このプロンプトをコピーして、使用中の AI アシスタントに送ってください。
Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/GoogleCloudPlatform/data-agent-kit-plugin.リポジトリの README を読み込んでいます…
収集済み skill 40 件中 40 件を表示しています。
Upgrades Spark workloads on Google Cloud Managed Service for Apache Spark (formerly known as Dataproc) clusters and Serverless to a newer image or runtime version. Supports static compatibility analysis, code upgrade, build checks against the target version,…
原文の言語: 英語
Configures (or reconfigures) the Google Cloud Data Agent Kit (DAK) plugin by checking gcloud and ADC credentials, collecting the GCP project ID, region, and services, and running its bundled `dak-setup` script. Use this proactively and without waiting to be…
原文の言語: 英語
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…
原文の言語: 英語
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…
原文の言語: 英語
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,…
原文の言語: 英語
Monitors, inventories, and assesses Google Cloud Managed Service for Apache Spark (Dataproc Serverless and Dataproc on Compute Engine) environments, clusters, batches, jobs, sessions, metrics, logs, costs, and configurations across single and multiple…
原文の言語: 英語
Authors, optimizes, and runs PySpark and Spark code on Google Cloud Managed Spark (Dataproc Serverless, clusters, and Spark Connect). Use when: - Authoring or running Spark/PySpark notebooks in any kernel (Local Kernel with spark-remote templates, Remote…
原文の言語: 英語
Provides data-retrieval best practices, tool selection guidance, and performant SQL query syntax for BigQuery telemetry across INFORMATION_SCHEMA, Cloud Monitoring, and the REST API. Use when the telemetry to fetch is already known, selecting telemetry tools,…
原文の言語: 英語
Provides diagnostic workflows and step-by-step root-cause analysis procedures for actively broken, failing, or slow BigQuery jobs, execution graph and query plan stage bottlenecks, system performance issues, or unexpectedly expensive workloads. Use when…
原文の言語: 英語
Provides workflows to optimize BigQuery environments (capacity planning, editions), storage assets (partitioning, clustering, storage lifecycles, billing models), and SQL queries. Use when optimizing cost, modeling Edition migrations, rightsizing…
原文の言語: 英語
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…
原文の言語: 英語
Stores, retrieves, and manages data as objects in Cloud Storage on Google Cloud (also known colloquially as GCS) buckets. Use when you need to interact with Cloud Storage — set up a Storage MCP server (remote or local Toolbox), create or configure buckets,…
原文の言語: 英語
Creates Cloud Storage (Google Cloud Storage, or GCS) buckets. Analyzes the workload (sensitive data, media hosting, ingestion, web hosting, archiving, backup, logging, analytics, AI/ML, or general-purpose), validates project-level security settings, and…
原文の言語: 英語
Mounts Cloud Storage buckets as a POSIX file system with Cloud Storage FUSE (gcsfuse). Use when you need to interact with gcsfuse — decide whether FUSE, native gs:// reads, or Filestore/Managed Lustre fits a workload, deploy tuned mounts on GKE, Compute…
原文の言語: 英語
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, predict values, detect outliers or anomalies, find key drivers, perform semantic…
原文の言語: 英語
Provides expert guidance for troubleshooting Google Cloud Spark and Dataproc workloads (Dataproc Serverless batches and standard Dataproc clusters), and inspecting, streaming, searching, tailing, or summarizing Spark driver outputs and event logs in Cloud…
原文の言語: 英語
Guides users through discovering their database requirements, recommends a Google Cloud database product or migration destination based on a recommendation matrix, and assists in database creation. Use when a user asks 'What database service should I use?',…
原文の言語: 英語
Provisions instances and tables, designs performant schemas, and queries data in Bigtable. Use when designing Bigtable row keys, configuring column families, writing SQL queries or client library code (Java, Go, Python) for Bigtable, or diagnosing…
原文の言語: 英語
Generates Python code using BigQuery DataFrames (BigFrames). Use by default for any Python data task involving BigQuery, including data processing, analysis, and machine learning. Don't use for SQL-first workflows or the google-cloud-bigquery client library —…
原文の言語: 英語
Ensures proper Python dependency management, avoiding global `pip install` and adhering to project-specific tooling. Use this skill if any of the following are true: 1. Attempting to run `pip install {package_name}`. 2. Python packages or dependencies need to…
原文の言語: 英語
This skill guides the use of Jupyter notebooks for data analysis, exploration, and visualization, particularly with BigQuery. It outlines best practices for notebook execution and validation (supporting both cell-by-cell execution and full notebook generation…
原文の言語: 英語
Mandatory Step 0 pre-flight check for regional Google Cloud MCP servers (e.g. Dataproc) before using MCP tools or falling back to gcloud/bq CLI. Use whenever interacting with Dataproc clusters, Spark batches, jobs, sessions, or regional GCP resources. Fixes…
原文の言語: 英語
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…
原文の言語: 英語
Provides an end-to-end journey for authoring a BigQuery property graph from your tables or from a model document/diagram (an ER diagram, an ontology, a semantic model): dataset discovery, candidate relationships verified against the data, a readable plan, and…
原文の言語: 英語
Provides guidelines and best practices for querying BigQuery property graphs and semantic graphs: native GQL (Graph Query Language) pattern matching, multi-hop and variable-length paths, aggregation, top-N, path extraction, output formatting (graph…
原文の言語: 英語
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…
原文の言語: 英語
Enforces resource attribution for CLI commands. Use this skill whenever you are running `bq` or `gcloud` commands via `run_command`. It ensures mandatory labeling for supported `bq` operations while avoiding invalid flags on read-only commands.
原文の言語: 英語
Guides the process of analyzing, mapping, and documenting transformations between source and target schemas for any database, data warehouse, or data platform. Focuses exclusively on creating a high-fidelity mapping plan (Mapping Manifesto). Used when…
原文の言語: 英語
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…
原文の言語: 英語
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…
原文の言語: 英語
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…
原文の言語: 英語
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…
原文の言語: 英語
**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…
原文の言語: 英語
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…
原文の言語: 英語
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…
原文の言語: 英語
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…
原文の言語: 英語
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…
原文の言語: 英語
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.
原文の言語: 英語
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…
原文の言語: 英語
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…
原文の言語: 英語
README の元ファイル：README.md
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