--- title: "Google (@google) skills · skilld" canonical_url: "https://skilld.dev/gh/google" meta: description: "172 agent skills published by Google on skilld." "og:description": "172 agent skills published by Google." "og:title": "Google on skilld" --- ` ![Avatar for Google](https://skilld.dev/_img/avatar?url=https%3A%2F%2Fgithub.com%2Fgoogle.png) # **Google** [@google](https://github.com/google)org Google ❤️ Open Source 172 skills7 repos 22k United States of America [GitHub](https://github.com/google) [Website](https://opensource.google/) ## Skills ### [google/skills](https://skilld.dev/gh/google/skills) Agent Skills for Google products and technologies 110 skills 21k `npx skilld add google/skills` - [ **/agent-platform-alert-configuration**21k Configures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard infrastructure monitoring unrelated to AI agents, or when the agent is not instrumented with OpenTelemetry (for Reliability, Cost, Safety, Security alerts). NOTE: Reliability, Cost, Safety, and Security alerts use generic OTel metrics and work across runtimes (such as Cloud Run, Vertex AI). Quality alerts rely on Vertex AI Online Monitors and are strictly bound to Vertex AI deployments. /agent-platform-alert-configuration by google](https://skilld.dev/gh/google/skills/agent-platform-alert-configuration) - [ **/agent-platform-deploy**21k Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (\`gcloud ai model-garden models list-deployment-config\`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use \`agent-platform-endpoint-management\`. Don't use for running model evaluations (use \`agent-platform-eval-flywheel\` skill). /agent-platform-deploy by google](https://skilld.dev/gh/google/skills/agent-platform-deploy) - [ **/agent-platform-endpoint-management**21k Manages Agent Platform serving endpoints. Use when you need to create, list, describe, update, or delete serving endpoints for model deployment on Agent Platform. Also use when troubleshooting endpoint permission, quota, or resource busy errors. Don't use for deploying models to endpoints or for running model evaluations. /agent-platform-endpoint-management by google](https://skilld.dev/gh/google/skills/agent-platform-endpoint-management) - [ **/agent-platform-eval-flywheel**21k Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when generating synthetic user scenarios, evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For general production deployment, use agent-platform-deploy. /agent-platform-eval-flywheel by google](https://skilld.dev/gh/google/skills/agent-platform-eval-flywheel) - [ **/agent-platform-inference**21k Connects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when asked to perform inference, ask a model a question, run a test prompt, execute chat completions, or generate code for calling Gemini or OpenMaaS models, authenticate with GenAI SDK, OpenAI SDK, or legacy Agent Platform SDK, configure base URLs and global/regional endpoints, or troubleshoot 429 Resource Exhausted (DSQ), 400 User Validation, or 404 Not Found errors. Don't use for deploying models to endpoints or for running model evaluations. /agent-platform-inference by google](https://skilld.dev/gh/google/skills/agent-platform-inference) - [ **/agent-platform-migrate-from-ai-studio**21k 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). /agent-platform-migrate-from-ai-studio by google](https://skilld.dev/gh/google/skills/agent-platform-migrate-from-ai-studio) - [ **/agent-platform-model-registry**21k Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models. /agent-platform-model-registry by google](https://skilld.dev/gh/google/skills/agent-platform-model-registry) - [ **/agent-platform-prompt-management**21k Manages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts. /agent-platform-prompt-management by google](https://skilld.dev/gh/google/skills/agent-platform-prompt-management) - [ **/agent-platform-rag-engine-management**21k Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google Workspace RAG, or other RAG products like gRAG. /agent-platform-rag-engine-management by google](https://skilld.dev/gh/google/skills/agent-platform-rag-engine-management) - [ **/agent-platform-skill-registry**21k Interact with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills. Use this skill to enable agents to register functionality or discover new capabilities. /agent-platform-skill-registry by google](https://skilld.dev/gh/google/skills/agent-platform-skill-registry) - [ **/agent-platform-troubleshooting**21k Troubleshoots Google Cloud Gemini Enterprise Agent Platform issues (Agent Gateway, Registry, Identity, Policies, Model Armor, Identity-Aware Proxy (IAP)). Use when agent requests fail with 403 (especially unauthorized egress), Agent Runtime queries return 500, or gateway/IAP logs show permission errors. Don't use for general Google Cloud Identity and Access Management (IAM) debugging or