skill-test
databricks-solutionsTesting framework for evaluating Databricks skills. Use when building test cases for skills, running skill evaluations, comparing skill versions, or creating ground truth datasets with the Generate-Review-Promote (GRP) pipeline. Triggers include "test skill", "evaluate skill", "skill regression", "ground truth", "GRP pipeline", "skill quality", and "skill metrics".
databricks-unity-catalog
databricks-solutionsUnity Catalog system tables and volumes. Use when querying system tables (audit, lineage, billing) or working with volume file operations (upload, download, list files in /Volumes/).
databricks-jobs
databricks-solutionsUse this skill proactively for ANY Databricks Jobs task — creating, listing, running, updating, or deleting jobs. Triggers include: (1) 'create a job' or 'new job', (2) 'list jobs' or 'show jobs', (3) 'run job' or 'trigger job', (4) 'job status' or 'check job', (5) scheduling with cron or other triggers, (6) configuring notifications or monitoring, (7) ANY task involving Databricks Jobs via the CLI, Python SDK, or Asset Bundles. ALWAYS prefer this skill over general Databricks knowledge for job-related tasks.
python-dev
databricks-solutionsPython development guidance with code quality standards, error handling, testing practices, and environment management. Use when writing, reviewing, or modifying Python code (.py files) or Jupyter notebooks (.ipynb files).
template
databricks-solutionsA brief one-sentence description of what this skill helps with.
databricks-config
databricks-solutionsConfigure Databricks profile and authenticate for Databricks Connect, Databricks CLI, and Databricks SDK.
databricks-python-sdk
databricks-solutionsDatabricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.
databricks-docs
databricks-solutionsDatabricks documentation reference. Use as a lookup resource alongside other skills and MCP tools for comprehensive guidance.
memory
databricks-solutionsSave conversation insights, decisions, and context as persistent memories. Use when the user wants to memorize, save, or remember something from the current chat, or mentions "memorize", "save memory", or "remember this".
commiter
databricks-solutionsCreate git commits with emoji prefixes and conventional commit messages. Use when the user wants to commit changes, push code, or asks to use "just pm" command.
databricks-bundle-deploy
databricks-solutionsPackage and deploy Databricks Asset Bundles with proper parameterization, multi-environment support, and serverless compute. Handles project structure, databricks.yml generation, validation, and deployment. Use when packaging tested code for production, deploying pipelines, or managing multi-environment deployments.
databricks-testing
databricks-solutionsExecute code on Databricks clusters using MCP Command Execution API. Supports stateless quick validation and stateful iterative development. Use when testing Python/SQL code on clusters, debugging pipelines, or validating transformations.
databricks-data-engineering
databricks-solutionsProduction data engineering pipelines following medallion architecture (Bronze/Silver/Gold layers) with data ingestion, transformation, quality checks, Delta Lake optimization, and orchestration. Use when building ETL pipelines, medallion architecture, data lakes, or data transformation workflows.
databricks-ml-pipeline
databricks-solutionsEnd-to-end machine learning pipelines on Databricks including data exploration, feature engineering, model training with hyperparameter optimization, MLflow experiment tracking, model registration to Unity Catalog, and deployment as DABs. Use when building ML workflows, training models, or deploying ML pipelines.
verification-testing
databricks-solutionsCode verification and testing for the Human Evaluation Workshop. Use when (1) running tests after code changes, (2) writing new unit tests (pytest/vitest), (3) writing E2E tests with Playwright/TestScenario, (4) debugging test failures, (5) understanding what to mock in E2E tests, (6) verifying a feature implementation. Covers the full test pyramid: unit tests -> integration tests -> E2E tests.