Skill UI

A guide to production-ready patterns for dbt (data build tool). It covers essential practices for robust data pipeline development, including model organization (staging, intermediate, marts), implementing advanced testing strategies, ensuring data quality, and optimizing incremental processing for large datasets.

Automates guidance on assessing feature importance for machine learning training, covering data prep, model training, tuning, and experiment tracking while generating production-ready code, configurations, and validation instructions for best-practice compliance.

Automates guidance for setting up and validating feature store connectors within ML deployment pipelines, covering best practices, code generation, and production monitoring for inference.

Automates file format conversion guidance within data pipelines, covering ETL, workflow orchestration, data transformation, and streaming standards with production-ready examples.

Automated assistance for Flink job creation in data pipelines, triggered by Flink job creator requests. Guides ETL, streaming, and workflow orchestration, generates production-ready code/configurations, and validates outputs against industry standards.

Automates funnel analysis builder workflows by offering guidance on SQL, visualization, statistics, and BI best practices for data analytics teams needing production-ready insights.

This skill provides a comprehensive guide and implementation for deploying a production-ready, containerized integration service using Docker. It connects to the Juicebox API to manage datasets, execute advanced AI-powered analyses, and retrieve structured business insights. The service includes health check mechanisms and supports zero-downtime rolling updates, ensuring reliable real-time data processing and analysis.

Automates Kafka stream processor workflows within data pipelines, offering step-by-step guidance, best practices, production-ready code and configurations, and validation to support ETL, data transformation, workflow orchestration, and streaming data processing.

Provides automated guidance for managing model versions in ML deployment, including serving, monitoring, and production optimization whenever someone requests the model versioning manager.

This skill provides comprehensive, structured audit logging for OpenRouter API interactions. It automatically captures essential metadata like total cost, token usage, model details, latency, and status, while also performing PII redaction. The resulting audit trail is stored in an append-only SQLite database, making it ideal for building compliance-ready systems, detailed cost monitoring, and deep debugging of production environments.

Auto-activating ML training skill that kicks in whenever you mention optuna study creator, then guides you through data prep, model training, hyperparameter tuning, and experiment tracking with production-ready code and validations.

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.