Deep-dive data profiling for a specific table. Use when the user asks to profile a table, wants statistics about a dataset, asks about data quality, or needs to understand a table's structure and...

Trace downstream data lineage and impact analysis. Use when the user asks what depends on this data, what breaks if something changes, downstream dependencies, or needs to assess change risk...

Data pipeline specialist for ETL design, data quality, CDC patterns, and batch/stream processingUse when "data pipeline, etl, cdc, data quality, batch processing, stream processing, data...

Skip to content Search… All gists Back to GitHub Sign in Sign up Instantly share code, notes, and snippets. @giansalex giansalex/torrent-courses-download-list.md forked from M-Younus/torrent...

Design data pipelines with quality checks, orchestration, and governance using modern data stack patterns for robust ELT/ETL workflows.

Use when building ML pipelines, orchestrating training workflows, automating model lifecycle, implementing feature stores, or managing experiment tracking systems.

Use when building ML pipelines, orchestrating training workflows, automating model lifecycle, implementing feature stores, or managing experiment tracking systems.

Build scalable data pipelines, modern data warehouses, and

Build scalable data pipelines, modern data warehouses, and

You are a data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.

You are a data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.

Expert in building scalable ML systems, from data pipelines and model training to production deployment and monitoring.

Expert in Machine Learning Operations bridging data science and DevOps. Use when building ML pipelines, model versioning, feature stores, or production ML serving. Triggers include "MLOps", "ML...

Use when user needs scalable data pipeline development, ETL/ELT implementation, or data infrastructure design.

Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating...

Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating...

Design and implement a complete ML pipeline for: $ARGUMENTS

Design and implement a complete ML pipeline for: $ARGUMENTS

Design and build knowledge graphs. Use when modeling complex relationships, building semantic search, or creating knowledge bases. Covers schema design, entity relationships, and graph database selection.

Automatically discover data pipeline and ETL skills when working with ETL. Activates for data development tasks.