AI tools for “data”

…writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and…

The missing context layer for enterprise AI. Atlan gives every AI agent the data graph, business logic, and governance to act on trusted data.

Unitlab AI is an enterprise multimodal data platform to curate, annotate, review, version, and manage production training data across every modality.

Supercharge your AI agents with data from the web and beyond. Building the library for superintelligence. 🔥 Introducing Alexandria and our $75M Series B. Read the announcement…

Omnilert is the leading provider of AI Gun Detection Technology, deploying advanced Data-Centric AI to enable the best weapon detection system on the market.

Grade or filter workflow HDF5 episodes with an OpenAI-compatible vision model. Use for visual success labels; do not use for replay, policy evaluation, or recordings without frames.

Record demonstrations through a workflow's teleop Task into workflow HDF5. Use for keyboard, leader, VR, or bus input; do not use for policy evaluation or autonomous rule-based Tasks.

Run `tao-daft validate` to check NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors. Do not use for non-DAFT formats. Use when the user asks to validate a DAFT dataset, check DAFT schema,…

Use Superset MCP tools for dataset inspection, semantic-layer querying, and virtual dataset creation. Use only for MCP tool workflows; do not use for direct API work.

Apache Iceberg tables on Databricks — Managed Iceberg tables, External Iceberg Reads (fka Uniform), Compatibility Mode, Iceberg REST Catalog (IRC), Iceberg v3, Snowflake interop, PyIceberg, OSS Spark, external engine…

…legacy AI Gateway on Model Serving endpoints; use databricks-model-serving for…

…wants to design, build, code, or deploy an AI agent on DataRobot; mentions agent_spec.yaml, dress rehearsal, the DataRobot agent template, LangGraph, CrewAI, LlamaIndex, NAT, Base agents, MCP servers, backend APIs,…

Use when the user wants to configure LLM integration for a DataRobot agent application. This skill helps to change LLM model, switch between the LLM integrations the project supports (LLM Gateway, a DataRobot-deployed…

Use when the user wants to find DataRobot capabilities — skills, MCP servers, agents, or platform resources — for a task. Fetches the live DataRobot catalog directly so results are always current, regardless of…

Comprehensive guidance for training models in DataRobot, including project creation, AutoML configuration, feature engineering, and model selection. Use when training models, creating AutoML projects, or selecting…

Tools and guidance for making predictions with DataRobot deployments, including real-time predictions, batch scoring, prediction dataset generation, and prediction explanations (SHAP/XEMP). Use when making predictions,…

Use this skill to run DataHub's saved evals and report answers for judging. Triggers on: "run our evals", "run the eval suite", "run eval urn:li:eval:...", "how are our evals doing", "check for eval regressions",…

This skill provides routing guidance for all DataHub interaction skills. It is injected at session start and helps map user intent to the correct skill. Do not invoke this skill directly — it is loaded automatically.

IDMP datasource diagnosis workflow. Read the connection, probe connectivity, inspect databases and metadata, compare model mappings, and reread after every probe or write.

…explicitly asks to create, scaffold, or initialize a new Datadog App project — they must use action words like "create", "scaffold", "new", or "build" together with "Datadog App" or "@datadog/apps" or "npm create…