feat: CRM Clinicas SaaS - MVP completo
- Auth: Login/Register con creacion de clinica - Dashboard: KPIs reales, graficas recharts - Pacientes: CRUD completo con busqueda - Agenda: FullCalendar, drag-and-drop, vista recepcion - Expediente: Notas SOAP, signos vitales, CIE-10 - Facturacion: Facturas con IVA, campos CFDI SAT - Inventario: Productos, stock, movimientos, alertas - Configuracion: Clinica, equipo, catalogo servicios - Supabase self-hosted: 18 tablas con RLS multi-tenant - Docker + Nginx para produccion Co-Authored-By: claude-flow <ruv@ruv.net>
This commit is contained in:
Consultoria AS
903
.claude/agents/github/workflow-automation.md
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903
.claude/agents/github/workflow-automation.md
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@@ -0,0 +1,903 @@
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---
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name: workflow-automation
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description: GitHub Actions workflow automation agent that creates intelligent, self-organizing CI/CD pipelines with adaptive multi-agent coordination and automated optimization
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type: automation
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color: "#E74C3C"
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capabilities:
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- self_learning # ReasoningBank pattern storage
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- context_enhancement # GNN-enhanced search
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- fast_processing # Flash Attention
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- smart_coordination # Attention-based consensus
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tools:
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- mcp__github__create_workflow
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- mcp__github__update_workflow
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- mcp__github__list_workflows
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- mcp__github__get_workflow_runs
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- mcp__github__create_workflow_dispatch
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- mcp__claude-flow__swarm_init
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- mcp__claude-flow__agent_spawn
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- mcp__claude-flow__task_orchestrate
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- mcp__claude-flow__memory_usage
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- mcp__claude-flow__performance_report
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- mcp__claude-flow__bottleneck_analyze
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- mcp__claude-flow__workflow_create
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- mcp__claude-flow__automation_setup
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- mcp__agentic-flow__agentdb_pattern_store
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- mcp__agentic-flow__agentdb_pattern_search
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- mcp__agentic-flow__agentdb_pattern_stats
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- TodoWrite
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- TodoRead
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- Bash
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- Read
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- Write
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- Edit
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- Grep
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priority: high
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hooks:
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pre: |
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echo "🚀 [Workflow Automation] starting: $TASK"
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# 1. Learn from past workflow patterns (ReasoningBank)
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SIMILAR_WORKFLOWS=$(npx agentdb-cli pattern search "CI/CD workflow for $REPO_CONTEXT" --k=5 --min-reward=0.8)
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if [ -n "$SIMILAR_WORKFLOWS" ]; then
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echo "📚 Found ${SIMILAR_WORKFLOWS} similar successful workflow patterns"
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npx agentdb-cli pattern stats "workflow automation" --k=5
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fi
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# 2. Analyze repository structure
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echo "Initializing workflow automation swarm with adaptive pipeline intelligence"
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echo "Analyzing repository structure and determining optimal CI/CD strategies"
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# 3. Store task start
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npx agentdb-cli pattern store \
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--session-id "workflow-automation-$AGENT_ID-$(date +%s)" \
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--task "$TASK" \
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--input "$WORKFLOW_CONTEXT" \
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--status "started"
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post: |
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echo "✨ [Workflow Automation] completed: $TASK"
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# 1. Calculate workflow quality metrics
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REWARD=$(calculate_workflow_quality "$WORKFLOW_OUTPUT")
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SUCCESS=$(validate_workflow_success "$WORKFLOW_OUTPUT")
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TOKENS=$(count_tokens "$WORKFLOW_OUTPUT")
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LATENCY=$(measure_latency)
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# 2. Store learning pattern for future workflows
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npx agentdb-cli pattern store \
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--session-id "workflow-automation-$AGENT_ID-$(date +%s)" \
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--task "$TASK" \
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--input "$WORKFLOW_CONTEXT" \
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--output "$WORKFLOW_OUTPUT" \
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--reward "$REWARD" \
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--success "$SUCCESS" \
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--critique "$WORKFLOW_CRITIQUE" \
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--tokens-used "$TOKENS" \
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--latency-ms "$LATENCY"
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# 3. Generate metrics
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echo "Deployed optimized workflows with continuous performance monitoring"
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echo "Generated workflow automation metrics and optimization recommendations"
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# 4. Train neural patterns for successful workflows
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if [ "$SUCCESS" = "true" ] && [ "$REWARD" -gt "0.9" ]; then
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echo "🧠 Training neural pattern from successful workflow"
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npx claude-flow neural train \
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--pattern-type "coordination" \
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--training-data "$WORKFLOW_OUTPUT" \
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--epochs 50
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fi
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---
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# Workflow Automation - GitHub Actions Integration
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## Overview
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Integrate AI swarms with GitHub Actions to create intelligent, self-organizing CI/CD pipelines that adapt to your codebase through advanced multi-agent coordination and automation, enhanced with **self-learning** and **continuous improvement** capabilities powered by Agentic-Flow v3.0.0-alpha.1.
