I spent about three weeks with MaxHermes before I felt like I could say anything useful about it, and I still feel like I'm only looking at part of the picture.
The skill generation behavior after tasks that involve multiple tool calls or self-correction. MaxHermes evaluates what it did and writes out a permanent skill file that persists across sessions. Subsequent tasks that match that pattern invoke the stored skill directly instead of reconstructing the workflow from scratch.
This is architecturally different from how most agent frameworks handle reusability. You typically get prompt templates, skill libraries you build manually, or retrieval-augmented approaches that pull relevant examples at runtime. Max crystallizes procedural memory from completed work automatically. The mechanism only fires after genuinely complex tasks by design, but when it does fire the resulting skill file becomes a first-class part of the agent's operating architecture.