AI tools for “data”

Read a single Databricks notebook (.ipynb / .py / .scala source format) and produce a migration-readiness report — what it does, what it depends on, what risks the migrator will hit, which gotchas (from…

Reviews DataHub connector implementations against 22 golden standards for compliance, code quality, silent failures, test coverage, type design, and merge readiness. Use when reviewing connector code, checking a PR,…

…or deploy an AI agent (not a predictive model) to DataRobot; mentions agent_spec.yaml, dr-assist, datarobot-agent-assist, dress rehearsal, swarm simulation, or the DataRobot agent template; wants to scaffold a…

Databricks Sandbox: on-demand serverless compute for running untrusted or agent-generated code and background tasks. Create/start/stop/delete sandboxes, run commands (synchronous execute_command_sync in all SDKs;…

…or diagnoses a uv-managed local Python .venv with `databricks environments setup-local`. Use when the user wants to set up or fix one for Databricks Connect, cluster or serverless compute, `--job-task`, or a…

Train ML models on Databricks. Use for: classification/regression/deep-learning (XGBoost, scikit-learn, LightGBM, PyTorch) with Optuna, @prod/@challenger aliases, batch scoring (spark_udf for plain models,…

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.

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,…

End-to-end dataset curation for FiftyOne: inspect schema and quality, audit annotations, analyze class distributions, explore embeddings, find duplicates, create curated subsets, and build train/val/test splits. Works…

…the user wants to assess whether an AI agent repository (DataRobot-built or not) is enterprise-ready, run a gap analysis / readiness scan against security, governance, reliability, or regulatory standards, score an…

Inspect Preset workspace datasets, database metadata, schemas, tables, columns, metrics, and dataset/database workflow routing through direct Superset API calls. Use only for direct API workflows; Do not use for…

…direct route for a single app with no hub, while store-metadata-writer is the one to prefer when a hub holds the profile and both stores have to stay consistent. It does NOT upload (play-store-deliver does), and does…

Audit and update metadata across multiple AEM Edge Delivery Services pages. Scans pages via the query index, identifies missing or inconsistent metadata (titles, descriptions, og tags, robots), and generates a corrected…

Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.

Migrate Databricks workloads from classic compute to serverless compute. Use when migrating notebooks, jobs, pipelines, or Scala JARs (`spark_jar_task`) from classic clusters to serverless, checking if existing code is…

Scaffold a new DataHub Micro Frontend (MFE) app with all boilerplate files. Use when the user wants to create a new micro frontend, MFE, remote app, or Module Federation app for DataHub.

Inspect or route Preset database connection configuration, validation, OAuth, upload, create, update, and delete workflows through direct Superset API calls. Use only for direct API workflows; Do not use for MCP-only…

Create Databricks AI/BI dashboards. Must use when creating, updating, or deploying Lakeview dashboards as Databricks Dashboard have a unique json structure. CRITICAL: You MUST test ALL SQL queries via CLI BEFORE…

Lakeflow Connect managed ingestion into Unity Catalog from databases (SQL Server, PostgreSQL, MySQL, Oracle) by CDC or query-based. Use when creating, running or debugging these pipelines.

Unity Catalog metric views: define, create, query, and manage governed business metrics in YAML. Use when building standardized KPIs, revenue metrics, order analytics, or any reusable business metrics that need…