networking issues unrelated to the Agent Platform stack. /agent-platform-troubleshooting by google](https://skilld.dev/gh/google/skills/agent-platform-troubleshooting) - [ **/agent-platform-tuning**21k Agent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use \`agent-platform-deploy\`), or managing serving endpoints (use \`agent-platform-endpoint-management\`). /agent-platform-tuning by google](https://skilld.dev/gh/google/skills/agent-platform-tuning) - [ **/agent-platform-tuning-management**21k Manages GenAI tuning jobs in Agent Platform. Use this to list, get, or cancel ongoing model tuning jobs. Don't use for fine-tuning models (use \`agent-platform-tuning\`), deploying models to endpoints (use \`agent-platform-deploy\`), or managing serving endpoints (use \`agent-platform-endpoint-management\`). /agent-platform-tuning-management by google](https://skilld.dev/gh/google/skills/agent-platform-tuning-management) - [ **/alloydb-basics**21k Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB Model Context Protocol (MCP) tools for automated database operations. Use when creating, configuring, or administering AlloyDB databases. Do NOT use for general PostgreSQL instances (e.g. Cloud SQL) or other GCP databases. /alloydb-basics by google](https://skilld.dev/gh/google/skills/alloydb-basics) - [ **/application-design-center-design-deploy**21k Processes GCP infrastructure design and deployment workflows within Application Design Center (ADC). Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Boundaries: - Only use for GCP-specific cloud infrastructure. - Only use for Terraform coding within the ADC context. /application-design-center-design-deploy by google](https://skilld.dev/gh/google/skills/application-design-center-design-deploy) - [ **/bigquery-ai-ml**21k 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 search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests. /bigquery-ai-ml by google](https://skilld.dev/gh/google/skills/bigquery-ai-ml) - [ **/bigquery-basics**21k Manages datasets, tables, and jobs in BigQuery. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources (datasets, tables, views), or perform basic data ingestion and analysis. /bigquery-basics by google](https://skilld.dev/gh/google/skills/bigquery-basics) - [ **/bigquery-bigframes**21k 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 — use bigquery-basics. /bigquery-bigframes by google](https://skilld.dev/gh/google/skills/bigquery-bigframes) - [ **/bigtable-basics**21k Assists in provisioning instances/tables, designing performant schemas, and querying 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 performance/hotspotting issues. Also use when provisioning Bigtable clusters using gcloud or cbt CLIs. Don't use for generic Cloud SQL administration. /bigtable-basics by google](https://skilld.dev/gh/google/skills/bigtable-basics) - [ **/cloud-logging-configuration-basics**21k Configure single-project Google Cloud Logging: regional log buckets, log sinks, log views, restricting or hiding sensitive logs in the default view (\_Default) filter, IAM permissions for views (Logs View Accessor, IAM conditions), logs-based metrics, log exclusions, and sampling. Don't use for cross-project logging or multi-project setups. /cloud-logging-configuration-basics by google](https://skilld.dev/gh/google/skills/cloud-logging-configuration-basics) - [ **/cloud-logging-cross-project-configuration**21k Configure and troubleshoot Google Cloud cross-project centralized logging and read-time aggregation. Use when: - Setting up log routing from multiple projects/folders/organizations to a central log bucket. - Creating cross-project log sinks and configuring central log buckets. - Troubleshooting cross-project routing. Don't use for single-project basic configurations. /cloud-logging-cross-project-configuration by google](https://skilld.dev/gh/google/skills/cloud-logging-cross-project-configuration) - [ **/cloud-logging-query-generation**21k Generates Logging Query Language (LQL) queries for Google Cloud Logging from natural language. Use this skill when you need to query log data or when you are debugging issues. You can filter log data by Google Cloud service. Don't use this skill to query other databases, such as SQL or Cloud Spanner. /cloud-logging-query-generation by google](https://skilld.dev/gh/google/skills/cloud-logging-query-generation) - [ **/cloud-monitoring-chart-generation**21k Generates Google Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos from resolved PromQL or ListTimeSeries queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery or TimeSeriesFilter datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus or ListTimeSeries queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills. /cloud-monitoring-chart-generation by google](https://skilld.dev/gh/google/skills/cloud-monitoring-chart-generation) - [ **/cloud-monitoring-list-time-series-request**21k