body-emotion-sensor

To give an AI agent a persistent body-emotion state across sessions, you use a local runtime that stores state grounded in the Five Elements and Five Zang in workspace folders. This maintains authentic emotional context between turns.

A body-emotion state model grounded in the Five Zang and Five Elements is a persistent internal framework that translates user AnalysisInput into prompt tags like TURN_CHANGE_TAGS and BODY_TAG to generate authentic, long-running emotional context for AI agents.

You bootstrap an AI agent session with emotional context tags by generating a session bootstrap payload. This payload initializes BASELINE_PERSONA, BODY_TAG, and TURN_CHANGE_TAGS from the locally stored workspace state before processing turns.

Yes, maintaining AI agent emotional state locally requires the bes CLI runtime. It stores workspace state locally, supports optional visualization panels, and follows strict runtime contracts to prevent remote actions or automatic package installs.

Yes, you can visualize the body-emotion state of your AI agent during a session by enabling the optional visualization panel. This panel monitors the body state updates processed turn-by-turn by the local bes CLI runtime.

Limitations of using local workspace state for AI emotional context include strict runtime contracts that prohibit remote actions and automatic installs. Additionally, the system requires local workspace folders and the bes CLI runtime to function properly.