
|
||||
task: "Research machine learning trends for 2025 and analyze market opportunities",
|
||||
strategy: "parallel",
|
||||
maxAgents: 4,
|
||||
priority: "high"
|
||||
})
|
||||
```
|
||||
|
||||
### CI/CD Pipeline Pattern
|
||||
|
||||
```javascript
|
||||
mcp__flow-nexus__workflow_create({
|
||||
name: "Deployment Pipeline",
|
||||
description: "Automated testing, building, and multi-environment deployment",
|
||||
steps: [
|
||||
{ id: "lint", action: "lint_code", agent: "code_quality", parallel: true },
|
||||
{ id: "unit_test", action: "unit_tests", agent: "test_runner", parallel: true },
|
||||
{ id: "integration_test", action: "integration_tests", agent: "test_runner", parallel: true },
|
||||
{ id: "build", action: "build_artifacts", agent: "builder", depends_on: ["lint", "unit_test", "integration_test"] },
|
||||
{ id: "security_scan", action: "security_scan", agent: "security", depends_on: ["build"] },
|
||||
{ id: "deploy_staging", action: "deploy", agent: "deployer", depends_on: ["security_scan"] },
|
||||
{ id: "smoke_test", action: "smoke_tests", agent: "test_runner", depends_on: ["deploy_staging"] },
|
||||
{ id: "deploy_prod", action: "deploy", agent: "deployer", depends_on: ["smoke_test"] }
|
||||
],
|
||||
triggers: ["github_push", "github_pr_merged"],
|
||||
metadata: {
|
||||
priority: 10,
|
||||
auto_rollback: true
|
||||
}
|
||||
})
|
||||
```
|
||||
|
||||
### Data Processing Pipeline Pattern
|
||||
|
||||
```javascript
|
||||
mcp__flow-nexus__workflow_create({
|
||||
name: "ETL Pipeline",
|
||||
description: "Extract, Transform, Load data processing",
|
||||
steps: [
|
||||
{ id: "extract", action: "extract_data", agent: "data_extractor" },
|
||||
{ id: "validate_raw", action: "validate_data", agent: "validator", depends_on: ["extract"] },
|
||||
{ id: "transform", action: "transform_data", agent: "transformer", depends_on: ["validate_raw"] },
|
||||
{ id: "enrich", action: "enrich_data", agent: "enricher", depends_on: ["transform"] },
|
||||
{ id: "load", action: "load_data", agent: "loader", depends_on: ["enrich"] },
|
||||
{ id: "validate_final", action: "validate_data", agent: "validator", depends_on: ["load"] }
|
||||
],
|
||||
triggers: ["schedule:0 2 * * *"], // Daily at 2 AM
|
||||
metadata: {
|
||||
retry_policy: "exponential_backoff",
|
||||
max_retries: 3
|
||||
}
|
||||
})
|
||||
```
|
||||
|
||||
## Templates & Patterns
|
||||
|
||||
### Use Pre-built Templates
|
||||
|
||||
```javascript
|
||||
// Create swarm from template
|
||||
mcp__flow-nexus__swarm_create_from_template({
|
||||
template_name: "full-stack-dev",
|
||||
overrides: {
|
||||
maxAgents: 6,
|
||||
strategy: "specialized"
|
||||
}
|
||||
})
|
||||
|
||||
// List available templates
|
||||
mcp__flow-nexus__swarm_templates_list({
|
||||
category: "quickstart", // Options: quickstart, specialized, enterprise, custom, all
|
||||
includeStore: true
|
||||
})
|
||||
```
|
||||
|
||||
**Available Template Categories:**
|
||||
|
||||
**Quickstart Templates:**
|
||||
- `full-stack-dev`: Complete web development swarm
|
||||
- `research-team`: Research and analysis swarm
|
||||
- `code-review`: Automated code review swarm
|
||||
- `data-pipeline`: ETL and data processing
|
||||
|
||||
**Specialized Templates:**
|
||||
- `ml-development`: Machine learning project swarm
|
||||
- `mobile-dev`: Mobile app development
|
||||
- `devops-automation`: Infrastructure and deployment
|
||||
- `security-audit`: Security analysis and testing
|
||||
|
||||
**Enterprise Templates:**
|
||||
- `enterprise-migration`: Large-scale system migration
|
||||
- `multi-repo-sync`: Multi-repository coordination
|
||||
- `compliance-review`: Regulatory compliance workflows
|
||||
- `incident-response`: Automated incident management
|
||||
|
||||
### Custom Template Creation
|
||||
|
||||
Save successful swarm configurations as reusable templates for future projects.