Generates valid Cloud Monitoring ListTimeSeries requests and aggregation specifications from metric descriptors and resource parameters. Use when asked to create, generate, format, or build ListTimeSeries requests, JSON payloads, filter expressions, or aligner/reducer aggregations for Cloud Monitoring metrics and charts. Don't use for metric discovery or metric selection. /cloud-monitoring-list-time-series-request by google](https://skilld.dev/gh/google/skills/cloud-monitoring-list-time-series-request) - [ **/cloud-monitoring-metric-selection**21k Retrieve, query, and identify relevant Google Cloud Monitoring metric descriptors for a GCP service or resource (such as Compute Engine, Spanner, BigQuery, Cloud Run, Cloud SQL, Pub/Sub, Cloud Storage, etc.). Use when asked to find, list, search, or discover GCP metric types, names, kind/value schemas, or descriptors. /cloud-monitoring-metric-selection by google](https://skilld.dev/gh/google/skills/cloud-monitoring-metric-selection) - [ **/cloud-run-basics**21k Manages Cloud Run services, jobs, and worker pools. Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools). /cloud-run-basics by google](https://skilld.dev/gh/google/skills/cloud-run-basics) - [ **/cloud-sql-basics**21k This file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server instances as resources in Cloud SQL. For example, when Cloud SQL creates an open-source MySQL instance, the resulting resource is a Cloud SQL for MySQL instance that Google Cloud manages. Cloud SQL handles backups, high availability, and secure connectivity for relational database workloads. /cloud-sql-basics by google](https://skilld.dev/gh/google/skills/cloud-sql-basics) - [ **/data-manager-api-audience-ingestion**21k Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an entire audience for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill). /data-manager-api-audience-ingestion by google](https://skilld.dev/gh/google/skills/data-manager-api-audience-ingestion) - [ **/data-manager-api-event-ingestion**21k Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload offline conversions, enhanced conversions for leads, click conversions, Google Analytics web or app events, or any other event ingestion use case supported by the Data Manager API. Don't use for uploading audience members (use the data-manager-api-audience-ingestion skill). /data-manager-api-event-ingestion by google](https://skilld.dev/gh/google/skills/data-manager-api-event-ingestion) - [ **/data-manager-api-setup**21k Guides developers through client library installation and authentication setup steps for the Data Manager API. Use this skill when a user is getting started with the Data Manager API and needs to setup their local environment, install the client library, or setup access to the API. Don't use for implementing audience or event ingestion logic (use the data-manager-api-audience-ingestion or data-manager-api-event-ingestion skills instead). /data-manager-api-setup by google](https://skilld.dev/gh/google/skills/data-manager-api-setup) - [ **/datalineage-bigquery-asset-impact-analysis**21k Analyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected. Use when: - Performing a blast radius or impact analysis for a BigQuery table or view. - Assessing the consequences of modifying, deleting, or pausing updates to a BigQuery asset. - Identifying downstream dependencies (tables, dashboards, processes) of a BigQuery asset. Don't use for: - General BigQuery querying or data analysis (use BigQuery-related tools instead). - Non-BigQuery assets (e.g., Cloud Storage files) unless they are part of the BigQuery lineage. - Creating or modifying lineage links directly. /datalineage-bigquery-asset-impact-analysis by google](https://skilld.dev/gh/google/skills/datalineage-bigquery-asset-impact-analysis) - [ **/datalineage-summary**21k Summarizes Google Cloud Data Lineage graphs to help users debug data quality issues and understand data provenance for BQ/GCS. Use when summarizing upstream and downstream data flows, and presenting complex lineage data as an intuitive Markdown report. Don't use for generic BigQuery queries, editing lineage relationships, or downstream deprecation. Don't use for downstream blast-radius impact analysis (use datalineage-bigquery-asset-impact-analysis skill instead). /datalineage-summary by google](https://skilld.dev/gh/google/skills/datalineage-summary) - [ **/detection-engineering-coverage-evaluation**21k Automates the end-to-end detection engineering workflow in Google SecOps using MCP tools. Use when fetching threat intelligence from blogs, generating Threat Detection Opportunities (TDOs), simulating attacker behavior with synthetic UDM events, evaluating rule coverage, and deploying gap-closing rules. Don't use for standalone YARA-L 2.0 rule authoring/tuning (use secops-detection-engineering), threat hunting, or SOC investigation. /detection-engineering-coverage-evaluation by google](https://skilld.dev/gh/google/skills/detection-engineering-coverage-evaluation) - [ **/developer-device-platform-basics**21k Provides guidance and instructions on managing remote devices on Developer Device Platform (DDP). Use when reserving remote Android devices, establishing connection tunnels, checking session status, or extending/cancelling leases. Don't use for iOS or local device/hardware inquiries. /developer-device-platform-basics by google](https://skilld.dev/gh/google/skills/developer-device-platform-basics) - [ **/firebase-basics**21k Provides foundational Firebase CLI setup, CLI installation, version checks (\`firebase-tools@latest --version\`), CLI login (including --no-localhost), project creation, project selection (\`firebase use\`), and app config file downloads (\`google-services.json\`, \`GoogleService-Info.plist\`). Use ONLY for CLI login, project creation/switching, or downloading app config files. Don't use for Firebase Hosting deploy, Firestore, Auth, App Hosting, Data Connect, Crashlytics, or Remote Config. /firebase-basics by google](https://skilld.dev/gh/google/skills/firebase-basics) - [ **/gcloud**21k Provides safety-critical validation, guardrails, and data reduction for gcloud CLI operations across Google Cloud Platform (GCP) services and infrastructure. Use when planning, generating, constructing, proposing, describing, or executing any gcloud CLI commands - including when answering questions about gcloud syntax, or formatting flags. Don't use when writing Google Cloud client library code or raw REST/gRPC API requests. /gcloud by google](https://skilld.dev/gh/google/skills/gcloud) - [ **/gemini-agents-api**21k Manages custom Agent resources on Gemini Enterprise Agent Platform. Use when the user wants to programmatically create, configure, list, update, or delete stateful, server-managed Agent resources (including mounting files, skills, and tools) before executing conversations. /gemini-agents-api by google](https://skilld.dev/gh/google/skills/gemini-agents-api) - [ **/gemini-api**21k Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like multimodal inputs, tools, media generation, caching, batch prediction, and Live API. /gemini-api by google](https://skilld.dev/gh/google/skills/gemini-api) - [ **/gemini-interactions-api**21k Guides the usage of Gemini Interactions API on Gemini Enterprise Agent Platform. Use when the user wants to use the stateful, server-managed Interactions API for multi-turn conversations, background execution, streaming, structured output, and function calling on the Agent Platform. /gemini-interactions-api by google](https://skilld.dev/gh/google/skills/gemini-interactions-api) - [ **/gemini-live-api**21k Generates a Gemini LiveAPI client service class in the user's chosen programming language. Use when the user wants to build, scaffold, or integrate a client that connects to the Gemini Enterprise LiveAPI websocket endpoint, handles session setup/resumption, bearer token refresh, and sending/receiving \`ClientMessage\`/\`ServerMessage\` protos. Don't use for general (non-live, non-bidirectional) Gemini API usage such as one-shot \`generateContent\`, embeddings, image/video generation, or fine-tuning — use the \`gemini-api\` skill for those. /gemini-live-api by google](https://skilld.dev/gh/google/skills/gemini-live-api) - [ **/gke-ai-troubleshooting-handle-disruption-gpu-tpu**21k Diagnoses, predicts, and mitigates node disruptions during Compute Engine host maintenance and hardware or software maintenance events for GPU and TPU workloads on GKE. Use when diagnosing node disruptions, predicting host maintenance events on GPU/TPU nodepools, inspecting node interruption PromQL metrics, auditing node taints, or configuring workload protection strategies (graceful termination, opportunistic maintenance, PodDisruptionBudgets). Don't use for general GKE cluster creation, network policy configuration, or non-disruption workload deployment. /gke-ai-troubleshooting-handle-disruption-gpu-tpu by google](https://skilld.dev/gh/google/skills/gke-ai-troubleshooting-handle-disruption-gpu-tpu) - [ **/gke-ai-troubleshooting-jobset-interruption**21k Diagnoses GKE JobSet interruptions, restarts, and preemptions for AI/ML training workloads autonomously. Use when troubleshooting JobSet restart loops, spot VM preemptions, node readiness failures, host VM issues, or coordinator worker crashes. Don't use for general GKE cluster creation, basic workload deployment, or non-JobSet application issues. /gke-ai-troubleshooting-jobset-interruption by google](https://skilld.dev/gh/google/skills/gke-ai-troubleshooting-jobset-interruption) - [ **/gke-ai-troubleshooting-tpu-vbar-oom**21k Diagnoses and prevents vbar\_control\_agent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbar\_control\_agent crashes, memory cgroup OOMs in serial console logs, tpu-device-plugin metrics checksum corruption errors, or custom