How Hermes Writes Agent Learning into Files: A Three-Layer Design of Memory, Skills, and Knowledge Base

The Hermes Agent open-sourced by Nous Research externalizes learning into files, using MEMORY.md and USER.md to store memory, SKILL.md to store reusable skills, and a wiki to store domain knowledge, while the underlying model weights remain unchanged. The article breaks down its closed-loop learning mechanism, including post-task background review that automatically creates and improves skills. The built-in llm-wiki skill 2.1.0 maintains the knowledge base with a three-layer structure of raw/, wiki, and SCHEMA.md, along with disciplines such as page-creation thresholds, bidirectional links, source-text hashing, and contradiction registration, and comes with an inspection mechanism.