Hermes Agent Guide: Surpassing OpenClaw, Boosting Productivity by 100x

Very few people noticed it at the time. Even though Nous Research has a certain reputation in the model community, and their Hermes series models have accumulated 33 million downloads on HuggingFace, the entire developer community’s attention was focused on the deified OpenClaw “Crawfish”. Surpassing React in 33 days to become the all-time number one, “Crawfish” became the fastest-growing project in GitHub history, peaking at 710 stars per hour. But at the same time, security researchers were continuously disclosing vulnerabilities within the same timeframe at an average rate of 2.2 CVEs per day, accumulating 138 security vulnerabilities over 63 days. The entire community began to reconsider a question: Can this thing actually be used in a production environment?

Against this backdrop, Hermes Agent, as a competing product, finally found an opportunity and entered its own first rapid growth phase.

Hermes wrote a one-click migration tool from OpenClaw into its code. Those developers leaving OpenClaw needed a place to land, and Hermes Agent became a well-recommended choice.

Thus, starting from early March, Hermes Agent broke into GitHub Trending, peaking at the 11th position, with stars exceeding 2200. AwesomeAgents called it “the most ambitious open-source Agent release of 2026 so far.” Currently, Hermes’ GitHub has 69.9k Stars and 9k Forks.

Today, BlockBeats talks with everyone about what makes this Agent different.

What is Hermes Agent?

Hermes Agent is a self-evolving AI agent built by Nous Research, and it is currently the only Agent with a built-in learning loop.

It can automatically create skills from usage experience, continuously improve these skills during use, actively solidify knowledge into reusable assets, retrieve its own past conversation history, and deepen its understanding of you, the user, across multiple sessions.

So, in simple terms, the biggest advantage of Hermes Agent is: the more you use it, the smarter and more convenient it becomes.

Its positioning is not as a programming assistant bound within an IDE, nor as a chat wrapper for a single API, but as a truly autonomous agent that resides on your server, remembers what it has learned, and becomes more capable the longer it runs.

From the beginning, Nous Research has positioned itself as an open-source-first, decentralization-oriented AI lab, aiming to build AI that users can autonomously control, rather than concentrating intelligence in the hands of a few closed companies. Their early work focused on the Hermes model series, while also heavily investing in infrastructure and systems. They explored DisTrO technology for model training across globally distributed consumer-grade GPUs, as well as simulation environments for multi-agent interaction and long-term behaviors like WorldSim and Doomscroll.

The team behind Hermes Agent is the same group that previously built a series of models including Nomos and Psyche.

What are the useful tools?

The core mechanisms of Hermes Agent are its memory system and skill system. The Agent maintains two streamlined core files: MEMORY.md stores environmental information, conventions, and summarized experiences from past tasks; USER.md stores your preferences and communication style. These two files are automatically injected into the system prompt at the start of each session, acting as the Agent’s “long-term working memory.” Additionally, all historical sessions are stored in a SQLite full-text search database, allowing the Agent to retrieve conversation content from weeks ago.

Regarding the skill system, each time a complex task is completed (typically involving 5 or more tool calls), the Agent autonomously creates a structured Markdown “skill document,” recording operational steps, known information, and verification methods for future reuse. Skill files follow a progressive disclosure pattern: the Agent by default only sees the skill name and description (about 3000 tokens), loading the full content of a specific skill only when needed, thereby controlling token consumption.

At the tool level, Hermes Agent comes with over 40 built-in tools, covering web search, browser automation, visual understanding, image generation, text-to-speech, and also supports setting scheduled tasks via natural language, allowing the Agent to automatically perform periodic work like report generation, data backup, and system monitoring unattended.

Among them, the most popular tools—those with the highest frequency of use, the most feedback from community users, and based on Hermes’ functional architecture and typical developer community needs—the top ones are these tools:

Hindsight is currently the hottest single tool within the ecosystem, recommended by Hermes as a long-term memory plugin. It automatically recalls relevant context before each LLM call, supports local PostgreSQL or cloud deployment, and is integrated into Hermes as a native Memory Provider.

Anthropic-Cybersecurity-Skills is the skill pack with the highest Stars in the ecosystem, containing 753+ structured cybersecurity skills, fully mapping the MITRE ATT&CK framework, suitable for security research and penetration testing scenarios.

mission-control is currently the most popular Agent orchestration dashboard in the ecosystem, supporting Agent fleet management, task distribution, cost tracking, and multi-agent collaborative workflows, recommended by the community as a standard for production-level deployment.

Hermes Agent Self-Evolution is an evolutionary self-improvement technique, using DSPy + GEPA to optimize skills, prompts, and code.

Hermes Workspace is the native workspace for Hermes, integrating a chat interface, terminal, and skill manager, and is the most popular graphical entry point.

Furthermore, it can spawn independent sub-agents, each with its own conversation context, independent terminal, and Python RPC scripts, enabling parallel pipelines with zero context cost.

In terms of infrastructure flexibility, it supports six terminal backends: local execution, Docker, SSH remote, Daytona serverless, Singularity containers, and Modal cloud functions. Daytona and Modal hibernate when idle, costing almost nothing. You can run it on a $5 VPS or a GPU cluster, issue commands via Telegram, and have it work on cloud servers you never SSH into directly.

Currently, Hermes Agent is in the most direct competitive relationship with OpenClaw, both being open-source Agent frameworks aimed at developers.

Their architectural philosophies are completely different: OpenClaw’s design core is a “control plane,” a unified long-running process responsible for managing sessions, routing, tool execution, and state—everything flows through this central controller. Hermes, on the other hand, centers on the Agent’s own execution loop, building everything—gateway, scheduler, tool runtime—around this iterative cycle of “do, learn, improve.”

The difference in skill systems is particularly significant: OpenClaw’s skills are mostly manually written, loaded from different levels like workspace, personal, shared, or plugins; Hermes’ approach is to let the Agent generate skills from experience, forming a true autonomous learning loop.

How to Install and Use

Getting started is extremely simple. One command, “curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash”, completes the installation. It supports Linux, macOS, and WSL2. Hermes Agent automatically completes all configurations without manual intervention.

Hermes Official Website

After installing Hermes Agent, run “hermes setup” to start the setup wizard. Choose your model provider (supports Nous Portal, OpenRouter, OpenAI, or any custom endpoint), connect your messaging platform (Telegram, Discord, Slack, or WhatsApp), and then start your first conversation. From the very first interaction, Hermes Agent immediately enters learning mode, starting to build memory, create skills, and becoming more capable after each session.

Core commands for daily use include:

hermes (start conversation),

hermes model (select LLM provider and model),

hermes tools (configure which tools to enable),

hermes gateway (start message gateway to connect to platforms like Telegram, Discord),

hermes setup (run the full setup wizard to configure everything at once),

hermes claw migrate (migrate from OpenClaw),

hermes update (update to the latest version),

hermes doctor (diagnose issues);

Hermes Agent is suitable for scenarios including: a general AI assistant that needs to remember context across sessions and continuously improve its capabilities; custom Agent workflows that require combining tools, plugins, MCP servers, browsers, or Shell; deploying Agents on local hardware, cloud VMs, or low-cost serverless infrastructure; and persistent assistant scenarios requiring searchable conversation history and learned skills across platforms.

More specifically, you can use it to have conversations with it on Telegram while it executes tasks on a cloud VM, set up automations and push reports to any platform, let it take over periodic tasks; you can also integrate it into Slack or Discord to provide AI collaboration support for an entire team; or utilize its trajectory export function to generate training data for RL training of next-generation tool-calling models.

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