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…
Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, detect outliers, find key drivers, or leverage generative AI capabilities in BigQuery.
Generates Python code using BigQuery DataFrames (BigFrames), the pandas/scikit-learn-style API over BigQuery. Use when writing BigFrames code or doing pandas-style dataframe/ML work against BigQuery (e.g. in a notebook). Don't use for SQL-first workflows or the google-cloud-bigquery client library — use…
Discovers and inspects BigQuery Data Transfer Service (DTS) configurations. Use this to identify existing ingestion pipelines and extract datasource or transfer config metadata for data pipelines. Use when a user asks for ingestion scenarios while building or managing data pipelines or when a user asks to "ingest" or…
Provides guidelines and best practices for querying and defining property graphs and semantic graphs in BigQuery using GQL (Graph Query Language). Use when creating property graphs or querying graph topologies in BigQuery.
Provides BigQuery SQL query optimization techniques, execution best practices, and performance tuning rules for high-efficiency querying. Use when optimizing BigQuery SQL queries, reducing query costs, or designing performant SQL transformations.
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…
Automated data quality and transformation capabilities for Dataform/dbt/BigQuery pipelines. Processes data sourced from BigQuery or Cloud Storage (GCS), applying best practices for data ingestion, movement, schema mapping, and comprehensive data cleaning.
Expertise in generating clean, correct, and efficient Dataform pipeline code for BigQuery ELT. Use this when creating or modifying Dataform pipelines, actions, or source declarations, when Dataform, SQLX, or BigQuery are mentioned in a transformation, when data needs to be ingested from GCS into BigQuery via Dataform…
Expert guidance for creating, modifying, and optimizing dbt pipelines for BigQuery. Use this skill whenever user asks for generating or modifying a dbt model or project. Activate this skill when the user - Creates, modifies, or troubleshoots dbt models or pipelines - Needs to optimize SQL within a dbt project - Is…
Finds and inspects data assets within Google Cloud. Relevant when any of the following conditions are true: 1. The user request involves finding, exploring, or inspecting data assets in Google Cloud, such as: BigQuery datasets, tables, or views BigLake catalog or tables Spanner instances, databases or tables etc. 2.…
Enforces resource attribution for CLI commands. Use this skill whenever you are running bq or gcloud commands via runcommand. It ensures mandatory labeling for supported bq operations while avoiding invalid flags on read-only commands.
Sets up Google Cloud Lakehouse federated catalogs to remote Iceberg REST Catalogs. Currently supported catalogs: Databricks Unity, AWS Glue. Supported clouds hosting those catalogs: GCP, AWS. The primary use case is connecting to remote data to query it from GCP engines (BigQuery, Spark). Examples of when to use this…
Provides expert guidance for troubleshooting Cloud Composer (Apache Airflow) and Orchestration pipelines. Use this skill when the user asks to generate Root Cause Analysis (RCA), troubleshoot or fix a failed pipeline, DAG in Composer environment and generate RCA report.
Primary entry point for building, managing, and orchestrating data pipelines on Google Cloud. Guides users to the appropriate skill for dbt, Dataflow (Apache Beam), Dataform, Spark (Dataproc Serverless), BigQuery Data Transfer Service (DTS) or orchestration pipeline using Cloud Composer. Clarify requirements and…
Guides writing, packaging, executing, and troubleshooting Apache Beam pipelines on Dataflow. Use when creating new pipelines, configuring Flex Templates, or analyzing performance of Dataflow jobs. Capabilities include Java/Python/Go setup, Cloud Build integration, and deep diagnostic analysis of job health and…
Guides the authoring and validation of Apache Airflow DAGs for Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers environment context discovery, Airflow 2 vs 3 compatibility, authoring best practices, and local/remote validation processes. Use when creating or extending an Airflow DAG. Don't…
Provides guidance for migrating Apache Airflow DAGs in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers migration to Airflow 2.11.1 (MSAA Gen 2 and 3) and Airflow 3 (MSAA Gen 3), including environment inspection, GCS download/upload and scanning patterns for breaking changes.
Provides recommendations and best practices for creating, configuring, tuning and optimizing Managed Service for Apache Airflow (MSAA, Cloud Composer) environments. Use when the user asks for guidance, recommendations, or best practices on configuring Cloud Composer, scaling Airflow environments, preventing workload…
This skill helps the agent generate or update orchestration pipeline definitions for Google Cloud Composer to initialize orchestration pipeline or update the orchestration definition for orchestration of various data pipelines, like dbt pipelines, notebooks, Spark jobs, Dataform, Python scripts or inline BigQuery SQL…
Automates declarative resource creation and provisioning for data pipelines, supporting BigQuery, Dataform, Dataproc, BigQuery Data Transfer Service (DTS), and other resources. It manages environment-specific configurations (dev, staging, prod) through a deployment.yaml file. Use when: Modifying or creating…
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…
Assesses the security posture of Google Cloud Storage (GCS) buckets and projects. Grounds every finding in gathered telemetry, evaluates buckets against Google security best practices (public access, IAM over-granting, CMEK, VPC Service Controls, audit logging), and correlates signals to flag toxic combinations of…
Stores, retrieves, and manages data as objects in Cloud Storage (Google Cloud Storage, or GCS) buckets. Use when you need to interact with Cloud Storage — create or configure buckets, upload, download, stream, or transfer data, organize objects with folders, generate signed URLs, control access (IAM, ACLs, public…