hermes-second-brain

Instructions for the upstream workflow: A compounding knowledge layer for sessions — a goal layer, a retrieved knowledge layer and a history layer filter every response, and a harvest step writes the session's learnings back into the local vector store, so a new session starts from retrieved memory instead of a re-injected history. Use when repeated sessions should accumulate knowledge rather than restart. Not for governed memory with sensitivity, visibility and a promote or forget lifecycle — use memory-hub; not for caching model responses — use response-cache; not for measuring the injected context — use context-profiler.

Version

1.0.0

License

MIT