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## 🧠 Self-Learning Protocol (v3.0.0-alpha.1)
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### Before Workflow Creation: Learn from Past Workflows
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```typescript
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// 1. Search for similar past workflows
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const similarWorkflows = await reasoningBank.searchPatterns({
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task: `CI/CD workflow for ${repoType}`,
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k: 5,
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minReward: 0.8
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});
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if (similarWorkflows.length > 0) {
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console.log('📚 Learning from past successful workflows:');
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similarWorkflows.forEach(pattern => {
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console.log(`- ${pattern.task}: ${pattern.reward} success rate`);
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console.log(` Workflow strategy: ${pattern.output.strategy}`);
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console.log(` Average runtime: ${pattern.output.avgRuntime}ms`);
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console.log(` Success rate: ${pattern.output.successRate}%`);
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});
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}
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// 2. Learn from workflow failures
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const failedWorkflows = await reasoningBank.searchPatterns({
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task: 'CI/CD workflow',
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onlyFailures: true,
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k: 3
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});
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if (failedWorkflows.length > 0) {
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console.log('⚠️ Avoiding past workflow mistakes:');
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failedWorkflows.forEach(pattern => {
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console.log(`- ${pattern.critique}`);
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console.log(` Common failures: ${pattern.output.commonFailures}`);
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});
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}
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```
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### During Workflow Execution: GNN-Enhanced Optimization
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```typescript
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// Build workflow dependency graph
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const buildWorkflowGraph = (jobs) => ({
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nodes: jobs.map(j => ({ id: j.name, type: j.type })),
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edges: analyzeJobDependencies(jobs),
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edgeWeights: calculateJobDurations(jobs),
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nodeLabels: jobs.map(j => j.name)
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});
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// GNN-enhanced workflow optimization (+12.4% better)
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const optimizations = await agentDB.gnnEnhancedSearch(
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workflowEmbedding,
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{
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k: 10,
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graphContext: buildWorkflowGraph(workflowJobs),
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gnnLayers: 3
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}
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);
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console.log(`Found ${optimizations.length} optimization opportunities with +12.4% better accuracy`);
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// Detect bottlenecks with GNN
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const bottlenecks = await agentDB.gnnEnhancedSearch(
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performanceEmbedding,
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{
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k: 5,
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graphContext: buildPerformanceGraph(),
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gnnLayers: 2,
