On February 25, a team called Nous Research quietly pushed a v0.1.0 on GitHub. Initially, the Hermes model only had one line of installation command and a one-sentence product positioning: "An agent that grows with you."
At that time, few people paid attention to it, even though Nous Research had a certain reputation in the model community, their Hermes series models had accumulated 33 million downloads on HuggingFace, but the attention of the entire developer community was focused on the revered OpenClaw "Little Lobster". In 33 days, it surpassed React to become the first in history, and "Little Lobster" became the fastest-growing project on GitHub ever, peaking at 710 stars per hour. However, during this time, security researchers continuously disclosed vulnerabilities at an average rate of 2.2 CVEs per day within the same time window, accumulating 138 security vulnerabilities over 63 days. The entire community began to reconsider a question: can this thing really be used in a production environment?
In this context, Hermes Agent, as a competing product, finally found its opportunity and welcomed its first rapid growth period.
Hermes has written a one-click migration tool from OpenClaw into its own code. Those developers who left OpenClaw need a place to land, and Hermes Agent has become a well-recommended choice.
As of early March, Hermes Agent surged into GitHub Trending, peaking at 11th place, with stars exceeding 2200. AwesomeAgents called it 'the most ambitious open-source Agent release of 2026 so far', and currently, Hermes's GitHub has 69.9k stars and 9k forks.
Today, Rhythm BlockBeats will talk about what makes this Agent different.
What is Hermes Agent?
Hermes Agent is a self-evolving AI entity 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, proactively solidify knowledge into reusable assets, retrieve its own past conversation history, and deepen its understanding of you as a user over multiple sessions.
So simply put, the biggest advantage of Hermes Agent is: the more you use it, the smarter it gets, and the easier it becomes to use.
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 residing on your server, capable of remembering what it learns and becoming more powerful the longer it runs.
Nous Research has positioned itself from the very beginning as an open-source-first, decentralized AI lab, aiming to build AI that users can control autonomously, rather than concentrating intelligence in a few closed companies. Their early work focused on the Hermes model series, while heavily investing in infrastructure and system-level capabilities, and exploring the DisTrO technology for model training across globally distributed consumer-grade GPUs, as well as multi-agent interaction and long-range behavior simulation environments like WorldSim and Doomscroll.
The team behind Hermes Agent is the same group that created the series of models including Nomos and Psyche.
What are some useful tools?
The core mechanism of Hermes Agent is its memory system and skill system. The Agent maintains two streamlined core files: MEMORY.md stores environmental information, agreements, and experiences summarized from past tasks; USER.md stores your preferences and communication style. These two files automatically inject system prompts at the start of each session, equivalent to the Agent's 'long-term working memory'. Additionally, all historical sessions are stored in an SQLite full-text search database, allowing the Agent to retrieve conversation content from weeks ago.
In terms of the skill system, each time a complex task is completed (usually more than 5 tool calls), the Agent autonomously creates a structured Markdown 'skill document', recording operation steps, known content, and verification methods for future reuse. Skill documents follow a progressive disclosure model: the Agent only sees the skill name and description by default (about 3000 tokens), loading the complete content of a skill only when needed, thus controlling token consumption.
On the tools side, Hermes Agent comes with over 40 built-in tools, covering web search, browser automation, visual understanding, image generation, text-to-speech, and it also supports setting scheduled tasks through natural language, allowing the Agent to automatically execute periodic tasks like report generation, data backup, and system monitoring without supervision.
Among the most popular tools, those that community users frequently use, provide the most feedback, and are prioritized based on Hermes's functional architecture and typical developer community needs include these several tools:
Hindsight is currently the most popular single tool within the ecosystem, and it is the long-term memory plugin officially recommended by Hermes. It automatically recalls relevant context before each LLM invocation, supports local PostgreSQL or cloud deployment, and has been integrated as a native Memory Provider into Hermes.
Anthropic-Cybersecurity-Skills is the highest-rated skill package within the ecosystem, featuring over 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-grade deployment.
Hermes Agent Self-Evolution is an evolutionary self-improvement technology that uses DSPy + GEPA to optimize skills, prompts, and code.
Hermes Workspace is the native workspace of Hermes, integrating chat interface, terminal, and skill manager, and is the most popular graphical entry point.
In addition, it can spawn independent sub-Agents, each with its own conversation context, independent terminals, and Python RPC scripts, thereby achieving zero context cost parallel pipelines.
In terms of infrastructure flexibility, it supports six types of terminal backends: local running, Docker, SSH remote, Daytona serverless, Singularity containers, and Modal cloud functions. Daytona and Modal will sleep when idle, with costs nearly zero. You can run it on a $5 VPS or GPU cluster, issuing commands via Telegram to let it work on cloud servers you never directly SSH into.
Hermes Agent currently competes most directly with OpenClaw, as both are open-source Agent frameworks aimed at developers.
The architectural philosophies of the two are completely different: OpenClaw's design core is a 'control plane', a unified long-running process responsible for managing sessions, routing, tool execution, and status, with everything flowing through this central controller. Hermes, on the other hand, centers around the execution loop of the Agent itself, building everything around this 'do, learn, improve' iterative cycle.
The differences between the two are especially significant in the skill system: OpenClaw's skills are mostly manually written, loaded from different levels such as workspace, personal, shared, or plugins; while Hermes's 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. A single command 'curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash' completes the installation, supporting 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, select your model provider (supporting Nous Portal, OpenRouter, OpenAI, or any custom endpoint), connect to your messaging platform (Telegram, Discord, Slack, or WhatsApp), and then start your first conversation. From the first interaction, Hermes Agent immediately enters learning mode, beginning to build memory, create skills, and become more capable after each session.
The core commands for daily use include:
hermes (start a conversation),
hermes model (choose LLM provider and model),
hermes tools (configure which tools to enable),
hermes gateway (start the message gateway, connect to platforms like Telegram, Discord, etc.),
hermes setup (run the complete 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 that require remembering context across sessions and continuously improving capabilities as a general-purpose AI assistant; 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 scenarios needing persistent assistants that maintain searchable conversation history and learned skills across platforms.
More specifically, you can chat with it on Telegram while having it execute tasks on a cloud VM, set up automations and push reports to any platform, let it take over periodic tasks; you can also connect it to Slack or Discord to provide AI collaboration support for the entire team; or utilize its tracking export feature to generate training data for the next generation of tool-calling model's RL training.