neuroskill-labels

Create timestamped EEG text annotations and search them semantically with HNSW embeddings.

11|4|Updated Mar 3, 2026
One-click install
npx skills add https://github.com/NeuroSkill-com/skills --skill neuroskill-labels
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: neuroskill-labels
Source: https://github.com/NeuroSkill-com/skills/tree/main/skills/neuroskill-labels
Command: npx skills add https://github.com/NeuroSkill-com/skills --skill neuroskill-labels

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill removes the friction of annotating EEG sessions and tracking past states by capturing labels, searching them semantically, and surfacing related EEG moments, labels, and screenshots in one query.

Core Features & Use Cases

  • Timestamped annotations: use the label command to capture descriptive text, optional context, and precise Unix seconds for every EEG moment worth remembering.
  • Semantic search: run search-labels to compare queries against HNSW embeddings for short text, long context, or both while viewing similarity, EEG metrics, and hidden context fields.
  • Interactive graph search: combine text labels, EEG neighbors, nearby labels, and screenshots into a cross-modal five-layer graph with DOT, JSON, and SVG outputs for exploration.

Quick Start

Ask the neuroskill-labels tool to label meditation start and then search for deep focus to discover related EEG moments, annotations, and screenshots.

Frequently Asked Questions about neuroskill-labels

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

FAQPage Schema
How do I label and annotate EEG brain states with text and timestamps?

You can label EEG brain states by capturing descriptive text, optional context, and precise Unix seconds for every session moment. This creates timestamped annotations that streamline tracking and correlating past brain states with EEG metrics.

Can I perform semantic search over past EEG annotations and contexts?

Yes, semantic search compares queries against HNSW embeddings for short text, long context, or both. This search retrieves matching EEG moments, displaying similarity scores, EEG metrics, and hidden context fields.

What is the best way to link EEG metrics, text labels, and screenshots together?

The best way to link these elements is an interactive five-layer graph search. It combines text labels, EEG neighbors, nearby labels, and screenshots into cross-modal outputs available in DOT, JSON, and SVG formats for exploration.

Does this EEG labeling tool require dependencies to start annotating sessions?

No dependencies are required. You can immediately capture labels, search past experiences semantically, and correlate results with screenshots and EEG embeddings within NeuroLoop scenarios without prior environment setup.

Why use HNSW for searching EEG text annotations instead of standard keyword search?

HNSW dual-index search enables semantic similarity matching rather than exact keyword matching. This surfaces related EEG moments and annotations even when query text differs from the original label descriptions.

How do I search EEG data for deep focus states after labeling meditation start?

Run a semantic search-labels query for deep focus after creating your initial timestamped labels. The HNSW search compares your query against existing EEG embeddings and text annotations to discover related brain states.