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Found 103 Skills
Google Cloud Platform CLI (gcloud, gcloud storage, bq). Use when: managing GCP resources, deploying to Cloud Run/Cloud Functions/GKE/App Engine, working with Cloud Storage, BigQuery, IAM, Compute Engine, Cloud SQL, Pub/Sub, Secret Manager, Artifact Registry, Cloud Build, Cloud Scheduler, Cloud Tasks, Vertex AI, VPC/networking, DNS, logging/monitoring, or any GCP service. Also covers: authentication, project/config management, CI/CD integration, serverless deployments, container registry, docker push to GCP, managing secrets, Workload Identity Federation, and infrastructure automation.
Operate the Google Cloud gcloud CLI safely and effectively. Authenticates users, reads cloud resource state freely for debugging and exploration, and creates, updates, or deletes resources only after explicit user confirmation. Use when working with gcloud, Google Cloud CLI, GCP resources, cloud debugging, reading logs, managing Compute Engine, Cloud Run, Cloud Functions, GKE, IAM, networking, Cloud Storage, Cloud SQL, Pub/Sub, or when the user mentions any gcloud command, Google Cloud project, or needs to authenticate with GCP.
Use when connecting your agent to external APIs, tools, or services via Gateway, or restricting tool access with Cedar policies. Handles gateway setup, target types, outbound auth (OAuth, API key, IAM), credentials, and Cedar policy authoring. Triggers on: "connect to API", "add gateway", "connect to MCP server", "Lambda tools", "OpenAPI", "gateway target", "Cedar policy", "restrict tools", "policy engine", "gateway auth error", "store API key", "outbound credential", "env var API key", "API key None after deploy", "credential not available after deploy", "should this be a gateway target", "give my agent tools", "add tools to agent". Not for inbound auth (who can call your agent) — use agents-harden. Not for debugging agent behavior — use agents-debug. Not for VPC networking errors (agent can't reach APIs due to VPC) — use agents-build. Not for creating or hosting a new MCP server project — use agents-get-started.
Infrastructure-as-code specialist for multi-cloud provisioning using Terraform across any provider (AWS, GCP, Azure, Oracle Cloud). Use for terraform plan/apply, state management, compute, databases, storage, networking, IAM, OIDC, cost optimization, policy-as-code, ISO/IEC 42001 AI controls, ISO 22301 continuity, and ISO/IEC/IEEE 42010 architecture documentation.
Use when the user wants to deploy and run a prepared AWS FIS experiment. Triggers on "execute FIS experiment", "run FIS experiment", "start chaos experiment", "deploy FIS template", "启动 FIS 实验", "运行混沌实验", "执行故障注入实验", "deploy and run the experiment in [directory]". Expects a prepared experiment directory (from aws-fis-experiment-prepare or manually created) containing experiment-template.json, iam-policy.json, cfn-template.yaml, and alarm configs. Deploys resources via CLI or CloudFormation, starts the experiment with strict user confirmation, monitors progress, and generates results report.
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.
Guides agents through a structured 6-step discovery process to design and deploy Google Cloud global external Application Load Balancers with Cloud CDN, Cloud Armor, and Service Extensions, mapping workload requirements to opinionated best-practice configurations. Use when: - Designing, configuring, or deploying a Google Cloud global external Application Load Balancer, Cloud CDN, Cloud Armor WAF, or Service Extensions. - Discovering existing Google Cloud resources (Cloud Storage buckets, Compute Engine MIGs, GKE, Cloud Run) to use as load balancer backends. - Generating production-grade Terraform HCL or gcloud CLI scripts for global external Application Load Balancer configurations. - Actuating deployments via Infrastructure Manager or bash scripts, including performing IAM pre-checks. - Detecting, analyzing, or reconciling configuration drift on deployed global external Application Load Balancers. Don't use for: - Non-Google Cloud load balancing or security configurations. - Purely regional or internal load balancing setups (unless part of a hybrid/failover global design).
Diagnoses and resolves Amazon EFS issues including mount failures, NFS timeouts, permission errors, throughput problems, and burst credit exhaustion. Use when the user has an EFS file system that is not mounting, returning errors, performing slowly, or showing access denied.
Diagnoses and resolves Amazon S3 Files issues including mount failures, permission errors, synchronization problems, and performance issues. Use when the user has an S3 file system that is not mounting, returning access denied, not syncing changes to S3, showing files in lost+found, or performing slower than expected.
Guides agents and users through migrating from Gemini API in Google AI Studio to Gemini Enterprise Agent Platform (formerly Vertex AI). Use this skill when moving applications to Google Cloud, to leverage Cloud credits, or to unify inferencing with other Cloud infrastructure (IAM, billing, telemetry).
Provides expert guidance on authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access.
Manages Google Cloud Pub/Sub topics, subscriptions, schemas, and messages safely and efficiently. Use when building or managing event-driven, decoupled systems, streaming data pipelines, or integrating push/pull asynchronous message consumers. Don't use when writing or debugging Google Cloud client library code or raw REST/gRPC API interactions directly.