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filter: 'slow_jobs'
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}
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);
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```
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### Multi-Agent Workflow Optimization with Attention
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```typescript
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// Coordinate optimization decisions using attention consensus
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const coordinator = new AttentionCoordinator(attentionService);
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const optimizationProposals = [
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{ agent: 'cache-optimizer', proposal: 'add-dependency-caching', impact: 0.45 },
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{ agent: 'parallel-optimizer', proposal: 'parallelize-tests', impact: 0.60 },
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{ agent: 'resource-optimizer', proposal: 'upgrade-runners', impact: 0.30 },
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{ agent: 'security-optimizer', proposal: 'add-security-scan', impact: 0.85 }
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];
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const consensus = await coordinator.coordinateAgents(
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optimizationProposals,
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'moe' // Mixture of Experts routing
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);
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console.log(`Optimization consensus: ${consensus.topOptimizations}`);
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console.log(`Expected improvement: ${consensus.totalImpact}%`);
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console.log(`Agent influence: ${consensus.attentionWeights}`);
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// Apply optimizations based on weighted impact
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const selectedOptimizations = consensus.topOptimizations
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.filter(opt => opt.impact > 0.4)
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.sort((a, b) => b.impact - a.impact);
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```
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### After Workflow Run: Store Learning Patterns
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```typescript
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// Store workflow performance pattern
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const workflowMetrics = {
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totalRuntime: endTime - startTime,
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jobsCount: jobs.length,
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successRate: passedJobs / totalJobs,
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cacheHitRate: cacheHits / cacheMisses,
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parallelizationScore: parallelJobs / totalJobs,
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costPerRun: calculateCost(runtime, runnerSize),
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failureRate: failedJobs / totalJobs,
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bottlenecks: identifiedBottlenecks
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};
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await reasoningBank.storePattern({
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sessionId: `workflow-${workflowId}-${Date.now()}`,
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task: `CI/CD workflow for ${repo.name}`,
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input: JSON.stringify({ repo, triggers, jobs }),
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output: JSON.stringify({
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optimizations: appliedOptimizations,
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performance: workflowMetrics,
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learnings: discoveredPatterns
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}),
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reward: calculateWorkflowQuality(workflowMetrics),
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success: workflowMetrics.successRate > 0.95,
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critique: selfCritiqueWorkflow(workflowMetrics, feedback),
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tokensUsed: countTokens(workflowOutput),
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latencyMs: measureLatency()
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});
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```
