designing-agent-workflows

Name: designing-agent-workflows
Availability: InStock
Author: maltemd

Design multi-step agent workflows with goals, decision points, and failure handling.

Updated Feb 26, 2026

Search Tags:#automation #workflow #agent #decision tree #orchestration #state machine

Ready to run

npx skills add https://github.com/maltemd/hoover-content-design-system --skill designing-agent-workflows-maltemd

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: designing-agent-workflows
Source: https://github.com/maltemd/hoover-content-design-system/tree/main/skills/mcp-and-agents/designing-agent-workflows
Command: npx skills add https://github.com/maltemd/hoover-content-design-system --skill designing-agent-workflows-maltemd

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you design and document multi-step workflows that orchestrate agent actions to achieve complex goals, ensuring clarity and predictability in autonomous operations.

Core Features & Use Cases

Workflow Design: Define clear goals, success criteria, and step-by-step processes for agents.
Decision Logic: Map out decision points and branching conditions for dynamic task execution.
State Management: Track and manage state variables across workflow steps.
Failure Handling: Implement robust strategies for handling errors and ensuring workflow resilience.
Use Case: Design a workflow for an agent to research a topic, summarize findings, and draft a report, including steps for data gathering, analysis, and human review.

Quick Start

Design an agent workflow to refactor a function, including steps for identification, testing, refactoring, and validation.

Frequently Asked Questions about designing-agent-workflows

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I design a multi-step workflow for orchestrating autonomous agent actions?▼

Designing agent orchestration involves mapping explicit workflow goals, success criteria, step sequences, decision points, state tracking, and failure handling to ensure predictable autonomous task execution.

What is a decision tree in agent workflow orchestration?▼

Decision trees in agent orchestration map branching conditions and decision points, enabling autonomous agents to dynamically select task execution paths based on real-time state variables.

How do I implement state management and failure handling for autonomous agent state machines?▼

Implement state management by tracking variables across workflow steps, and ensure workflow resilience by defining explicit failure handling strategies that govern error recovery during autonomous operations.

Can I use this approach to plan an agent task sequence for research and report drafting?▼

Yes, you can design workflows for agents to research, summarize, and draft reports by defining sequential steps for data gathering, analysis, and human review, including specific decision points and success criteria.

What's the best way to structure a refactoring workflow for an autonomous agent?▼

Structure a refactoring workflow by defining sequential steps for function identification, testing, refactoring, and validation, ensuring each step has clear success criteria and state tracking for reliable autonomous execution.