agent-workflow-designer

What This Skill Does

The Agent Workflow Designer is a powerful architectural framework designed for engineers building complex multi-agent systems. It moves beyond simple prompt chaining to help you architect production-grade orchestration logic. The tool provides a structured approach to implementing five foundational patterns: Sequential Pipelines, Parallel Fan-out/Fan-in, Hierarchical Delegation, Event-Driven triggers, and Consensus models. By utilizing this skill, you can define clear handoff protocols, manage state transitions between specialist agents, and implement robust error recovery strategies that prevent workflow degradation in production environments.

Installation

You can integrate this skill directly into your OpenClaw environment using the following command: clawhub install openclaw/skills/skills/alirezarezvani/agent-workflow-designer

Use Cases

• Complex Content Pipelines: Automating multi-stage document workflows where research, drafting, and editorial review require distinct persona-driven agents.
• Data Processing Orchestration: Implementing parallelized data analysis tasks that require a fan-in stage for final aggregation and reporting.
• Fault-Tolerant Automation: Designing self-healing agent architectures that use state management and retry logic to recover from API failures or context window overflows.
• Multi-Agent Teams: Coordinating diverse agent pools like those used in CrewAI or AutoGen by enforcing strict communication contracts and token budget allocations.

Example Prompts

1. "I am building a research agent that needs to draft a whitepaper. Design a sequential pipeline that includes a fact-checker agent and a copy-editor agent, ensuring the context window remains optimized for Claude 3.5 Sonnet."
2. "Help me create a parallel fan-out architecture where four agents investigate different market sectors, then have a single 'Manager' agent synthesize their reports into a unified strategy document."
3. "My multi-agent workflow is failing during the handover between the data extraction agent and the analysis agent. Can you help me define a structured JSON handoff protocol to preserve state and reduce hallucinations?"

Tips & Limitations

• Context Budgeting: Always define max_tokens per stage; the designer is designed to optimize usage, but recursive delegation can rapidly balloon costs.
• Hierarchy: Avoid creating more than three levels of delegation unless absolutely necessary to minimize latency.
• State Management: Use the state-persistence features to ensure that if a workflow is interrupted, it can resume from the last successful stage rather than restarting entirely.