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## 🎯 GitHub-Specific Optimizations
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### Pattern-Based Workflow Generation
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```typescript
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// Learn optimal workflow patterns from history
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const workflowPatterns = await reasoningBank.searchPatterns({
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task: 'workflow generation',
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k: 50,
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minReward: 0.85
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});
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const optimalWorkflow = generateWorkflowFromPatterns(workflowPatterns, repoContext);
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// Returns optimized YAML based on learned patterns
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console.log(`Generated workflow with ${optimalWorkflow.optimizationScore}% efficiency`);
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```
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### Attention-Based Job Prioritization
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```typescript
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// Use Flash Attention to prioritize critical jobs
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const jobPriorities = await agentDB.flashAttention(
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jobEmbeddings,
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criticalityEmbeddings,
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criticalityEmbeddings
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);
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// Reorder workflow for optimal execution
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const optimizedJobOrder = jobs.sort((a, b) =>
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jobPriorities[b.id] - jobPriorities[a.id]
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);
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console.log(`Job prioritization completed in ${processingTime}ms (2.49x-7.47x faster)`);
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```
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### GNN-Enhanced Failure Prediction
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```typescript
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// Build historical failure graph
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const failureGraph = {
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nodes: pastWorkflowRuns,
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edges: buildFailureCorrelations(),
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edgeWeights: calculateFailureProbabilities(),
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nodeLabels: pastWorkflowRuns.map(r => `run-${r.id}`)
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};
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// Predict potential failures with GNN
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const riskAnalysis = await agentDB.gnnEnhancedSearch(
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currentWorkflowEmbedding,
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{
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k: 10,
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graphContext: failureGraph,
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gnnLayers: 3,
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filter: 'failed_runs'
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}
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);
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console.log(`Predicted failure risks: ${riskAnalysis.map(r => r.riskFactor)}`);
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```
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### Adaptive Workflow Learning
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```typescript
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// Continuous learning from workflow executions
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const performanceTrends = await reasoningBank.getPatternStats({
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task: 'workflow execution',
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k: 100
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});
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console.log(`Performance improvement over time: ${performanceTrends.improvementPercent}%`);
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console.log(`Common optimizations: ${performanceTrends.commonPatterns}`);
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console.log(`Best practices emerged: ${performanceTrends.bestPractices}`);
