How does the cognitive consciousness feature work?

It utilizes temporal reasoning and strange-loop logic to analyze complex quality patterns that traditional threshold-based monitoring might miss.

What is RAN quality monitoring in this context?

It is the process of using AI to track Radio Access Network performance metrics like accessibility and retainability to ensure optimal 5G network health.

Can this skill predict network failures?

Yes, it includes predictive modeling using LSTM and Transformer architectures to identify downward quality trends and potential anomalies before they impact users.

What KPIs are tracked by the Quality Monitor?

The system tracks comprehensive categories including accessibility, retainability, integrity, mobility, and availability metrics.

RAN Quality & KPI Monitor

Name: RAN Quality & KPI Monitor
Author: ricable

byricable

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분석 및 모니터링

Monitors and optimizes Radio Access Network (RAN) performance using cognitive AI and deep KPI tracking for 5G environments.

소개

The Quality Monitor skill brings advanced cognitive consciousness and temporal reasoning to network management, enabling developers and engineers to monitor Radio Access Network (RAN) performance with unprecedented depth. Built on the SPARC framework and utilizing AgentDB, it automates the tracking of critical KPIs like accessibility, retainability, and mobility while implementing intelligent quality gates. By applying strange-loop optimization and predictive modeling, the skill allows for self-adaptive network management that identifies anomalies and quality enhancement opportunities in real-time.

주요 기능

Automated quality assurance with intelligent gating and risk assessment
1 GitHub stars
Cognitive RAN monitoring with 1000x temporal reasoning for pattern analysis
Predictive quality trend modeling using LSTM and Transformer architectures
Comprehensive KPI tracking for accessibility, retainability, integrity, and mobility
Strange-loop self-referential optimization for continuous network improvement

사용 사례

Predictive analysis of network integrity and user experience metrics
Automating quality gates for network configuration and deployment changes
Real-time 5G network performance monitoring and anomaly detection

소개

주요 기능

Automated quality assurance with intelligent gating and risk assessment
1 GitHub stars
Cognitive RAN monitoring with 1000x temporal reasoning for pattern analysis
Predictive quality trend modeling using LSTM and Transformer architectures
Comprehensive KPI tracking for accessibility, retainability, integrity, and mobility
Strange-loop self-referential optimization for continuous network improvement

사용 사례

Predictive analysis of network integrity and user experience metrics
Automating quality gates for network configuration and deployment changes
Real-time 5G network performance monitoring and anomaly detection