全部 Agent Skills
41,263 个结果
- Federate Lakehouse CatalogGoogle Cloud PlatformSets 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).
- Gcp Composer TroubleshootingGoogle Cloud PlatformProvides 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.
- Gcp Data PipelinesGoogle Cloud PlatformPrimary 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.
- Gcp DataflowGoogle Cloud PlatformGuides 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 autoscaling. Use when: - Creating an Apache Beam Dataflow pipeline.
- Gcp Managed Airflow Dag AuthoringGoogle Cloud PlatformGuides 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 use when authoring Python code unrelated to Airflow DAGs.
- Gcp Managed Airflow MigrationsGoogle Cloud PlatformProvides 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.
- Gcp Managed Airflow RecommendationsGoogle Cloud PlatformProvides 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 restarts, or analyzing system health.
- Gcp Managed Spark UpgradesGoogle Cloud PlatformUpgrades GCP Spark/Dataproc jobs to newer versions by analyzing, remediating, and testing job on target image version. Use when: - Upgrading Spark/Dataproc versions (major, minor, or sub-minor). Example prompt: "Upgrade Dataproc job [job_id] in project [project_id], region [region] to target image version [target_version].
- Gcp Pipeline OrchestrationGoogle Cloud PlatformThis 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 queries. This skill also helps deploy and trigger orchestration pipelines.
- Gcp Pipeline Resource ProvisioningGoogle Cloud PlatformAutomates 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.
- Gcp SparkGoogle Cloud PlatformDevelops, optimizes and runs PySpark/Spark code on Managed Spark (Dataproc clusters and Serverless) on Google Cloud. Use when: - Authoring or running Spark/PySpark notebooks (any kernel), incl. data analysis, reports and visualizations. - Writing Spark ETL pipelines or preparing workloads for production. - Training or running inference with ML models on Spark.
- Gcp Spark TroubleshootingGoogle Cloud PlatformProvides 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 Storage.
- Gcs Security AssessmentGoogle Cloud PlatformAssesses 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 individually low-risk settings, with actionable remediation.
- Google Cloud Auth VerificationGoogle Cloud PlatformMandatory Step 0 pre-flight execution order and authentication verification for Google Cloud Platform (GCP), Application Default Credentials (ADC), gcloud CLI, Spark, Dataproc, BigQuery, GCS, and notebook runtimes. Use whenever interacting with GCP resources, running Spark/PySpark pipelines, BigQuery queries, GCS paths (gs://), or creating/running notebooks.
- Google Cloud Storage BasicsGoogle Cloud PlatformStores, retrieves, and manages data as objects in Cloud Storage (Google Cloud Storage, or 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, upload, download, stream, or transfer data, organize objects with folders, generate signed URLs, control access (IAM, ACLs, public access prevention), set…
- Google Cloud Storage Bucket ArchitectGoogle Cloud PlatformCreates 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 designs a secure-by-default, cost-effective configuration (location, storage class, uniform bucket-level access, public access prevention, soft…
- Google Cloud Storage FuseGoogle Cloud PlatformMounts 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 Engine, or Cloud Run, enable and size the file, stat, and list caches, tune mount flags or config-file settings, apply workload profiles, keep…
- GoogleCloudPlatform/data-agent-kit-pluginGoogle Cloud Platform技能合集Your entire data stack in your favorite agentic tool.
- Managing Python DependenciesGoogle Cloud PlatformEnsures 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 be added or modified. 3. Initiating a new Python project. 4. Installing missing packages inside a notebook or Python project. 5.
- Ml Best PracticesGoogle Cloud PlatformCRITICAL 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…
- Notebook GuidanceGoogle Cloud PlatformThis 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 depending on tool availability), library installation, and structuring notebooks for clarity.
- OpentuimsmpsComprehensive OpenTUI skill for building terminal user interfaces. Covers the core imperative API, React reconciler, and Solid reconciler. Use for any TUI development task including components, layout, keyboard handling, animations, and testing.
- Resolving MCP Region ConfigsGoogle Cloud PlatformMandatory 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.
- Schema MappingGoogle Cloud PlatformGuides 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 initiating an ETL, ELT, or data integration task with schema mapping specification for multiple tables (i.e.