# Daedalus: A Plugin System for Building Workflows for Hermes Intelligent Agents

> A plugin designed specifically for Hermes-agent that enables users to create, orchestrate, and manage workflows for AI agents, automating the execution of complex multi-step tasks.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-04-29T18:44:24.000Z
- 最近活动: 2026-04-29T18:56:35.251Z
- 热度: 159.8
- 关键词: AI代理, Hermes-agent, 工作流编排, 插件系统, Agent工作流, 任务自动化, DAG, 错误恢复
- 页面链接: https://www.zingnex.cn/en/forum/thread/daedalus-hermes
- Canonical: https://www.zingnex.cn/forum/thread/daedalus-hermes
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: Daedalus: A Plugin System for Building Workflows for Hermes Intelligent Agents

A plugin designed specifically for Hermes-agent that enables users to create, orchestrate, and manage workflows for AI agents, automating the execution of complex multi-step tasks.

## Project Background: The Hermes-agent Ecosystem

To understand the value of Daedalus, we first need to understand its host platform, Hermes-agent. Hermes-agent is an AI agent framework aimed at building intelligent agents that can perform tasks autonomously. These agents can:
- Understand natural language instructions
- Call tools to complete specific operations
- Reason and make decisions in multi-step tasks
- Interact with external systems (APIs, databases, file systems, etc.)

However, the capabilities of a single agent are always limited. Complex business scenarios often require coordination of multiple steps, handling of conditional branches, error recovery mechanisms, etc. This is exactly the problem Daedalus aims to solve.

## Core Functionality: Workflow Orchestration

Daedalus's core mission is to add workflow capabilities to Hermes-agent. Specifically, it provides:

## Step Definition and Connection

A workflow consists of a series of steps, each of which can be:
- Calling a specific tool or API
- Executing a logical judgment
- Delegating to a sub-agent for processing
- Waiting for an external event to trigger

Daedalus allows users to define dependencies and execution order between these steps, building various workflows from simple linear processes to complex Directed Acyclic Graphs (DAGs).

## Conditional Branching and Decision Making

Real-world workflows are rarely linear. Daedalus supports:
- Conditional branching based on the results of previous steps
- Convergence after parallel execution of multiple paths
- Loop and iteration processing
- Dynamic step generation (determining the next step based on runtime data)

## State Management

Multi-step workflows need to maintain execution states. Daedalus provides:
- Data transfer mechanism between steps
- Workflow-level context storage
- Persistence of execution history
- Resumable execution capability (support for long-running workflows)

## Error Handling and Recovery

A robust workflow must have the ability to handle failures. Daedalus implements:
- Step-level retry strategies
- Timeout control and graceful degradation
- Error propagation and capture
- Compensating transactions (undoing completed steps)

## Architectural Design Principles

Daedalus's design embodies several important architectural principles: