Skill UI

Specializes in the expert deployment and orchestration of production-grade multi-agent systems using Google's Agent Development Kit (ADK). This skill manages the complex lifecycle, including AgentCard discovery, A2A protocol communication, state management via Memory Bank, and secure execution within the Code Execution Sandbox. Ideal for setting up robust, enterprise-level AI workflows on the Vertex AI Agent Engine, especially during CI/CD pipelines.

A comprehensive tool for designing, generating schemas, and evaluating complex multi-agent systems. It guides users through defining system requirements, selecting optimal orchestration patterns (Supervisor, Swarm, Pipeline), generating provider-ready tool schemas (Anthropic/OpenAI), and analyzing execution logs for performance bottlenecks, cost, and latency. This ensures robust, production-grade autonomous workflows.

Guides you through building Airflow operators for data pipelines with automated best practices, production-ready code/config generation, and validation for ETL, transformation, orchestration, and streaming scenarios.

Automates change-data-capture pipeline planning by guiding developers through ETL, orchestration, and streaming best practices, then generating validated configs and code when “cdc pipeline creator” is requested.

Master essential practices for writing robust, secure, and portable Bash scripts suitable for production environments, CI/CD pipelines, and critical system automation. This guide covers strict error handling, safe argument parsing, input validation, process orchestration, and cross-platform compatibility, ensuring scripts are resilient to unexpected inputs and failures.

Automates beam pipeline builder tasks by guiding best practices, generating production-ready code, and validating ETL, transformation, orchestration, and streaming workflows.

A comprehensive workflow bundle covering the entire cloud-native development lifecycle. It guides users through critical phases, including cloud infrastructure setup (AWS, Azure, GCP, Terraform IaC), container orchestration with Kubernetes, robust CI/CD pipeline automation, observability implementation, security hardening, cost optimization, and disaster recovery planning. This ensures best practices across all stages of modern application deployment.

Guides you through building Dagster data pipelines with best-practice advice, ready-to-use configurations, and validation checks for ETL, transformation, orchestration, and streaming workflows whenever the Dagster pipeline creator skill is activated.

Automates guidance for data catalog updater tasks, covering ETL, transformation, orchestration, and streaming workflows to keep pipeline metadata accurate.

An expert in designing, implementing, and optimizing scalable, reliable, and cost-effective data pipelines for both batch and streaming data. Covers advanced topics including ETL/ELT patterns, Kappa/Lambda architectures, workflow orchestration (Airflow/Prefect), transformation using dbt/Spark, and managing modern storage formats like Delta Lake and Iceberg. Focuses heavily on data quality, monitoring, and cost optimization strategies.

Offers automated guidance for implementing data lineage trackers across ETL and streaming pipelines, including best practices on transformations, orchestration, and validation for production environments.

Guides you through generating dbt models inside data pipelines, covering setup, code generation, configuration, and validation while following best practices for ETL, orchestration, and streaming workloads.