AI tools for “data”
979 results (tools & skills) · 240 ms · understood as category: Data & Analytics
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,…
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…
REQUIRED companion for Salesforce metadata generation — load this schema/API-context skill in the SAME turn as ANY metadata generator (if you load a generator, you ALSO load this). Use whenever you create, generate,…
Use when the user wants to create, list, describe, or drop databases in Milvus.
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…
…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…
…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…
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.
Serverless compute for Databricks jobs, Lakeflow pipelines and Declarative Automation Bundles (DABs), with STANDARD or PERFORMANCE_OPTIMIZED and classic only where serverless cannot run the workload. Use when creating,…
…to an EXISTING SFDX project, or configuring UI bundle metadata and config files. TRIGGER when: adding or scaffolding a new UI bundle — including adding one more or another UI bundle — into a project that already…
Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.
Guidance for setting up CI/CD pipelines for DataRobot application templates using GitLab, GitHub Actions, and Pulumi for infrastructure as code. Use when setting up CI/CD pipelines, configuring deployments, or managing…
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,…
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…
ALWAYS USE THIS SKILL to retrieve metadata from an org to your local project with sf project retrieve start. Supports retrieval by all changes, source directory, metadata type (wildcards), manifest (package.xml), or…
Generates code that transforms datasets between ML schemas for model training or evaluation. Use when the user says "transform", "convert", "reformat", "change the format", or when a dataset's schema needs to change to…
Turns scattered notes and recurring work into useful Notion trackers for requests, content plans, or team work. Use to set up or improve a tracker, choosing its fields and views from the user's needs; ordinary record…
Use this skill when the user needs to set up a DataHub connection, install the DataHub CLI, configure authentication, verify connectivity, set default scopes, or create agent configuration profiles. Triggers on: "set up…
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…
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,…