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Found 94 Skills
Use these skills when you need to optimize storage, identify index issues, analyze table statistics, or manage autovacuum and tablespace configurations to maintain peak database health.
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 deployment.yaml for deployment settings. - Resolving environment-specific variables (e.g., Project IDs, Regions) for deployment. - Provisioning supported infrastructure like BigQuery datasets/tables, Dataform resources, or DTS resources via deployment.yaml. Do not use when: - Resources already exist. - Managing resources not supported by `gcloud beta orchestration-pipelines resource-types list`. - Managing general cloud infrastructure (VMs, networks, Kubernetes, IAM policies), which are better suited for Terraform. - Infrastructure spans multiple cloud providers (AWS, Azure, etc.). - Already uses Terraform for the target resources.
A repository of BigQuery-specific logic, knowledge, and specialized standards. Use this skill whenever you are doing anything with BigQuery, including: 1. BigQuery query optimization 2. BigFrames Python code 3. BigQuery ML/AI functions.
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, or when setting up a new Dataform project or configuring workflow_settings.yaml.
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 resolve ambiguity for creating, updating and running data pipelines.
Use these skills when you need to provision new AlloyDB clusters and instances, monitor their creation status, and retrieve high-level configuration or health data for the environment.
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 "add" data that may already be managed by a DTS transfer.
Use these skills when you need to explore the database structure, discover schema objects like views or stored procedures, and execute custom SQL queries to interact with your data.
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.
Skill for BigQuery AI and Machine Learning queries using standard SQL and `AI.*` functions (preferred over dedicated tools).
Use this skill during code reviews to proactively investigate the codebase for duplicated functionality, reinvented wheels, or failure to reuse existing project best practices and shared utilities.
Use these skills when you need to troubleshoot slow performance, analyze query execution plans, identify resource-heavy processes, and monitor system-level PromQL metrics.