databricks-solutions/lakebase-online-ml

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agent-evaluation Use this when you need to EVALUATE OR IMPROVE or OPTIMIZE an existing LLM agent's output quality - including improvin…

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analyzing-mlflow-session Analyzes an MLflow session — a sequence of traces from a multi-turn chat conversation or interaction. Use when the us…

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analyzing-mlflow-trace Analyzes a single MLflow trace to answer a user query about it. Use when the user provides a trace ID and asks to deb…

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apx Quick reference for building full-stack Databricks Apps with apx (React + FastAPI). Use when working on apx projects,…

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databricks-agent-bricks Create and manage Databricks Agent Bricks: Knowledge Assistants (KA) for document Q&A, Genie Spaces for SQL explorati…

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databricks-aibi-dashboards Create Databricks AI/BI dashboards. CRITICAL: You MUST test ALL SQL queries via execute_sql BEFORE deploying. Follow …

databricks-solutions/lakebase-online-ml

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databricks-app-apx Build full-stack Databricks applications using APX framework (FastAPI + React).

databricks-solutions/lakebase-online-ml

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databricks-app-python Builds Python-based Databricks applications using Dash, Streamlit, Gradio, Flask, FastAPI, or Reflex.

databricks-solutions/lakebase-online-ml

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databricks-asset-bundles Create and configure Databricks Asset Bundles (DABs) with best practices for multi-environment deployments.

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databricks-config Manage Databricks workspace connections: check which workspace you're connected to, switch workspaces, list available…

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databricks-dbsql >- Databricks SQL (DBSQL) advanced features and SQL warehouse capabilities. This skill MUST be invoked when the user …

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databricks-docs Databricks documentation reference. Use as a lookup resource alongside other skills and MCP tools for comprehensive g…

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databricks-genie Create and query Databricks Genie Spaces for natural language SQL exploration. Use when building Genie Spaces or aski…

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databricks-iceberg Apache Iceberg tables on Databricks — Managed Iceberg tables, External Iceberg Reads (fka Uniform), Compatibility Mod…

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databricks-jobs Use this skill proactively for ANY Databricks Jobs task - creating, listing, running, updating, or deleting jobs.

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databricks-lakebase-autoscale Patterns and best practices for using Lakebase Autoscaling (next-gen managed PostgreSQL) with autoscaling, branching,…

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databricks-lakebase-provisioned Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads.

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databricks-metric-views Unity Catalog metric views: define, create, query, and manage governed business metrics in YAML. Use when building st…

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databricks-mlflow-evaluation MLflow 3 GenAI agent evaluation. Use when writing mlflow.genai.evaluate() code, creating @scorer functions, using bui…

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databricks-model-serving Deploy and query Databricks Model Serving endpoints.

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databricks-parsing Parse documents (PDF, DOCX, PPTX, images) using ai_parse_document, or build custom RAG pipelines. Use when the user a…

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databricks-python-sdk Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with da…

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databricks-spark-declarative-pipelines Creates, configures, and updates Databricks Lakeflow Spark Declarative Pipelines (SDP/LDP) using serverless compute.

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databricks-spark-structured-streaming Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, im…

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databricks-synthetic-data-gen Generate realistic synthetic data using Spark + Faker (strongly recommended).

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databricks-unity-catalog Unity Catalog system tables and volumes. Use when querying system tables (audit, lineage, billing) or working with vo…

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databricks-unstructured-pdf-generation Generate synthetic PDF documents for RAG and unstructured data use cases. Use when creating test PDFs, demo documents…

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databricks-vector-search Patterns for Databricks Vector Search: create endpoints and indexes, query with filters, manage embeddings. Use when …

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databricks-zerobus-ingest Build Zerobus Ingest clients for near real-time data ingestion into Databricks Delta tables via gRPC.

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instrumenting-with-mlflow-tracing Instruments Python and TypeScript code with MLflow Tracing for observability. Must be loaded when setting up tracing …

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mlflow-onboarding Onboards users to MLflow by determining their use case (GenAI agents/apps or traditional ML/deep learning) and guidin…

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querying-mlflow-metrics Fetches aggregated trace metrics (token usage, latency, trace counts, quality evaluations) from MLflow tracking serve…

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retrieving-mlflow-traces Retrieves MLflow traces using CLI or Python API.

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searching-mlflow-docs Searches and retrieves MLflow documentation from the official docs site.

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spark-python-data-source Use when building custom Spark data source connectors for external systems (databases, APIs, message queues), impleme…

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