|
||||
|
||||
## Advanced Features
|
||||
|
||||
### Real-time Monitoring
|
||||
|
||||
```javascript
|
||||
// Subscribe to execution streams
|
||||
mcp__flow-nexus__execution_stream_subscribe({
|
||||
stream_type: "claude-flow-swarm",
|
||||
deployment_id: "deployment_id"
|
||||
})
|
||||
|
||||
// Get execution status
|
||||
mcp__flow-nexus__execution_stream_status({
|
||||
stream_id: "stream_id"
|
||||
})
|
||||
|
||||
// List files created during execution
|
||||
mcp__flow-nexus__execution_files_list({
|
||||
stream_id: "stream_id",
|
||||
created_by: "claude-flow"
|
||||
})
|
||||
```
|
||||
|
||||
### Swarm Metrics & Analytics
|
||||
|
||||
```javascript
|
||||
// Get swarm performance metrics
|
||||
mcp__flow-nexus__swarm_status({
|
||||
swarm_id: "id"
|
||||
})
|
||||
|
||||
// Analyze workflow efficiency
|
||||
mcp__flow-nexus__workflow_status({
|
||||
workflow_id: "id",
|
||||
include_metrics: true
|
||||
})
|
||||
```
|
||||
|
||||
### Multi-Swarm Coordination
|
||||
|
||||
Coordinate multiple swarms for complex, multi-phase projects:
|
||||
|
||||
```javascript
|
||||
// Phase 1: Research swarm
|
||||
const researchSwarm = await mcp__flow-nexus__swarm_init({
|
||||
topology: "mesh",
|
||||
maxAgents: 4
|
||||
})
|
||||
|
||||
// Phase 2: Development swarm
|
||||
const devSwarm = await mcp__flow-nexus__swarm_init({
|
||||
topology: "hierarchical",
|
||||
maxAgents: 8
|
||||
})
|
||||
|
||||
// Phase 3: Testing swarm
|
||||
const testSwarm = await mcp__flow-nexus__swarm_init({
|
||||
topology: "star",
|
||||
maxAgents: 5
|
||||
})
|
||||
```
|
||||
|
||||
## Best Practices
|
||||
|
||||
### 1. Choose the Right Topology
|
||||
|
||||
```javascript
|
||||
// Simple projects: Star
|
||||
mcp__flow-nexus__swarm_init({ topology: "star", maxAgents: 3 })
|
||||
|
||||
// Collaborative work: Mesh
|
||||
mcp__flow-nexus__swarm_init({ topology: "mesh", maxAgents: 5 })
|
||||
|
||||
// Complex projects: Hierarchical
|
||||
mcp__flow-nexus__swarm_init({ topology: "hierarchical", maxAgents: 10 })
|
||||
|
||||
// Sequential workflows: Ring
|
||||
mcp__flow-nexus__swarm_init({ topology: "ring", maxAgents: 4 })
|
||||
```
|
||||
|
||||
### 2. Optimize Agent Assignment
|
||||
|
||||
```javascript
|
||||
// Use vector similarity for optimal matching
|
||||
mcp__flow-nexus__workflow_agent_assign({
|
||||
task_id: "complex-task",
|
||||
use_vector_similarity: true
|
||||
})
|
||||
```
|
||||
|
||||
### 3. Implement Proper Error Handling
|
||||
|
||||
```javascript
|
||||
mcp__flow-nexus__workflow_create({
|
||||
name: "Resilient Workflow",
|
||||
steps: [...],
|
||||
metadata: {
|
||||
retry_policy: "exponential_backoff",
|
||||
max_retries: 3,
|
||||
timeout: 300000, // 5 minutes
|
||||
on_failure: "notify_and_rollback"
|
||||
}
|
||||
})
|
||||
```
|
||||
|
||||
### 4. Monitor and Scale
|
||||
|
||||
```javascript
|
||||
// Regular monitoring
|
||||
const status = await mcp__flow-nexus__swarm_status()
|
||||
|
||||
// Scale based on workload
|
||||
if (status.workload > 0.8) {
|
||||
