AI tools for “data”

Tools and guidance for model explainability, prediction explanations, feature impact analysis, SHAP values, SHAP distributions, anomaly assessment, and model diagnostics. Use when analyzing model explanations, feature…

…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…

…discovery, feature importance analysis, and understanding DataRobot's automated feature engineering capabilities. Use when working with feature engineering, feature discovery, or analyzing feature importance in…

Create, upload to, mount and read a Domino Dataset; take, list, read or restore (copy to a new Dataset) a snapshot; tag snapshots; share a Dataset with another Project or user. Covers mount paths…

Use the domino-data Python library (PyPI dominodatalab-data, import domino_data) for programmatic data access inside Domino executions. Covers DataSourceClient for SQL queries and object-store reads and writes against…

Connect Domino executions to external data and cloud services. Covers the mechanisms Domino documents (Data Source connectors, External Data Volumes at /domino/edv/<name>, SAML-based AWS credential propagation,…

Configure a DataHub instance to load and display a Micro Frontend (MFE) app. Use when the user wants to register an MFE with DataHub, add an MFE to the nav sidebar, set up MFE config for local dev or production/k8s, or…

Enrich a customer-orders stream with loyalty tier using Flink SQL on Confluent Cloud. Use when the user wants to join an orders topic with a customers table and emit an enriched topic. Do NOT trigger for self-managed…

Query, explore, and update databases through existing DataRobot data connections (datastores) with the connection's stored credentials: no connection strings, no app scaffolding. Use when the user wants to list…

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Resolve data lake and lakehouse asset references across Glue Data Catalog, S3, S3 Tables, and Redshift. Triggers on: find the table, where is our data, which table has, locate dataset, find data for, search catalog,…

Queries the data warehouse with SQL and answers business questions about data. Use when answering anything that needs warehouse data - counts, metrics, trends, aggregations, joins across tables, data lookups, or ad-hoc…

This skill guides the use of Jupyter notebooks for data analysis, exploration, and visualization, particularly with BigQuery. It outlines best practices for notebook execution and validation (supporting both…

…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…

…and validate App Store / Mac App Store listing metadata for an Xcode project — localized text (name, subtitle, description, keywords, promo text, release notes, URLs), review information, categories, and…

…a public company ahead of its next earnings call, using Bigdata.com data (estimates, tearsheet financials, news, filings, transcripts, events calendar). Produces an EPIC driver table, earnings quality screen with…

…move a public company over the next few quarters, using Bigdata.com data (events calendar, filings, news, tearsheet). Covers scheduled catalysts — earnings, investor days, index reviews, lock-up and patent expiries,…

…happened at a public company and why it matters — using Bigdata.com data (news, filings, transcripts, tearsheet financials). Findings are categorized into financial results, product and tech launches, M&A and…

Produce a deep country economic analysis using Bigdata.com data — GDP, inflation, monetary policy, labor markets, debt mechanics, and investment implications. Goes beyond a point-in-time snapshot: structural and…

…sector inside a specific country or region using Bigdata.com data — combining the macroeconomic backdrop (GDP, inflation, rates, policy), country-specific sector trends and valuations, fundamentals of…