Agent Skills by andregit2026
Showing 17 vetted skills indexed across 1 GitHub repositories.
andregit2026databricks-bundle-deploy
Package, validate, and deploy Databricks Asset Bundles across environments.
andregit2026databricks-jobs
Create, run, and monitor Databricks Jobs via CLI, Python SDK, or Asset Bundles.
andregit2026databricks-python-sdk
Guide Databricks automation using Python SDK, REST API, CLI, and Databricks Connect.
andregit2026databricks-data-engineering
Automate medallion architecture data pipelines in Databricks with Delta Lake.
andregit2026databricks-unity-catalog
Manage Unity Catalog catalogs, schemas, and tables with governance and naming conventions.
andregit2026databricks-testing
Test Databricks Python and SQL code against real clusters via MCP.
andregit2026databricks-genie
Create and manage Databricks Genie Spaces via natural language and the Conversation API.
andregit2026databricks-spark-structured-streaming
Develop Spark Structured Streaming pipelines for Kafka-to-Delta ingestion on Databricks.
andregit2026databricks-synthetic-data-generation
Generate realistic synthetic datasets with Faker and Spark for Databricks.
andregit2026databricks-ml-pipeline
Orchestrate end-to-end ML pipelines on Databricks from exploration to deployment.
andregit2026databricks-mlflow-evaluation
Orchestrate MLflow GenAI agent evaluations with scorers and trace datasets.
andregit2026databricks-model-serving
Deploy and query Databricks Model Serving endpoints for ML models and GenAI agents.
andregit2026databricks-aibi-dashboards
Design and deploy Databricks AI/BI dashboards with tested SQL queries.
andregit2026databricks-vector-search
Create and query Databricks Vector Search indexes for RAG and semantic search.
andregit2026databricks-dq-professionally
Register generic DQ rules and map them to table fields on Databricks.
andregit2026databricks-spark-declarative-pipelines
Build and update Databricks Lakeflow Spark Declarative Pipelines on serverless compute.
andregit2026databricks-dbsql
Document advanced Databricks SQL features including stored procedures, recursive CTEs, and materialized views.