Observed Signal · Sep 6, 2026 · Technical Release · Source: DEV Community · Impact: 3/5 · Sentiment: Positive
Hermes Command Cheat Sheet Updated for Real Usage
This article provides an updated cheat sheet for the Hermes agent, a product by Nous Research, focusing on new commands for session management, controlling active work, setting goals and loops, model behavior, skills/memory, automation, and debugging. It highlights the difference between similar commands like /goal, /heartbeat, /loop, and /cron, and offers terminal essentials. The guide is based on the official source code and a community cheat sheet, aiming to help users leverage the agent's full potential in daily workflows.
The article provides a detailed overview of new commands for an AI agent platform, highlighting features that enhance workflow automation and control. While it doesn't announce a new product launch, it is informative for the AdTech/AI community interested in agent capabilities, but it lacks industry-specific impact.
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Key Takeaways & Evidence Grounding
- Hermes agent v0.20.6 commands are documented.
- New control commands include /queue, /steer, /bg, and /btw.
- Automation commands include /cron, /suggestions, /blueprint, and /kanban.
- The cheat sheet is compiled by Nokka and references HermesWatcher on X.
- Commands are verified against the Hermes source code on GitHub.
Ontology Mapping & Concepts
Related Market Signals & Shifts
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Hermes Agent Desktop: Getting Started Guide
This MarTech how-to outlines installing and using Hermes Agent Desktop, a cross-platform agent runtime and GUI for local LLM-driven marketing workflows. The guide explains the local "context store" (conversation history, embeddings, tool outputs), connecting provider-agnostic models (OpenAI, Anthropic, Google, Meta, self-hosted LLaMA) via API keys, and recommends OpenRouter as an easy multi-model gateway. It describes creating reusable "skills" (via a /learn command or by placing Markdown files in a Skills folder), running tasks through the chat UI, verifying stored data on disk, and optional scaling options (CLI, Docker, or remote API server) for team deployments. The piece stresses that context remains under user control and that skills and conversation assets are portable across model providers. Published 2026-07-08.
Hermes Agent: Self-Hosted AI Assistant Guide
Hermes Agent is an open-source, model-agnostic, self-hosted AI assistant from Nous Research that runs on local machines or low-cost VPS instances. It operates via a CLI and messaging gateway, separates conversation from execution, and uses tools, skills, and file-based memory to persist and improve behavior over time. The project provides a one-line installer for Linux/macOS/WSL2, supports termux on Android, and exposes commands for model selection, tool toggles, setup, updates, and diagnostics (e.g., hermes model, hermes tools, hermes setup, hermes doctor). Configuration and state live under ~/.hermes with support for profiles. Hermes supports multiple terminal execution backends (local, docker, ssh, modal, daytona, singularity) and a messaging gateway for multi-platform access, and is distributed under the MIT license.
Hermes Agent: Open-Source Self‑Improving AI Agent
This developer-focused article reviews Hermes Agent, an open-source autonomous AI agent built by Nous Research. The piece highlights Hermes Agent’s design priorities—persistent cross-session memory, reusable procedural skills, broad built‑in tool access (60+ tools depending on configuration), and support for multiple runtime backends (local, Docker, SSH, Daytona, Singularity, Modal). It describes fast onboarding (one-line installer and recommended hermes setup --portal flow), example developer workflows (research pipeline with search, extraction, summarization, and memory), trade-offs around complexity and observability, and why the project is worth watching as an agent framework that aims to improve over repeated use. The article is a submission to the Hermes Agent Challenge and includes links to official docs and the GitHub repo.
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