Claude-skill-registry cloud-workflow
Event-driven workflow automation in Flow Nexus cloud. Use for creating, executing, and managing complex automated workflows with message queue processing and intelligent agent coordination.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/cloud-workflow" ~/.claude/skills/majiayu000-claude-skill-registry-cloud-workflow && rm -rf "$T"
manifest:
skills/data/cloud-workflow/SKILL.mdsource content
Cloud Workflow
Design and orchestrate event-driven automation workflows with intelligent agent coordination and message queue processing.
Quick Start
// Create a CI/CD workflow const workflow = await mcp__flow-nexus__workflow_create({ name: "CI/CD Pipeline", description: "Automated testing and deployment", steps: [ { id: "test", action: "run_tests", agent: "tester" }, { id: "build", action: "build_app", agent: "builder" }, { id: "deploy", action: "deploy_prod", agent: "deployer" } ], triggers: ["push_to_main", "manual_trigger"] }); // Execute the workflow await mcp__flow-nexus__workflow_execute({ workflow_id: workflow.workflow_id, input_data: { branch: "main" }, async: true });
When to Use
- Automating CI/CD pipelines with multiple stages
- Orchestrating data processing and ETL workflows
- Creating event-driven automation for business processes
- Managing multi-stage review and approval workflows
- Scheduling recurring automated tasks
- Coordinating complex multi-agent collaboration
Prerequisites
- Flow Nexus account with active session
- MCP server
configuredflow-nexus - Sufficient rUv credits for workflow execution
Core Concepts
Workflow Patterns
| Pattern | Description | Use Case |
|---|---|---|
| CI/CD Pipeline | Test, build, deploy sequence | Software deployment |
| Data Processing | ETL with validation steps | Data engineering |
| Multi-Stage Review | Automated analysis + approval | Code review |
| Event-Driven | Reactive to external events | Webhooks, notifications |
| Scheduled | Time-based execution | Recurring tasks |
| Conditional | Branching logic and decisions | Complex business rules |
Execution Strategies
- Sequential: Steps run one after another
- Parallel: Independent steps run simultaneously
- Conditional: Steps execute based on conditions
Agent Assignment
Workflows can automatically assign optimal agents to tasks using:
- Explicit Assignment: Specify agent type per step
- Vector Similarity: AI-powered matching based on task requirements
MCP Tools Reference
Workflow Creation
mcp__flow-nexus__workflow_create({ name: "Workflow Name", description: "Workflow description", steps: [ { id: "step1", action: "action_name", agent: "agent_type", // Optional: auto-assigned if not specified config: {} // Step-specific configuration }, { id: "step2", action: "action_name", depends: ["step1"] // Dependencies on other steps } ], triggers: ["trigger1", "trigger2"], // Event triggers priority: 5, // Priority 0-10 metadata: {} // Additional metadata }) // Returns: { workflow_id, name, status, created_at }
Workflow Execution
mcp__flow-nexus__workflow_execute({ workflow_id: "workflow_id", input_data: { // Input data for execution key: "value" }, async: true // Execute asynchronously via queue }) // Returns: { execution_id, status, started_at }
Status and Monitoring
// Get workflow status mcp__flow-nexus__workflow_status({ workflow_id: "workflow_id", execution_id: "execution_id", // Optional: specific execution include_metrics: true }) // Returns: { status, progress, metrics, step_results } // List all workflows mcp__flow-nexus__workflow_list({ status: "active", // Filter by status limit: 10, offset: 0 }) // Check message queue status mcp__flow-nexus__workflow_queue_status({ queue_name: "queue_name", // Optional: specific queue include_messages: true })
Agent Assignment
mcp__flow-nexus__workflow_agent_assign({ task_id: "task_id", agent_type: "coder", // Preferred agent type use_vector_similarity: true // Use AI matching }) // Returns: { agent_id, type, match_score }
Audit Trail
mcp__flow-nexus__workflow_audit_trail({ workflow_id: "workflow_id", start_time: "2026-01-01T00:00:00Z", limit: 50 }) // Returns: { events: [{ timestamp, action, user, details }] }
Usage Examples
Example 1: CI/CD Pipeline
// Create comprehensive CI/CD workflow const cicdWorkflow = await mcp__flow-nexus__workflow_create({ name: "Full CI/CD Pipeline", description: "Complete testing, building, and deployment workflow", steps: [ { id: "lint", action: "run_linter", agent: "code-analyzer", config: { strict: true } }, { id: "test", action: "run_tests", agent: "tester", config: { coverage_threshold: 80 }, depends: ["lint"] }, { id: "security_scan", action: "security_check", agent: "security-analyzer", depends: ["lint"] }, { id: "build", action: "build_app", agent: "builder", depends: ["test", "security_scan"] }, { id: "deploy_staging", action: "deploy", agent: "deployer", config: { environment: "staging" }, depends: ["build"] }, { id: "integration_tests", action: "run_integration_tests", agent: "tester", depends: ["deploy_staging"] }, { id: "deploy_prod", action: "deploy", agent: "deployer", config: { environment: "production" }, depends: ["integration_tests"] } ], triggers: ["push_to_main", "release_tag"], priority: 8 }); // Execute on push await mcp__flow-nexus__workflow_execute({ workflow_id: cicdWorkflow.workflow_id, input_data: { branch: "main", commit: "abc123", author: "developer@example.com" }, async: true }); // Monitor progress const status = await mcp__flow-nexus__workflow_status({ workflow_id: cicdWorkflow.workflow_id, include_metrics: true }); console.log(`Progress: ${status.progress}%, Current step: ${status.current_step}`);