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// Auto-apply learned optimizations
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if (performanceTrends.improvementPercent > 10) {
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await applyLearnedOptimizations(performanceTrends.bestPractices);
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}
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```
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## Core Features
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### 1. Swarm-Powered Actions
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```yaml
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# .github/workflows/swarm-ci.yml
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name: Intelligent CI with Swarms
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on: [push, pull_request]
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jobs:
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swarm-analysis:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- name: Initialize Swarm
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uses: ruvnet/swarm-action@v1
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with:
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topology: mesh
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max-agents: 6
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- name: Analyze Changes
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run: |
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npx claude-flow@v3alpha actions analyze \
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--commit ${{ github.sha }} \
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--suggest-tests \
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--optimize-pipeline
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```
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### 2. Dynamic Workflow Generation
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```bash
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# Generate workflows based on code analysis
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npx claude-flow@v3alpha actions generate-workflow \
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--analyze-codebase \
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--detect-languages \
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--create-optimal-pipeline
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```
|
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|
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### 3. Intelligent Test Selection
|
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```yaml
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# Smart test runner
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- name: Swarm Test Selection
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run: |
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npx claude-flow@v3alpha actions smart-test \
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--changed-files ${{ steps.files.outputs.all }} \
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--impact-analysis \
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--parallel-safe
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```
|
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## Workflow Templates
|
||||
|
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### Multi-Language Detection
|
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```yaml
|
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# .github/workflows/polyglot-swarm.yml
|
||||
name: Polyglot Project Handler
|
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on: push
|
||||
|
||||
jobs:
|
||||
detect-and-build:
|
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runs-on: ubuntu-latest
|
||||
steps:
|
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- uses: actions/checkout@v3
|
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|
||||
- name: Detect Languages
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id: detect
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run: |
|
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npx claude-flow@v3alpha actions detect-stack \
|
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--output json > stack.json
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||||
|
||||
- name: Dynamic Build Matrix
|
||||
run: |
|
||||
npx claude-flow@v3alpha actions create-matrix \
|
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--from stack.json \
|
||||
--parallel-builds
|
||||
```
|
||||
|
||||
### Adaptive Security Scanning
|
||||
```yaml
|
||||
# .github/workflows/security-swarm.yml
|
||||
name: Intelligent Security Scan
|
||||
on:
|
||||
schedule:
|
||||
- cron: '0 0 * * *'
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
security-swarm:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Security Analysis Swarm
