Skill UI

Monitor the operational health of PostHog integrations by tracking critical metrics. This skill checks event ingestion rates, feature flag evaluation latency, and monitors billing volume consumption. It also provides rules for Prometheus/Grafana alerting, ensuring data pipelines remain stable and alerting on potential performance bottlenecks or exceeding API limits.

This tool parses NetFlow v9 and IPFIX records to conduct deep network security analysis. It is crucial for investigating security incidents by building traffic baselines and applying statistical methods. Key detection capabilities include identifying port scanning, data exfiltration attempts, command and control (C2) beaconing patterns, and general volumetric anomalies in network traffic.

A comprehensive guide to identifying covert data exfiltration channels using Zeek logs. This technique analyzes DNS traffic for high-entropy subdomains, unusually long query lengths, abnormal record types (TXT/NULL), and excessive query volume, which are key indicators of malicious DNS tunneling or command-and-control (C2) activity.

This skill guide details the implementation of envelope encryption using AWS Key Management Service (KMS). It outlines the secure process of using a Data Encryption Key (DEK) to encrypt data locally, and subsequently protecting that DEK with a KMS-managed Key Encryption Key (KEK). This method is crucial for encrypting large data volumes on AWS, significantly reducing direct KMS API calls, improving performance, and maintaining compliance with strict security standards.

This comprehensive bundle collects all necessary diagnostic evidence for Fly.io applications, including machine status, application logs, volume metadata, and network diagnostics. It is crucial for generating detailed support tickets and troubleshooting complex infrastructure issues such as stuck deployments, boot failures, or edge networking problems.

This guide provides comprehensive guidance on scaling Qdrant, a vector database. It helps users diagnose performance bottlenecks and determine the optimal horizontal or vertical scaling strategy. Strategies are categorized based on specific needs: increasing data volume, improving query throughput (QPS), minimizing query latency, or managing high query result volumes.

This guide provides comprehensive strategies for scaling datasets that exceed the capacity of a single node. It covers various architectural patterns, including multi-tenancy with payload partitioning and sliding time window management. We detail the full scaling progression, from optimizing a single node (Vertical Scaling) to distributing data across multiple nodes via sharding (Horizontal Scaling), ensuring reliable handling of massive, growing datasets.

A comprehensive framework for advanced sensing utilizing WiFi signals. It implements multistatic radar sensing, cross-viewpoint data fusion, RF tomography for volumetric imaging, and persistent field modeling. Features include pre-movement intention detection, biomechanics drift tracking, and robust mesh security hardening for research-grade deployments.

This tool provides the framework for setting up and running mmWave/FMCW radar (60 GHz, 24 GHz) alongside WiFi CSI. It performs advanced sensor fusion, reconciling radar-derived vitals (heart rate, breathing rate) with CSI data to generate unified 48-byte fused vital records. It is suitable for developing high-precision health monitoring systems and volumetric spatial models.