Example 2: Data Processing Pipeline
// ETL workflow with validation const etlWorkflow = await mcp__flow-nexus__workflow_create({ name: "Data ETL Pipeline", description: "Extract, transform, and load data with validation", steps: [ { id: "extract", action: "extract_data", agent: "data-extractor", config: { source: "s3://bucket/raw-data" } }, { id: "validate", action: "validate_schema", agent: "data-validator", depends: ["extract"] }, { id: "transform", action: "transform_data", agent: "data-transformer", config: { rules: ["normalize", "dedupe", "enrich"] }, depends: ["validate"] }, { id: "quality_check", action: "run_quality_checks", agent: "data-analyst", depends: ["transform"] }, { id: "load", action: "load_to_warehouse", agent: "data-loader", config: { target: "postgres://warehouse" }, depends: ["quality_check"] } ], triggers: ["schedule:0 2 * * *", "manual_trigger"] // Daily at 2 AM }); // Manual execution await mcp__flow-nexus__workflow_execute({ workflow_id: etlWorkflow.workflow_id, input_data: { date: "2026-01-02" } });
Example 3: Multi-Stage Code Review
// Automated code review workflow const reviewWorkflow = await mcp__flow-nexus__workflow_create({ name: "Automated Code Review", description: "Multi-stage code analysis and review", steps: [ { id: "static_analysis", action: "run_static_analysis", agent: "code-analyzer" }, { id: "security_review", action: "security_scan", agent: "security-reviewer", depends: ["static_analysis"] }, { id: "performance_review", action: "analyze_performance", agent: "perf-analyzer", depends: ["static_analysis"] }, { id: "ai_review", action: "ai_code_review", agent: "ai-reviewer", depends: ["static_analysis"] }, { id: "compile_report", action: "generate_report", agent: "report-generator", depends: ["security_review", "performance_review", "ai_review"] } ], triggers: ["pull_request_opened", "pull_request_updated"] }); // Assign optimal agent dynamically await mcp__flow-nexus__workflow_agent_assign({ task_id: "security_review_123", use_vector_similarity: true });
Example 4: Queue Management
// Check queue status const queueStatus = await mcp__flow-nexus__workflow_queue_status({ include_messages: true }); console.log(`Pending messages: ${queueStatus.pending}`); console.log(`Processing: ${queueStatus.processing}`); // Review audit trail const audit = await mcp__flow-nexus__workflow_audit_trail({ workflow_id: "workflow_id", limit: 100 }); for (const event of audit.events) { console.log(`${event.timestamp}: ${event.action} by ${event.user}`); }
Execution Checklist
- Define workflow steps and dependencies
- Assign or auto-assign agents to steps
- Configure triggers (events, schedules)
- Set workflow priority
- Create the workflow
- Execute with appropriate input data
- Monitor progress and step status
- Review audit trail for compliance
- Clean up or archive completed workflows
Best Practices
- Step Granularity: Break complex tasks into atomic steps for better monitoring
- Dependency Chains: Carefully plan dependencies to maximize parallelism
- Error Handling: Include retry logic and fallback steps
- Async Execution: Use async mode for long-running workflows
- Agent Matching: Leverage vector similarity for optimal agent assignment
- Audit Compliance: Regularly review audit trails for security
Error Handling
| Error | Cause | Solution |
|---|---|---|
| Invalid step configuration | Verify step IDs and dependencies |
| Step error or timeout | Check step logs, increase timeout |
| No suitable agent available | Specify alternative agent type |
| Too many pending messages | Scale workers or reduce rate |
| Steps reference each other | Review dependency graph |
Metrics & Success Criteria
- Workflow Completion Rate: Target >95%
- Average Execution Time: Track per workflow type
- Queue Latency: <10 seconds for async jobs
- Agent Utilization: >80% during active workflows
- Error Rate: <5% per workflow type
Integration Points
With Swarms
// Swarm-powered workflow const swarm = await mcp__flow-nexus__swarm_init({ topology: "mesh" }); await mcp__flow-nexus__workflow_create({ name: "Swarm Workflow", steps: [ { id: "task", action: "swarm_execute", config: { swarm_id: swarm.swarm_id } } ] });
With Sandboxes
// Sandbox execution in workflow await mcp__flow-nexus__workflow_create({ name: "Sandbox Pipeline", steps: [ { id: "create", action: "sandbox_create", config: { template: "node" } }, { id: "test", action: "sandbox_execute", depends: ["create"] }, { id: "cleanup", action: "sandbox_delete", depends: ["test"] } ] });
Related Skills
- cloud-swarm - Multi-agent orchestration
- cloud-sandbox - Isolated execution environments
- cloud-neural - Neural network operations
References
Version History
- 1.0.0 (2026-01-02): Initial release - converted from flow-nexus-workflow agent