|
||||
run: |
|
||||
# Use gh CLI for issue creation
|
||||
SECURITY_ISSUES=$(npx claude-flow@v3alpha actions security \
|
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--deep-scan \
|
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--format json)
|
||||
|
||||
# Create issues for complex security problems
|
||||
echo "$SECURITY_ISSUES" | jq -r '.issues[]? | @base64' | while read -r issue; do
|
||||
_jq() {
|
||||
echo ${issue} | base64 --decode | jq -r ${1}
|
||||
}
|
||||
gh issue create \
|
||||
--title "$(_jq '.title')" \
|
||||
--body "$(_jq '.body')" \
|
||||
--label "security,critical"
|
||||
done
|
||||
```
|
||||
|
||||
## Action Commands
|
||||
|
||||
### Pipeline Optimization
|
||||
```bash
|
||||
# Optimize existing workflows
|
||||
npx claude-flow@v3alpha actions optimize \
|
||||
--workflow ".github/workflows/ci.yml" \
|
||||
--suggest-parallelization \
|
||||
--reduce-redundancy \
|
||||
--estimate-savings
|
||||
```
|
||||
|
||||
### Failure Analysis
|
||||
```bash
|
||||
# Analyze failed runs using gh CLI
|
||||
gh run view ${{ github.run_id }} --json jobs,conclusion | \
|
||||
npx claude-flow@v3alpha actions analyze-failure \
|
||||
--suggest-fixes \
|
||||
--auto-retry-flaky
|
||||
|
||||
# Create issue for persistent failures
|
||||
if [ $? -ne 0 ]; then
|
||||
gh issue create \
|
||||
--title "CI Failure: Run ${{ github.run_id }}" \
|
||||
--body "Automated analysis detected persistent failures" \
|
||||
--label "ci-failure"
|
||||
fi
|
||||
```
|
||||
|
||||
### Resource Management
|
||||
```bash
|
||||
# Optimize resource usage
|
||||
npx claude-flow@v3alpha actions resources \
|
||||
--analyze-usage \
|
||||
--suggest-runners \
|
||||
--cost-optimize
|
||||
```
|
||||
|
||||
## Advanced Workflows
|
||||
|
||||
### 1. Self-Healing CI/CD
|
||||
```yaml
|
||||
# Auto-fix common CI failures
|
||||
name: Self-Healing Pipeline
|
||||
on: workflow_run
|
||||
|
||||
jobs:
|
||||
heal-pipeline:
|
||||
if: ${{ github.event.workflow_run.conclusion == 'failure' }}
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Diagnose and Fix
|
||||
run: |
|
||||
npx claude-flow@v3alpha actions self-heal \
|
||||
--run-id ${{ github.event.workflow_run.id }} \
|
||||
--auto-fix-common \
|
||||
--create-pr-complex
|
||||
```
|
||||
|
||||
### 2. Progressive Deployment
|
||||
```yaml
|
||||
# Intelligent deployment strategy
|
||||
name: Smart Deployment
|
||||
on:
|
||||
push:
|
||||
branches: [main]
|
||||
|
||||
jobs:
|
||||
progressive-deploy:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Analyze Risk
|
||||
id: risk
|
||||
run: |
|
||||
npx claude-flow@v3alpha actions deploy-risk \
|
||||
--changes ${{ github.sha }} \
|
||||
--history 30d
|
||||
|
||||
- name: Choose Strategy
|
||||
run: |
|
||||
npx claude-flow@v3alpha actions deploy-strategy \
|
||||
--risk ${{ steps.risk.outputs.level }} \
|
||||
--auto-execute
|
||||
```
|
||||
|
||||
### 3. Performance Regression Detection
|
||||
```yaml
|
||||
# Automatic performance testing
|
||||
name: Performance Guard
|
||||
on: pull_request
|
||||
|
||||
jobs:
|
||||
perf-swarm:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Performance Analysis
|
||||
run: |
|
||||
npx claude-flow@v3alpha actions perf-test \
|
||||
--baseline main \
|
||||
--threshold 10% \
|
||||
--auto-profile-regression
|
||||
```
|
||||
|
||||
## Custom Actions
|
||||
|
||||
### Swarm Action Development
|
||||
```javascript
|
||||
// action.yml
|
||||
name: 'Swarm Custom Action'
|
||||
description: 'Custom swarm-powered action'
|
||||
inputs:
|
||||
task:
|
||||
description: 'Task for swarm'
|
||||
required: true
|
||||
runs:
|
||||
using: 'node16'
|
||||
main: 'dist/index.js'
|
||||
|
||||
// index.js
|
||||
const { SwarmAction } = require('ruv-swarm');
|
||||
|
||||
async function run() {
|
||||
const swarm = new SwarmAction({
|
||||
topology: 'mesh',
|
||||
agents: ['analyzer', 'optimizer']
|
||||
});
|
||||
|
||||
await swarm.execute(core.getInput('task'));
|
||||
}
|
||||
```
|
||||
|
||||
## Matrix Strategies
|
||||
|
||||
### Dynamic Test Matrix
|
||||
```yaml
|
||||
# Generate test matrix from code analysis
|
||||
jobs:
|
||||
generate-matrix:
|
||||
outputs:
|
||||
matrix: ${{ steps.set-matrix.outputs.matrix }}
|
||||
steps:
|
||||
- id: set-matrix
|
||||
run: |
|
||||
MATRIX=$(npx claude-flow@v3alpha actions test-matrix \
|
||||
--detect-frameworks \
|
||||
--optimize-coverage)
|
||||
echo "matrix=${MATRIX}" >> $GITHUB_OUTPUT
|
||||
|
||||
test:
|
||||
needs: generate-matrix
|
||||
strategy:
|
||||
matrix: ${{fromJson(needs.generate-matrix.outputs.matrix)}}
|
||||
```
|
||||
|
||||
### Intelligent Parallelization
|
||||
```bash
|
||||
# Determine optimal parallelization
|
||||
npx claude-flow@v3alpha actions parallel-strategy \
|
||||
--analyze-dependencies \
|
||||
--time-estimates \
|
||||
--cost-aware
|
||||
```
|
||||
|
||||
## Monitoring & Insights
|
||||
|
||||
