Skill UI

Aggregates performance metrics from applications, systems, databases, caches, queues, and external services into a central platform, helping teams define a consistent taxonomy, choose aggregation tools, and create dashboards and alerts for faster monitoring and troubleshooting.

Auto-activating aggregation helper skill for data analytics, following best practices for SQL, visualization and BI workflows, guiding queries/configs, and validating outputs.

This guide provides comprehensive patterns and best practices for working with ClickHouse, a high-performance OLAP database. It covers advanced topics such as MergeTree engine design, efficient query optimization (filtering, aggregations, window functions), bulk/streaming data ingestion, materialized view creation, and performance monitoring techniques, ensuring optimal performance for large-scale analytical workloads.

This comprehensive guide outlines the end-to-end process of building production-grade ETL data pipelines using Databricks and Delta Lake. It implements the robust Medallion Architecture (Bronze, Silver, Gold) for scalable data management. Techniques covered include Auto Loader for incremental streaming ingestion, MERGE INTO for upsert semantics, data cleansing, and advanced aggregation into analytics-ready layers. Ideal for establishing reliable data pipelines in a data lakehouse environment.

This skill acts as an expert guide for implementing comprehensive monitoring and observability solutions. It covers setting up the three pillars of observability—metrics, distributed tracing, and log aggregation—along with defining monitoring architecture, creating actionable dashboards, and establishing effective alerting runbooks. Use it to achieve full visibility into system health, reduce MTTR, and ensure proactive issue detection.

An expert guide for performing complex data analysis, cleaning, and transformation using pandas DataFrames. This skill covers advanced techniques such as vectorized operations, efficient merging, time series resampling, group-by aggregations, and memory optimization, ensuring production-grade code and robust data validation.

Automates deployment and configuration of ELK, Loki, or Splunk log aggregation platforms by gathering requirements, crafting secure scalable configs, and producing deployment code for observability needs.

Use this resource to implement comprehensive end-to-end monitoring and observability for Supabase projects. It guides users through analyzing API metrics, diagnosing slow database queries using pg_stat_statements, managing log drains for external aggregation, and setting up custom alerts, ensuring optimal project health and performance.

A comprehensive technical reference for implementing advanced Lightning Network channel factories. It covers complex topics such as multi-party channels, Layer 2 scaling on Bitcoin, and advanced protocols including Decker-Wattenhofer invalidation trees, MuSig2 key aggregation, and encrypted Noise NK transport. Essential for developers building highly scalable and secure Bitcoin infrastructure.

This expert assists developers in building type-safe, high-performance database layers using Drizzle ORM with TypeScript. It provides deep knowledge of schema design, complex relational querying (joins, aggregations), managing migrations via Drizzle Kit, and seamless integration with modern stacks like Next.js, tRPC, and serverless environments. Ideal for developers needing a zero-overhead, type-safe ORM alternative.

This guide details the deployment and configuration of MISP (Malware Information Sharing Platform) using Docker. It demonstrates how to aggregate, correlate, and distribute threat intelligence from diverse sources like abuse.ch and AlienVault OTX. Learn automated feed synchronization, STIX/TAXII integration, and connecting the platform to SIEM and SOAR tools like Splunk and Elasticsearch for centralized IOC management.

This skill enables users to analyze uploaded Excel and CSV files using DuckDB. It supports schema inspection, SQL querying, statistical summaries, and exporting results to various formats. Ideal for data exploration, aggregation, and structured data processing tasks.