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neuroskill-search

Indexes EEG embeddings to search neural similarity across sessions and generate JSON/UMLAP metadata for downstream tools.

11|4|Updated Mar 3, 2026
Search Tags:#metrics#ann#umap#json-api#neural-search#eeg#session-comparison
One-click install
npx skills add https://github.com/NeuroSkill-com/skills --skill neuroskill-search
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: neuroskill-search
Source: https://github.com/NeuroSkill-com/skills/tree/main/skills/neuroskill-search
Command: npx skills add https://github.com/NeuroSkill-com/skills --skill neuroskill-search

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Mapping current EEG states to similar historical moments and comparing two sessions is tedious because all metrics and embeddings live across scattered history, so this skill surfaces relevant neighbors and delta trends automatically.

Core Features & Use Cases

  • Neural similarity search: The search command runs an ANN query over five-second embeddings, highlights temporal distributions and metrics, and lets you auto-range to the last session or specify exact start/end times.
  • Session comparison: The compare command averages metrics for two ranges, reports deltas with trend directions, flags improvements and declines, and enqueues a 3D UMAP projection for spatial state comparison.
  • Cross-modal follow-ups: After retrieving neighbors, bridge to screenshots, label search, or the interactive graph tool to contextualize similar focus states from other sensors.
  • Use Case: To track when you last reached a relaxed focus state, search your entire history for matching embeddings and then compare that session to today to see which metrics improved.

Quick Start

Ask the skill to search for the five closest EEG neighbors from your most recent block to see similar focus states.

Frequently Asked Questions about neuroskill-search

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

FAQPage Schema
How do I find similar EEG states across different recording sessions?▼

To find similar EEG states across sessions, you query historical neural embeddings using an ANN search. This surfaces matching temporal distributions and neighbor metrics automatically, eliminating manual history scans.

What is the best way to compare EEG metrics between two specific time ranges?▼

Comparing EEG metrics between two time ranges requires averaging the data and reporting deltas with trend directions. This process flags specific metric improvements and declines while enqueuing a 3D UMAP projection for spatial state comparison.

How does neural similarity search handle five-second EEG embeddings?▼

Neural similarity search handles five-second EEG embeddings by indexing them for ANN queries. You can specify exact start and end times or auto-range to the last session to retrieve the closest matching neighbor states.

Can I retrieve neural search results and UMAP metadata through a JSON API?▼

Yes, you can retrieve neural search results and UMAP metadata through a JSON API. The system exposes HTTP search and compare commands that return neighbor metrics, delta trends, and UMAP enqueue metadata for downstream tooling.

How do I contextualize EEG focus states with data from other sensors?▼

To contextualize EEG focus states with other sensors, you bridge the retrieved neural neighbors to screenshots, label search, or interactive graph tools. This cross-modal follow-up maps similar focus states from additional sensor data.

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