skill-system-insight

An AI agent learns user preferences by observing interaction patterns within sessions to extract behavioral facets and update a dual-matrix soul state. It then synthesizes a personalized user profile to guide more efficient and adaptive future interactions.

A dual-matrix soul state is an internal representation tracking personality and emotion facets derived from user behavior. This hybrid 3-layer architecture uses base profiles and synthesized profiles to store personalized adaptation data in agent_memories.

You can adapt collaboration style by asking the agent to run an insight pass, which analyzes session transcripts to identify communication patterns. The agent then updates its internal state to reflect preferences like directness or autonomy.

Yes, this Skill observes user interaction patterns within sessions to extract behavioral facets. It analyzes session transcripts to identify decision-making patterns and periodically synthesizes a user-specific profile for improved collaboration.

No, this skill operates with zero external dependencies. It uses an internal hybrid 3-layer architecture with base profiles, a dual matrix for personality and emotion, and synthesized profiles, storing all extracted data in agent_memories.

You should run an insight pass when you want the agent to learn from the current session and update its user profile. This helps the agent adapt to individual working styles, ensuring more efficient and personalized interactions in subsequent sessions.