await mcp__flow-nexus__swarm_scale({ target_agents: status.agents + 2 })
|
||||
}
|
||||
```
|
||||
|
||||
### 5. Use Async Execution for Long-Running Workflows
|
||||
|
||||
```javascript
|
||||
// Long-running workflows should use message queues
|
||||
mcp__flow-nexus__workflow_execute({
|
||||
workflow_id: "data-pipeline",
|
||||
async: true // Non-blocking execution
|
||||
})
|
||||
|
||||
// Monitor progress
|
||||
mcp__flow-nexus__workflow_queue_status({ include_messages: true })
|
||||
```
|
||||
|
||||
### 6. Clean Up Resources
|
||||
|
||||
```javascript
|
||||
// Destroy swarm when complete
|
||||
mcp__flow-nexus__swarm_destroy({ swarm_id: "id" })
|
||||
```
|
||||
|
||||
### 7. Leverage Templates
|
||||
|
||||
```javascript
|
||||
// Use proven templates instead of building from scratch
|
||||
mcp__flow-nexus__swarm_create_from_template({
|
||||
template_name: "code-review",
|
||||
overrides: { maxAgents: 4 }
|
||||
})
|
||||
```
|
||||
|
||||
## Integration with Claude Flow
|
||||
|
||||
Flow Nexus swarms integrate seamlessly with Claude Flow hooks:
|
||||
|
||||
```bash
|
||||
# Pre-task coordination setup
|
||||
npx claude-flow@alpha hooks pre-task --description "Initialize swarm"
|
||||
|
||||
# Post-task metrics export
|
||||
npx claude-flow@alpha hooks post-task --task-id "swarm-execution"
|
||||
```
|
||||
|
||||
## Common Use Cases
|
||||
|
||||
### 1. Multi-Repo Development
|
||||
- Coordinate development across multiple repositories
|
||||
- Synchronized testing and deployment
|
||||
- Cross-repo dependency management
|
||||
|
||||
### 2. Research Projects
|
||||
- Distributed information gathering
|
||||
- Parallel analysis of different data sources
|
||||
- Collaborative synthesis and reporting
|
||||
|
||||
### 3. DevOps Automation
|
||||
- Infrastructure as Code deployment
|
||||
- Multi-environment testing
|
||||
- Automated rollback and recovery
|
||||
|
||||
### 4. Code Quality Workflows
|
||||
- Automated code review
|
||||
- Security scanning
|
||||
- Performance benchmarking
|
||||
|
||||
### 5. Data Processing
|
||||
- Large-scale ETL pipelines
|
||||
- Real-time data transformation
|
||||
- Data validation and quality checks
|
||||
|
||||
## Authentication & Setup
|
||||
|
||||
```bash
|
||||
# Install Flow Nexus
|
||||
npm install -g flow-nexus@latest
|
||||
|
||||
# Register account
|
||||
npx flow-nexus@latest register
|
||||
|
||||
# Login
|
||||
npx flow-nexus@latest login
|
||||
|
||||
# Add MCP server to Claude Code
|
||||
claude mcp add flow-nexus npx flow-nexus@latest mcp start
|
||||
```
|
||||
|
||||
## Support & Resources
|
||||
|
||||
- **Platform**: https://flow-nexus.ruv.io
|
||||
- **Documentation**: https://github.com/ruvnet/flow-nexus
|
||||
- **Issues**: https://github.com/ruvnet/flow-nexus/issues
|
||||
|
||||
---
|
||||
|
||||
**Remember**: Flow Nexus provides cloud-based orchestration infrastructure. For local execution and coordination, use the core `claude-flow` MCP server alongside Flow Nexus for maximum flexibility.
|
||||
Reference in New Issue
Block a user