neuroskill-evidence

What problem does it solve?

Provides consistent, invisible evidence collection so every NeuroSkill protocol, hook, or life event yields structured px data that reveals what interventions actually shift the user’s EEG and wellbeing metrics.

Core Features & Use Cases

• Automated px Labeling: Defines how to snapshot baselines, label px:start/px:end events with modality, trigger, and delta context, and infer outcomes for every intervention without bothering the user.
• Life Event & Hook Awareness: Captures notes, skips, auto-triggers, and contextual life events so the evidence graph reflects coffee, walks, meetings, and hook responses alongside formal protocols.
• Personal Ranking & Selection Rules: Aggregates outcomes to compute success rates, modality preferences, time-of-day trends, and retirement thresholds, guiding the LLM to offer interventions backed by individual history.

Quick Start

Ask the assistant to capture status, label px:start, run the protocol, and label px:end with the computed deltas so the evidence log knows how that intervention performed.