AI tools for “ui”

…skill (it routes to Genie One). Contains up-to-date guidelines for Databricks-related CLI…

Build apps on Databricks Apps platform. Use when asked to create data apps, analytics tools, or custom interactive visualizations. A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use…

…explore, and query Databricks data via Genie — the CLI equivalent of the Genie One MCP. MUST be invoked whenever the user asks to find or locate data ('what tables are in X', 'where does X live', 'which…

…and manage governed business metrics in YAML. Use when building standardized KPIs, revenue metrics, order analytics, or any reusable business metrics that need consistent definitions across teams and…

MLflow GenAI evaluation and agent improvement on Databricks. Use when running mlflow.genai.evaluate(), building scorers or datasets, aligning judges with MemAlign, optimizing prompts, or monitoring production quality.

Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.

…(formerly Delta Live Tables) on Databricks. Use when building batch or streaming data pipelines with Python or SQL, including Auto CDC from event streams or periodic complete snapshots. Invoke BEFORE starting…

…fixes for the serverless Spark Connect architecture and guides the full migration. Not for classic DBR version upgrades or cluster configuration changes within classic…

…— mapped to concrete AppKit components. Use when BUILDING or reviewing the UI of an AppKit/React app that displays data or answers data questions: choosing genre, layout, charts, KPIs, semantic color, required…

…test ALL SQL queries via CLI BEFORE deploying. Follow guidelines…

Use Databricks built-in AI Functions (ai_classify, ai_decide, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment, ai_similarity, ai_parse_document, ai_prep_search, ai_query,…

Build custom Python data sources for Apache Spark using the PySpark DataSource API — batch and streaming readers/writers for external systems. Use this skill whenever someone wants to connect Spark to an external system…

…(or the project-local equivalent), and keep the token out of opencode.json. Use when the user wants to set up Dash0, enable telemetry, paste credentials, change the team or dataset,…

…Metric Views, and documents in UC volumes. Use when building, migrating, tuning, or asking a specific Agent, and for document Q&A or docs + data agents (replaces the legacy Knowledge Assistant and Supervisor…

IDMP panel build workflow. Resolve owner, reserve names, create panel objects, verify query and SQL output, place panels into dashboards, and clean up safely.

IDMP data import/export skill. Use it to inspect exportable root elements, review import/export records, download artifacts, and distinguish package export, artifact download, and import flows.

…panels, create analyses or panels from prompts, and distinguish chat recording from draft recommendation usage…

…use action words like "create", "scaffold", "new", or "build" together with "Datadog App" or "@datadog/apps" or "npm create @datadog/apps". Do NOT use for any question that does not involve creating a new project…

Build RAG / unstructured-document evaluation datasets and demo documents (e.g. for a Genie Agent with an attached volume) on Databricks: generate synthetic PDFs locally, upload to Unity Catalog volumes, and pair each…

Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, working with Kafka ingestion, implementing Real-Time Mode (RTM), configuring triggers (processingTime,…