Assess user cognitive readiness from a 14-dimension state vector and timing metrics.
npx skills add https://github.com/brian-wijaya/dotfiles --skill sense-user
Please help me install this Agent Skill. Skill: sense-user Source: https://github.com/brian-wijaya/dotfiles/tree/main/.claude/skills/sense-user Command: npx skills add https://github.com/brian-wijaya/dotfiles --skill sense-user
This skill helps AI assess a user's cognitive readiness before taking significant actions.
Before initiating a major action, retrieve the 14-dimension state vector with mcp__somatic-fusion__get_state_vector and tailor your guidance based on the user's detected engagement.
High-intent search queries and answers about installing and using this skill.
Assess user cognitive readiness by retrieving a 14-dimension state vector capturing mouse activity, typing rhythm, and engagement indicators. The AI queries somatic sensors to gauge user state before high-stakes tasks, calibrating its approach based on detected engagement levels.
AI guidance calibration adapts response timing and complexity based on real-time user state vectors. It uses somatic sensors tracking mouse dynamics, typing rhythm, and dwell time to determine whether to proceed, pause, or seek confirmation during complex operations.
Detect user engagement levels by analyzing somatic input timing and pointer dynamics. The system collects a 14-dimension state vector measuring mouse activity and typing rhythm, enabling the AI to adjust its guidance strategy for risky tasks.
Yes, gauging user state requires somatic sensors. The skill relies on somatic-fusion, somatic-input-timing, and somatic-pointer modules to produce the 14-dimension state vector and timing metrics necessary for calibrated AI guidance.
Use user state assessment before major actions, large refactors, or risky tasks where user engagement directly influences the appropriate approach. It is essential for complex operations requiring calibrated guidance based on real-time cognitive readiness.
The 14-dimension user state vector captures mouse activity, typing rhythm, dwell time, and engagement indicators. These metrics combine with input timing data to produce a comprehensive assessment of user cognitive readiness for calibrated AI guidance.
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