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neuroskill-bci

Read real-time brain and biometrics data from the local NeuroSkill API.

Updated Apr 9, 2026
Search Tags:#real-time#coaching#biometrics#EEG#neuroskill#cognitive-state#brain-metrics
One-click install
npx skills add https://github.com/nadicodeai/argo-agent --skill neuroskill-bci-nadicodeai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: neuroskill-bci
Source: https://github.com/nadicodeai/argo-agent/tree/main/optional-skills/health/neuroskill-bci
Command: npx skills add https://github.com/nadicodeai/argo-agent --skill neuroskill-bci-nadicodeai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Connect Argo to a running NeuroSkill instance to read real-time brain and body metrics (focus, relaxation, mood, cognitive load, drowsiness, heart rate, HRV, sleep staging, and 40+ derived EXG scores) and integrate them into responses.

Core Features & Use Cases

  • Real-time metric ingestion: feed scores such as focus, relaxation, mood, cognitive_load, drowsiness, hr, hrv, sleep_stage, and EXG-derived markers into AI prompts.
  • Cognitively-aware coaching: provide tailored interventions and feedback based on live data.
  • Performance tracking: accumulate metrics over time to assess cognitive performance and recovery.
  • Use Case: During a focus block, Argo can adjust its replies based on user's focus and fatigue levels.

Quick Start

Connect NeuroSkill to the local app and verify that live metrics are feeding into responses.

Frequently Asked Questions about neuroskill-bci

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I incorporate real-time EEG and biometric data into AI coaching responses?▼

Real-time EEG and biometric data is incorporated into AI coaching responses by reading live scores like focus, cognitive load, and HRV from a local API to tailor interventions. This allows AI to adjust feedback based on the user's current physiological and cognitive state.

What cognitive and emotional states can real-time biometric monitoring track for productivity?▼

Real-time biometric monitoring can track focus, relaxation, mood, cognitive load, and drowsiness, alongside heart rate, HRV, and sleep staging. It utilizes 40+ derived EXG scores to provide a comprehensive view of the user's current cognitive and emotional state.

Can I use live brain metrics to adjust AI prompts during a focus block?▼

Yes, you can use live brain metrics to adjust AI prompts during a focus block. The system reads real-time focus and fatigue levels, allowing the AI to modify its replies and provide cognitively-aware interventions based on the user's current capacity.

How do I connect an AI assistant to a local NeuroSkill instance for live metric ingestion?▼

To connect an AI assistant for live metric ingestion, you link it to a running local instance and verify that real-time brain and body metrics are actively feeding into responses. This integration is guided by referencing local API documentation.

What is the best way to perform similarity searches on cognitive state data?▼

The best way to perform similarity searches on cognitive state data is by utilizing 128-D ZUNA embeddings. This technique processes the real-time biometric and EXG scores to find matching patterns, enabling the AI to reference relevant metrics and guide interventions.

Are there limitations when feeding sleep staging and EXG scores into AI prompts?▼

A key limitation is that feeding sleep staging and EXG scores requires a running local instance of the biometric app to provide the live API data. Without this local connection, the AI cannot access the real-time metrics needed to guide interventions.

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