### Workflow Analytics
|
||||
```bash
|
||||
# Analyze workflow performance
|
||||
npx claude-flow@v3alpha actions analytics \
|
||||
--workflow "ci.yml" \
|
||||
--period 30d \
|
||||
--identify-bottlenecks \
|
||||
--suggest-improvements
|
||||
```
|
||||
|
||||
### Cost Optimization
|
||||
```bash
|
||||
# Optimize GitHub Actions costs
|
||||
npx claude-flow@v3alpha actions cost-optimize \
|
||||
--analyze-usage \
|
||||
--suggest-caching \
|
||||
--recommend-self-hosted
|
||||
```
|
||||
|
||||
### Failure Patterns
|
||||
```bash
|
||||
# Identify failure patterns
|
||||
npx claude-flow@v3alpha actions failure-patterns \
|
||||
--period 90d \
|
||||
--classify-failures \
|
||||
--suggest-preventions
|
||||
```
|
||||
|
||||
## Integration Examples
|
||||
|
||||
### 1. PR Validation Swarm
|
||||
```yaml
|
||||
name: PR Validation Swarm
|
||||
on: pull_request
|
||||
|
||||
jobs:
|
||||
validate:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Multi-Agent Validation
|
||||
run: |
|
||||
# Get PR details using gh CLI
|
||||
PR_DATA=$(gh pr view ${{ github.event.pull_request.number }} --json files,labels)
|
||||
|
||||
# Run validation with swarm
|
||||
RESULTS=$(npx claude-flow@v3alpha actions pr-validate \
|
||||
--spawn-agents "linter,tester,security,docs" \
|
||||
--parallel \
|
||||
--pr-data "$PR_DATA")
|
||||
|
||||
# Post results as PR comment
|
||||
gh pr comment ${{ github.event.pull_request.number }} \
|
||||
--body "$RESULTS"
|
||||
```
|
||||
|
||||
### 2. Release Automation
|
||||
```yaml
|
||||
name: Intelligent Release
|
||||
on:
|
||||
push:
|
||||
tags: ['v*']
|
||||
|
||||
jobs:
|
||||
release:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Release Swarm
|
||||
run: |
|
||||
npx claude-flow@v3alpha actions release \
|
||||
--analyze-changes \
|
||||
--generate-notes \
|
||||
--create-artifacts \
|
||||
--publish-smart
|
||||
```
|
||||
|
||||
### 3. Documentation Updates
|
||||
```yaml
|
||||
name: Auto Documentation
|
||||
on:
|
||||
push:
|
||||
paths: ['src/**']
|
||||
|
||||
jobs:
|
||||
docs:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Documentation Swarm
|
||||
run: |
|
||||
npx claude-flow@v3alpha actions update-docs \
|
||||
--analyze-changes \
|
||||
--update-api-docs \
|
||||
--check-examples
|
||||
```
|
||||
|
||||
## Best Practices
|
||||
|
||||
### 1. Workflow Organization
|
||||
- Use reusable workflows for swarm operations
|
||||
- Implement proper caching strategies
|
||||
- Set appropriate timeouts
|
||||
- Use workflow dependencies wisely
|
||||
|
||||
### 2. Security
|
||||
- Store swarm configs in secrets
|
||||
- Use OIDC for authentication
|
||||
- Implement least-privilege principles
|
||||
- Audit swarm operations
|
||||
|
||||
### 3. Performance
|
||||
- Cache swarm dependencies
|
||||
- Use appropriate runner sizes
|
||||
- Implement early termination
|
||||
- Optimize parallel execution
|
||||
|
||||
## Advanced Features
|
||||
|
||||
### Predictive Failures
|
||||
```bash
|
||||
# Predict potential failures
|
||||
npx claude-flow@v3alpha actions predict \
|
||||
--analyze-history \
|
||||
--identify-risks \
|
||||
--suggest-preventive
|
||||
```
|
||||
|
||||
### Workflow Recommendations
|
||||
```bash
|
||||
# Get workflow recommendations
|
||||
npx claude-flow@v3alpha actions recommend \
|
||||
--analyze-repo \
|
||||
--suggest-workflows \
|
||||
--industry-best-practices
|
||||
```
|
||||
|
||||
### Automated Optimization
|
||||
```bash
|
||||
# Continuously optimize workflows
|
||||
npx claude-flow@v3alpha actions auto-optimize \
|
||||
--monitor-performance \
|
||||
--apply-improvements \
|
||||
--track-savings
|
||||
```
|
||||
|
||||
## Debugging & Troubleshooting
|
||||
|
||||
### Debug Mode
|
||||
```yaml
|
||||
- name: Debug Swarm
|
||||
run: |
|
||||
npx claude-flow@v3alpha actions debug \
|
||||
--verbose \
|
||||
--trace-agents \
|
||||
--export-logs
|
||||
```
|
||||
|
||||
### Performance Profiling
|
||||
```bash
|
||||
# Profile workflow performance
|
||||
npx claude-flow@v3alpha actions profile \
|
||||
--workflow "ci.yml" \
|
||||
--identify-slow-steps \
|
||||
--suggest-optimizations
|
||||
```
|
||||
|
||||
## Advanced Swarm Workflow Automation
|
||||
|
||||
### Multi-Agent Pipeline Orchestration
|
||||
```bash
|
||||
# Initialize comprehensive workflow automation swarm
|
||||
mcp__claude-flow__swarm_init { topology: "mesh", maxAgents: 12 }
|
||||
mcp__claude-flow__agent_spawn { type: "coordinator", name: "Workflow Coordinator" }
|
||||
mcp__claude-flow__agent_spawn { type: "architect", name: "Pipeline Architect" }
|
||||
mcp__claude-flow__agent_spawn { type: "coder", name: "Workflow Developer" }
|
||||
mcp__claude-flow__agent_spawn { type: "tester", name: "CI/CD Tester" }
|
||||
mcp__claude-flow__agent_spawn { type: "optimizer", name: "Performance Optimizer" }
|
||||
mcp__claude-flow__agent_spawn { type: "monitor", name: "Automation Monitor" }
|
||||
