Skill UI

A powerful toolset for automating core PostHog product analytics tasks via Rube MCP. It enables developers and analysts to capture user events, list and filter event data, manage feature flags (creation, retrieval, listing), and inspect user profiles. Ideal for integrating advanced product tracking and A/B testing workflows directly into development pipelines.

This expert tool guides users through rigorous statistical analysis, specializing in A/B testing, hypothesis testing, and interpreting experimental results. It helps define sample sizes, executes appropriate tests (Z-test, T-test, Chi-square), and critically distinguishes between 'statistical significance' and 'practical significance' to ensure data-driven decision-making for product and business strategy.

This skill automatically generates an interactive SQL Notebook designed to validate changes in dbt models or snapshots. It processes changes identified from a GitHub PR or local repository, generating comparison queries that compare 'before' (production) and 'after' (development) data states. It is essential for embedding data observability and quality checks into CI/CD pipelines.

This tool opens the dedicated Context Mode Insight dashboard in your default browser. Insight serves as the central analytics layer for AI-assisted engineering teams, providing crucial metrics such as per-engineer productive rates, identifying retry waste, detecting blockers, and offering role-narrowed performance views. It is designed to be the single source of truth for comprehensive team performance monitoring and sign-in details.

Run and analyze molecular dynamics simulations using OpenMM and MDAnalysis. Set up protein/small molecule systems, define force fields, perform energy minimization, NVT equilibration, production MD, and analyze trajectories including RMSD, RMSF, contact maps, and free energy surfaces.

This skill provides the core mechanism for integrating Hex into external data pipelines. It enables triggering, monitoring, and managing Hex projects (e.g., via Airflow or Dagster) programmatically. Users can implement parameterized runs, execute multi-step ETL workflows sequentially, and handle status polling and error management, making it ideal for production data orchestration.

This skill provides comprehensive methods and code examples for optimizing spending on Bright Data services. It covers product selection (Proxy vs. API), implementing caching strategies, bulk usage monitoring, and setting budget alerts, ensuring cost efficiency in large-scale web scraping projects.

This guide provides production-ready patterns for integrating with Bright Data proxy services. It covers critical aspects like setting up a proxy client, implementing robust retry logic for transient errors (e.g., 502, 503), managing sticky sessions for consistent IPs, and parsing complex HTML responses. Essential for building reliable, high-scale web scrapers using TypeScript and Python.

This comprehensive checklist guides users through critical operational readiness steps for a ClickHouse production deployment. It covers server tuning (config.xml), schema design best practices, robust backup strategies (S3), detailed monitoring setup (Prometheus/Grafana), security hardening, and application integration verification. Use this document before go-live, during major upgrades, or when auditing production systems to ensure maximum stability and performance.

This comprehensive guide details best practices for securing a ClickHouse deployment. It covers essential security measures including role-based access control (RBAC) for granular user permissions, implementing row-level security for multi-tenancy, configuring network IP restrictions, enabling TLS encryption, and setting up detailed audit logging. Use this when hardening a production ClickHouse instance or enforcing strict data governance.

This expert acts as a dedicated data analysis partner for Product Managers. It helps users explore data, write complex queries (e.g., SQL, BigQuery), analyze key metrics, and create structured dashboards. Use this tool when you need to derive actionable insights from complex datasets, compare user cohorts, or understand product performance trends to inform critical business decisions.

Provides a comprehensive checklist for deploying Hex data analytics integrations into production. It covers critical operational best practices, including API key management, rate limit handling, error resilience (circuit breakers, exponential backoff), and robust monitoring strategies. This guide ensures that data pipelines are deployed reliably, minimizing downtime and guaranteeing consistent, high-quality data reporting for go-live scenarios.