What database does hy-regime use for storage?

It uses DuckDB, an in-process SQL OLAP database, to store message batches and regime transition history for persistence and querying.

How does the GF(3) triadic bucketing work?

It classifies every message into one of three states (-1, 0, +1) across three dimensions (semantic, temporal, structural) to maintain a balanced mathematical model for prediction.

Do I need to know Hylang to use hy-regime?

While the skill is built with Hylang (a Lisp dialect for Python), Claude handles the execution; however, basic Lisp knowledge helps for customizing analysis scripts.

Is this suitable for real-time message alerts?

It is optimized for batch processing (typically 69 messages at a time) rather than single-message real-time triggers, making it better for trend analysis.

What is a 'regime' in the context of this skill?

A regime is a specific pattern of communication behavior, such as a 'Burst' (concentrated activity) or 'Scattered' (distributed activity), identified through temporal and semantic analysis.

Hylang Message Regime Analyzer

Name: Hylang Message Regime Analyzer
Author: plurigrid

byplurigrid

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Data Science & ML

Analyzes and predicts message stream patterns using triadic GF(3) classification and Hylang-based regime detection.

hy-regime is a sophisticated tool for multivariate analysis of message batches, utilizing the Hylang Lisp dialect to classify data across semantic, temporal, and structural dimensions. It implements a GF(3) triadic balance to identify communication regimes—such as burst, scattered, or biphasic patterns—and provides predictive momentum modeling for future message distributions. This skill is ideal for developers and researchers needing to detect behavioral shifts in communication streams, maintain structural stability in large datasets, and perform deep meta-analysis of group dynamics through persistent DuckDB storage.

Key Features

018 GitHub stars

02High-performance Hylang implementation for expressive data transformation and logic

03Automatic detection of communication regimes including Burst, Scattered, and Biphasic

04Integrated DuckDB storage for persistent regime transition tracking and analysis

05Triadic GF(3) classification across semantic, temporal, and structural dimensions

06Predictive momentum modeling for forecasting next-batch message distributions

Use Cases

01Analyzing large-scale chat logs to detect shifts in community engagement or focus

02Monitoring communication streams for anomalies or deviations from established patterns

03Predicting upcoming message volume and content types based on recent behavioral momentum

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi hy-regime

For use in Claude.ai and ChatGPT

Download Skill