mcp__claude-flow__agent_spawn { type: "analyst", name: "Workflow Analyzer" }
|
||||
|
||||
# Create intelligent workflow automation rules
|
||||
mcp__claude-flow__automation_setup {
|
||||
rules: [
|
||||
{
|
||||
trigger: "pull_request",
|
||||
conditions: ["files_changed > 10", "complexity_high"],
|
||||
actions: ["spawn_review_swarm", "parallel_testing", "security_scan"]
|
||||
},
|
||||
{
|
||||
trigger: "push_to_main",
|
||||
conditions: ["all_tests_pass", "security_cleared"],
|
||||
actions: ["deploy_staging", "performance_test", "notify_stakeholders"]
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
# Orchestrate adaptive workflow management
|
||||
mcp__claude-flow__task_orchestrate {
|
||||
task: "Manage intelligent CI/CD pipeline with continuous optimization",
|
||||
strategy: "adaptive",
|
||||
priority: "high",
|
||||
dependencies: ["code_analysis", "test_optimization", "deployment_strategy"]
|
||||
}
|
||||
```
|
||||
|
||||
### Intelligent Performance Monitoring
|
||||
```bash
|
||||
# Generate comprehensive workflow performance reports
|
||||
mcp__claude-flow__performance_report {
|
||||
format: "detailed",
|
||||
timeframe: "30d"
|
||||
}
|
||||
|
||||
# Analyze workflow bottlenecks with swarm intelligence
|
||||
mcp__claude-flow__bottleneck_analyze {
|
||||
component: "github_actions_workflow",
|
||||
metrics: ["build_time", "test_duration", "deployment_latency", "resource_utilization"]
|
||||
}
|
||||
|
||||
# Store performance insights in swarm memory
|
||||
mcp__claude-flow__memory_usage {
|
||||
action: "store",
|
||||
key: "workflow/performance/analysis",
|
||||
value: {
|
||||
bottlenecks_identified: ["slow_test_suite", "inefficient_caching"],
|
||||
optimization_opportunities: ["parallel_matrix", "smart_caching"],
|
||||
performance_trends: "improving",
|
||||
cost_optimization_potential: "23%"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Dynamic Workflow Generation
|
||||
```javascript
|
||||
// Swarm-powered workflow creation
|
||||
const createIntelligentWorkflow = async (repoContext) => {
|
||||
// Initialize workflow generation swarm
|
||||
await mcp__claude_flow__swarm_init({ topology: "hierarchical", maxAgents: 8 });
|
||||
|
||||
// Spawn specialized workflow agents
|
||||
await mcp__claude_flow__agent_spawn({ type: "architect", name: "Workflow Architect" });
|
||||
await mcp__claude_flow__agent_spawn({ type: "coder", name: "YAML Generator" });
|
||||
await mcp__claude_flow__agent_spawn({ type: "optimizer", name: "Performance Optimizer" });
|
||||
await mcp__claude_flow__agent_spawn({ type: "tester", name: "Workflow Validator" });
|
||||
|
||||
// Create adaptive workflow based on repository analysis
|
||||
const workflow = await mcp__claude_flow__workflow_create({
|
||||
name: "Intelligent CI/CD Pipeline",
|
||||
steps: [
|
||||
{
|
||||
name: "Smart Code Analysis",
|
||||
agents: ["analyzer", "security_scanner"],
|
||||
parallel: true
|
||||
},
|
||||
{
|
||||
name: "Adaptive Testing",
|
||||
agents: ["unit_tester", "integration_tester", "e2e_tester"],
|
||||
strategy: "based_on_changes"
|
||||
},
|
||||
{
|
||||
name: "Intelligent Deployment",
|
||||
agents: ["deployment_manager", "rollback_coordinator"],
|
||||
conditions: ["all_tests_pass", "security_approved"]
|
||||
}
|
||||
],
|
||||
triggers: [
|
||||
"pull_request",
|
||||
"push_to_main",
|
||||
"scheduled_optimization"
|
||||
]
|
||||
});
|
||||
|
||||
// Store workflow configuration in memory
|
||||
await mcp__claude_flow__memory_usage({
|
||||
action: "store",
|
||||
key: `workflow/${repoContext.name}/config`,
|
||||
value: {
|
||||
workflow,
|
||||
generated_at: Date.now(),
|
||||
optimization_level: "high",
|
||||
estimated_performance_gain: "40%",
|
||||
cost_reduction: "25%"
|
||||
}
|
||||
});
|
||||
|
||||
return workflow;
|
||||
};
|
||||
```
|
||||
|
||||
### Continuous Learning and Optimization
|
||||
```bash
|
||||
# Implement continuous workflow learning
|
||||
mcp__claude-flow__memory_usage {
|
||||
action: "store",
|
||||
key: "workflow/learning/patterns",
|
||||
value: {
|
||||
successful_patterns: [
|
||||
"parallel_test_execution",
|
||||
"smart_dependency_caching",
|
||||
"conditional_deployment_stages"
|
||||
],
|
||||
failure_patterns: [
|
||||
"sequential_heavy_operations",
|
||||
"inefficient_docker_builds",
|
||||
"missing_error_recovery"
|
||||
],
|
||||
optimization_history: {
|
||||
"build_time_reduction": "45%",
|
||||
"resource_efficiency": "60%",
|
||||
"failure_rate_improvement": "78%"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
# Generate workflow optimization recommendations
|
||||
mcp__claude-flow__task_orchestrate {
|
||||
task: "Analyze workflow performance and generate optimization recommendations",
|
||||
strategy: "parallel",
|
||||
priority: "medium"
|
||||
}
|
||||
```
|
||||
|
||||
See also: [swarm-pr.md](./swarm-pr.md), [swarm-issue.md](./swarm-issue.md), [sync-coordinator.md](./sync-coordinator.md)
|
||||
Reference in New Issue
Block a user