Hermes Agent Getting Started Guide: A Better AI Agent Framework Than OpenClaude

What Is Hermes: An AI Agent Framework to Rival OpenClaude

Hermes is an AI Agent framework similar to OpenClaude (affectionately nicknamed "Crawfish" in the Chinese community), designed to serve as a personal work assistant. It can read and manipulate files on your computer, execute multi-step tasks, and act as an intelligent helper for everyday work.

Based on real-world usage, the course instructor offers a clear verdict: Hermes delivers a significantly better overall experience than OpenClaude. This "better" isn't just about interaction flow — more importantly, when Hermes operates on sensitive files, it provides timely warnings that reduce the risk of accidentally deleting important data. For an Agent that has permission to touch your local files, that's a critically important safety design.

The experience is significantly better

Precisely because the Agent has the ability to operate on local files, the course recommends deploying Hermes on Linux (Ubuntu) rather than directly on Windows. The reason is straightforward: on Windows, if operations run too fast and confirmations aren't carefully reviewed, you can easily delete important files. Isolating it in a Ubuntu environment essentially carves out a more controlled workspace for this "digital assistant." The instructor does clarify that Windows installation is technically possible — it's simply a tradeoff made for safety reasons.

AI Agent frameworks are a category of software architecture that allows large language models (LLMs) to go beyond mere "conversation" and actually execute tasks. Unlike simple chatbots, Agent frameworks give models the ability to call external tools (such as reading/writing files, executing commands, and accessing the web), completing complex multi-step tasks through a "think → act → observe" loop. OpenClaude — a community toolchain associated with Claude, often nicknamed "Crawfish" in Chinese circles — was one of the earlier implementations of this kind to gain traction in the Chinese-speaking community. Hermes builds on that foundation with more engineering encapsulation and safety optimizations. Understanding the concept of an "Agent framework" is the prerequisite for understanding why Hermes needs file permissions and why it should run in an isolated environment.

Environment Setup: Installing Ubuntu on VMware

The first part of the course covers environment setup and is aimed at users with zero prior experience with large models. The process breaks down into two steps:

Install VMware First, Then Ubuntu

VMware is a virtualization software. You install it first, then set up an Ubuntu system with a graphical interface on top of it. The GUI version of Ubuntu is chosen specifically to make things more intuitive and beginner-friendly. This "virtual machine + Linux" combination gives users the benefits of running Hermes in a Linux environment while avoiding the risks of modifying their primary Windows system.

For users who have never touched Linux, this step is the foundation for the rest of the course — and reflects the tutorial's commitment to being a true beginner's guide.

Getting Started: Installing and Configuring Hermes

The second part dives into Hermes itself. It covers how to install it, how to configure it, how to use it, and walks through the file directory structure. Understanding the directory structure is a prerequisite for troubleshooting issues and extending functionality down the line.

How to configure and use it

In terms of interaction style, Hermes more closely resembles Claude Code: it doesn't provide a visual interface by default the way OpenClaude does. Instead, after launching the client, you work through command-line multi-turn conversations. The course includes dedicated coverage of Session management — how to maintain multi-turn conversations and how to organize context. For users accustomed to graphical interfaces, Hermes also supports configuring a Web UI, which is covered in a later section of the course.

Tools and Skills: The Core Capabilities of an Agent

As an Agent, calling Tools and Skills is where its core value lies. This section of the course covers two levels:

Built-in Tools and Tool Extensions

First, what tools come built into Hermes; second, how to extend it with external tools so the Agent's capability boundary can grow with your needs.

Skill Configuration and Web-Based Skills

On the Skill side, the course explains how to configure Skills and how to support Skills loaded from the web. Tools handle "hands-on execution," while Skills handle "knowing how" — together they determine the complexity of tasks the Agent can complete.

We'll walk you through Hermes Agent's tools

In the design semantics of Agent frameworks, a Tool typically refers to an atomic operation the Agent can directly invoke — such as reading a file, executing a shell command, or making an HTTP request. A Skill, by contrast, is closer to an encapsulated composite capability or predefined task workflow: essentially a bundle of multiple tool calls packaged into a reusable "experience module." The benefit of this layered design is that lower-level tools remain general-purpose and atomic, while higher-level Skills can be rapidly customized for specific business scenarios without needing to re-orchestrate tool call chains from scratch each time. Supporting Skills loaded from the web means the community can share and distribute capability modules — users can gain access to complex task execution capabilities built by others without writing anything themselves.

Memory and Context: A Key Mechanism of the Agent

Memory and context are flagged by the instructor as a "particularly important" topic. Hermes has several distinct types of context internally. The course clarifies what each type is, how they relate to one another, and how they are loaded at runtime — including their loading order.

For an Agent, context management directly determines whether it can "remember" task objectives and maintain coherence across long chains of reasoning. Understanding this mechanism is the dividing line between "knowing how to use it" and "using it well."

The "memory" problem in Agents is fundamentally an engineering response to the hard constraint of limited context windows in large language models. There is a ceiling on how many tokens can be fed into a model at once, yet a complete task may span dozens of turns of interaction or even hours of work. To address this, Agent frameworks typically divide context into several categories: short-term memory (the conversation history of the current session), working memory (intermediate state and variables for the current task), and long-term memory (user preferences and historical conclusions persisted across sessions). The loading order determines which information gets prioritized within the model's effective perception window. Understanding this mechanism helps users diagnose whether a task failure was caused by lost context or a failed tool call — enabling more targeted adjustments to how they use the system.

Advanced Features: Voice, Web UI, and Multi-Platform Integration

The final section of the course covers several advanced capabilities.

Summary

The course spans eight modules in total: from installing Ubuntu on VMware and configuring Hermes, to Session management, Tools and Skills, memory and context, and finally voice mode, Web UI, and multi-platform integration. It forms a complete learning path from zero to advanced. For users who want to build their own AI work assistant but worry about the learning curve, this is a well-structured, accessible starting point.