Skill UI

Automates dashboard layout planning for data analytics tasks, guiding best practices, generating robust configs, and validating layouts for SQL-driven BI scenarios.

Guides ML training teams through data augmentation pipelines, offering best practices, code/config generation, validation, and experiment-tracking support so pipelines stay production-ready.

Automated guidance for data normalization tool tasks in ML training, offering best practices, production-ready code/configuration generation, and output validation.

A specialized skill for optimizing database performance and scalability across PostgreSQL and MySQL. It guides users through analyzing slow queries, interpreting execution plans (EXPLAIN ANALYZE), designing optimal indexing strategies, tuning configuration parameters, and resolving bottlenecks like lock contention. Essential for DevOps engineers, database administrators, and backend developers.

Offers automated guidance for database query profiler tasks in performance testing, including best practices, code/config generation, and validation when working with load/stress benchmarking.

Automates database-focused test work by offering best-practice guidance, fixtures, and configurations for unit, integration, and mocking scenarios in test automation workflows.

A comprehensive guide detailing the setup process for Databricks CLI v2 and Python SDK. It covers essential steps for connecting to various Databricks workspaces, including configuring Personal Access Tokens (PAT), interactive OAuth U2M flows, and secure OAuth M2M service principals for CI/CD pipelines. Essential for developers integrating Databricks into their projects.

A comprehensive guide detailing optimization techniques for Databricks environments. It covers optimal cluster sizing for various workloads (ETL, ML, Streaming), advanced Spark configurations (AQE, memory management), and deep data optimization strategies for Delta Lake, including Z-Ordering and Liquid Clustering. It also provides methods for query plan analysis and join optimization.

This skill provides a comprehensive guide to configuring event-driven workflows and robust notification systems for Databricks jobs. It covers setting up various notification destinations (Slack, Teams, Email, PagerDuty) and triggering alerts based on job lifecycle events (success, failure, start). Furthermore, it demonstrates advanced monitoring using system audit tables and creating automated SQL alerts for critical data pipeline monitoring.

This guide provides essential best practices for building reliable, fault-tolerant applications in Go using DBOS durable workflows. It covers architectural patterns for integrating DBOS into existing Go code, defining complex workflows, managing steps, and utilizing queues for robust concurrency control. Essential reading for developers setting up, configuring, or testing mission-critical asynchronous processes.

Guides you through generating dbt models inside data pipelines, covering setup, code generation, configuration, and validation while following best practices for ETL, orchestration, and streaming workloads.

Provides comprehensive instructions for deploying Deepgram transcription services into various production environments. This guide covers building production-ready Docker images, configuring Docker Compose, setting up robust Kubernetes manifests (including HPA and secrets), and implementing serverless handlers for platforms like AWS Lambda. Essential for scaling Deepgram services reliably and securely in the cloud.