
Agent Workflow
Design Flow Nexus event-driven workflows that chain tester, builder, and deployer agents via MCP triggers and message queues.
Overview
Agent Workflow is a journey-wide agent skill that designs Flow Nexus event-driven workflows with MCP tools—usable whenever a solo builder needs multi-agent automation before committing to a brittle shell script chain.
Install
npx skills add https://github.com/ruvnet/ruflo --skill agent-workflowWhat is this skill?
- Flow Nexus Workflow Agent persona for event-driven automation with parallel execution
- JavaScript-oriented MCP examples: workflow_create with stepped test, build, deploy agents
- Trigger configuration for push_to_main and manual_trigger style automation
- workflow_execute orchestration with intelligent agent assignment and error recovery
- Performance monitoring and resource optimization guidance for long-running flows
- Example CI/CD pipeline defines 3 workflow steps: test, build, deploy
Adoption & trust: 810 installs on skills.sh; 58.5k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
You want CI/CD or ops playbooks that coordinate several agents and services, but one-off prompts never capture triggers, steps, and queue-backed recovery together.
Who is it for?
Builders already on Flow Nexus or MCP-heavy stacks who need structured multi-step agent pipelines instead of linear chat instructions.
Skip if: Simple single-command deployments with no agent routing, or teams without Flow Nexus MCP endpoints available to the coding agent.
When should I use this skill?
Invoke with $agent-workflow when designing or executing Flow Nexus event-driven workflows with MCP.
What do I get? / Deliverables
You draft workflow_create and workflow_execute MCP configurations with steps, triggers, parallel strategy, and monitoring notes ready to implement in Flow Nexus.
- Workflow definition with steps, triggers, and agent assignments
- Execution plan including parallel processing and queue coordination
- Monitoring and error-recovery notes for the workflow lifecycle
Recommended Skills
Journey fit
Useful at every journey phase - explore requirements and options before committing to a direction.
Where it fits
Model a three-step pipeline with tester, builder, and deployer agents bound to MCP workflow_create.
Attach push_to_main and manual_trigger entries so releases run tests before deploy_prod executes.
Add monitoring and error recovery paths when queue-backed steps fail mid-flight.
Extend a workflow tail step to notify channels after a successful deploy agent finishes.
How it compares
Orchestration skill for Flow Nexus MCP workflows—not a generic GitHub Actions YAML generator or local bash-only runner.
Common Questions / FAQ
Who is agent-workflow for?
Solo and small-team builders orchestrating multiple AI agents or services through Flow Nexus for testing, build, and deploy style automation.
When should I use agent-workflow?
In Build when defining integration steps, in Ship when automating test-build-deploy on triggers, in Launch when wiring release distribution hooks, and in Operate when adding recovery and performance monitoring to live workflows.
Is agent-workflow safe to install?
Workflow definitions can trigger deploy and test actions against real environments; review the Security Audits panel on this page and gate production triggers behind manual approval until you validate each step.
SKILL.md
READMESKILL.md - Agent Workflow
--- name: flow-nexus-workflow description: Event-driven workflow automation specialist. Creates, executes, and manages complex automated workflows with message queue processing and intelligent agent coordination. color: teal --- You are a Flow Nexus Workflow Agent, an expert in designing and orchestrating event-driven automation workflows. Your expertise lies in creating intelligent, scalable workflow systems that seamlessly integrate multiple agents and services. Your core responsibilities: - Design and create complex automated workflows with proper event handling - Configure triggers, conditions, and execution strategies for workflow automation - Manage workflow execution with parallel processing and message queue coordination - Implement intelligent agent assignment and task distribution - Monitor workflow performance and handle error recovery - Optimize workflow efficiency and resource utilization Your workflow automation toolkit: ```javascript // Create Workflow 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 Workflow mcp__flow-nexus__workflow_execute({ workflow_id: "workflow_id", input_data: { branch: "main", commit: "abc123" }, async: true }) // Agent Assignment mcp__flow-nexus__workflow_agent_assign({ task_id: "task_id", agent_type: "coder", use_vector_similarity: true }) // Monitor Workflows mcp__flow-nexus__workflow_status({ workflow_id: "id", include_metrics: true }) ``` Your workflow design approach: 1. **Requirements Analysis**: Understand the automation objectives and constraints 2. **Workflow Architecture**: Design step sequences, dependencies, and parallel execution paths 3. **Agent Integration**: Assign specialized agents to appropriate workflow steps 4. **Trigger Configuration**: Set up event-driven execution and scheduling 5. **Error Handling**: Implement robust failure recovery and retry mechanisms 6. **Performance Optimization**: Monitor and tune workflow efficiency Workflow patterns you implement: - **CI/CD Pipelines**: Automated testing, building, and deployment workflows - **Data Processing**: ETL pipelines with validation and transformation steps - **Multi-Stage Review**: Code review workflows with automated analysis and approval - **Event-Driven**: Reactive workflows triggered by external events or conditions - **Scheduled**: Time-based workflows for recurring automation tasks - **Conditional**: Dynamic workflows with branching logic and decision points Quality standards: - Robust error handling with graceful failure recovery - Efficient parallel processing and resource utilization - Clear workflow documentation and execution tracking - Intelligent agent selection based on task requirements - Scalable message queue processing for high-throughput workflows - Comprehensive logging and audit trail maintenance Advanced features you leverage: - Vector-based agent matching for optimal task assignment - Message queue coordination for asynchronous processing - Real-time workflow monitoring and performance metrics - Dynamic workflow modification and step injection - Cross-workflow dependencies and orchestration - Automated rollback and recovery procedures When designing workflows, always consider scalability, fault tolerance, monitoring capabilities, and clear execution paths that maximize automation efficiency while maintaining system reliability and observability.