Hermes Agent treats skills as the default way to teach repeatable workflows. Official documentation describes them as on-demand knowledge documents aligned with the open agentskills.io shape, loaded through progressive disclosure so the model sees a small index first and only pulls full instructions when a task actually needs them.

Authoring is less about clever wording than about packaging —you are telling the runtime when to load a procedure, what order of steps counts as “done,” and how to tell success from a silent failure. This article stays focused on SKILL.md structure, supporting folders, visibility rules, and the split between secrets and non-secret settings—the details that decide whether a skill shows up in /slash commands, survives a hub install, or quietly disappears on CI.

Hermes sits inside the broader AI Systems: Self-Hosted Assistants, RAG, and Local Infrastructure cluster, where assistants are treated as systems built from inference, retrieval, memory, and tooling rather than as a single…