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Found 715 Skills
Use these skills when you need to handle large-scale data exploration and dataset management. Use when users need to find data assets or run SQL at scale. Provides metadata discovery and query execution across the data warehouse.
Use these skills when you need to provision new Cloud SQL instances, create databases and users, clone existing environments, and monitor the progress of long-running operations.
CRITICAL RULE: You MUST use this skill whenever the task involves any machine learning tasks or data analysis. Use this skill if the user's prompt or requirements mention any of the following: * Clustering * Classification * Regression * Time series forecasting * Statistical testing * Model comparison * ML * Data analysis SQL/BigQuery ML HANDOFF: If the user requires a SQL solution, use this skill to dictate the ANALYSIS STEPS (e.g., markdown analysis cells, visualization logic), but defer to `bigquery` for all SQL syntax.
Develops and executes Spark code on Dataproc Clusters and Serverless. Reads and writes data using BigLake Iceberg catalogs, BigQuery and Spanner. Debugs execution failures. Use when: - Writing Spark ETL pipelines on GCP. - Training or running inference with ML models with spark on GCP. - Managing Spark clusters, jobs, batches, and interactive sessions. Don't use when: - Writing generic Python scripts that don't use Spark. - Performing simple SQL queries that can be done directly in BigQuery.
Provides guidance for writing, packaging and executing Apache Beam pipelines on GCP using Cloud Dataflow. Use when: - Creating an Apache Beam Dataflow pipeline. - Creating a Google Flex Template.
Use these skills when you need to explore the database schema, identify objects like views and triggers, and execute custom SQL queries to interact with your data.
Integrate with Home Assistant REST and WebSocket APIs. Use when making API calls, managing entity states, calling services, subscribing to events, or setting up authentication. Activates on keywords REST API, WebSocket, API endpoint, service call, access token, Bearer token, subscribe_events.
Interact with GitLab repositories, merge requests, and APIs using the GITLAB_TOKEN environment variable. Use when working with code hosted on GitLab or managing GitLab resources.
**STOP AND VERIFY**: Before running any command or tool that results in irreversible data loss, you MUST obtain explicit user consent. When in doubt, ask. It is better to wait for confirmation than to accidentally delete production data or critical project assets. Use this for: - SQL: DROP TABLE/VIEW/SCHEMA/DATABASE, TRUNCATE, or broad DELETE (missing WHERE or using 1=1). - Cloud Storage: gsutil rm or gcloud storage rm targeting production data or critical buckets. - Infrastructure: gcloud projects delete, deleting Spanner/BigQuery/Dataproc resources, deleting secrets, or KMS key destruction.
Build modern data apps, dashboards, and interactive reports using either React + Vite or Streamlit. Includes optional Gemini Data Analytics chat integration for an AI powered "chat with your data" experience. Relevant when any of the following conditions are true: 1. User explicitly requests to build a data dashboard, data application, or visualization UI, and the UI pulls data from a GCP database (defaulting to BigQuery unless otherwise specified). 2. You need to generate a frontend web application to interact with, query, and visualize data from GCP data sources. 3. User wants to build a "chat with your data" experience or integrate the Gemini Data Analytics chat API into a web interface. Do NOT use when any of the following conditions are true: 1. The request is for building backend-only services. 2. The request is for simple CLI scripts or command-line applications. 3. The web application is not data-centric or does not involve visualizing/querying data from GCP sources.
Use these skills when you need to audit database health, identify storage bloat, find invalid indexes, analyze table statistics, and manage maintenance configurations like autovacuum.
Use these skills when you need to handle advanced data intelligence and predictive tasks. Use when a user asks "why" data changed or needs future projections. Provides automated insight generation and time-series forecasting.