TPU metrics collection conflicts on GKE TPU v6e nodes. Don't use for general non-TPU container OOM troubleshooting or standard GKE node lifecycle operations. /gke-ai-troubleshooting-tpu-vbar-oom by google](https://skilld.dev/gh/google/skills/gke-ai-troubleshooting-tpu-vbar-oom) - [ **/gke-app-onboarding**21k Manages GKE application onboarding, covering containerization, deployment manifests, and migration. Use when onboarding or deploying an application to GKE for the first time, or containerizing an app for GKE. Don't use for general GKE cluster administration or upgrades (use gke-basics or gke-upgrades instead). /gke-app-onboarding by google](https://skilld.dev/gh/google/skills/gke-app-onboarding) - [ **/gke-backup-dr**21k Configures Backup for GKE: the BackupRestore cluster addon, BackupPlan and RestorePlan resources, restore workflows, and CMEK-encrypted backups. Use for backup policies, disaster recovery, or GKE cluster restores. Don't use for database backups. /gke-backup-dr by google](https://skilld.dev/gh/google/skills/gke-backup-dr) - [ **/gke-basics**21k Manages core GKE cluster provisioning, credentials, Autopilot vs Standard selection, and workload deployment. Use when creating GKE clusters, fetching kubectl credentials, or deciding between Autopilot and Standard modes. Don't use for Workload Identity (use gke-workload-identity), GKE networking (use gke-networking), security hardening (use gke-platform-security or gke-workload-security), or cluster upgrades (use gke-upgrades). /gke-basics by google](https://skilld.dev/gh/google/skills/gke-basics) - [ **/gke-batch-hpc**21k Runs batch and HPC workloads on GKE, utilizing job queues and parallel processing. Use when running GKE batch jobs, configuring GKE HPC, or setting up GKE job queues. Don't use for standard web application deployments (use gke-app-onboarding instead). /gke-batch-hpc by google](https://skilld.dev/gh/google/skills/gke-batch-hpc) - [ **/gke-cluster-autoscaler**21k Trigger on mention of GKE cluster autoscaler, node autoscaling, node pool auto-creation / node auto-provisioning. Provides guidance on enabling and optimizing cluster autoscaler, best practices, and troubleshooting issues such as nodes not scaling up or down, zonal stockouts, or capacity buffers. Do not use for ComputeClass-specific YAML generation or priority configuration (defer to gke-compute-classes skill). /gke-cluster-autoscaler by google](https://skilld.dev/gh/google/skills/gke-cluster-autoscaler) - [ **/gke-cluster-creation**21k Plans and executes GKE cluster creation, provisioning, and production readiness audits using pre-defined templates (Autopilot, Standard Regional, GPU/AI Inference, AI Hypercompute). Use when creating GKE clusters, provisioning GKE environments, selecting cluster modes, or auditing GKE clusters. Don't use for application onboarding or deployment configuration (use gke-app-onboarding instead). /gke-cluster-creation by google](https://skilld.dev/gh/google/skills/gke-cluster-creation) - [ **/gke-compute-classes**21k Configures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto Provisioning configuration or general GKE cluster creation. /gke-compute-classes by google](https://skilld.dev/gh/google/skills/gke-compute-classes) - [ **/gke-cost-analysis**21k Answer natural language questions and perform analysis on GKE cluster and workload costs using BigQuery billing exports, cost allocation data, and live cluster monitoring metrics. Use when querying GKE costs across projects, namespaces, or workloads, analyzing billing reports in BigQuery (\`bq\`), checking cluster cost budgets (\`gcloud billing\`), or diagnosing cost drivers like pod requests vs. actual utilization (\`kubectl top\`). Don't use for applying cost optimization changes, creating rightsizing manifests (VPA/MPA), or selecting ComputeClasses (use gke-cost-optimization instead). /gke-cost-analysis by google](https://skilld.dev/gh/google/skills/gke-cost-analysis) - [ **/gke-cost-optimization**21k Optimizes GKE costs, rightsizes workloads, and configures Spot VMs, CUDs, cost allocation, and resource quotas. Use when optimizing GKE cluster or workload costs, configuring GKE cost allocation or quotas, rightsizing CPU/memory requests, or selecting Spot VMs and machine types. Don't use for general compute class provisioning or GPU Selection (use gke-compute-classes instead). /gke-cost-optimization by google](https://skilld.dev/gh/google/skills/gke-cost-optimization) - [ **/gke-golden-path**21k Provides GKE golden path configuration defaults, production readiness checklists, and cluster default patterns. Use when designing GKE clusters, verifying GKE production readiness, or checking configurations against GKE defaults. Don't use for setting up workload autoscaling specifically (use gke-workload-scaling instead). /gke-golden-path by google](https://skilld.dev/gh/google/skills/gke-golden-path) - [ **/gke-inference**21k Deploys and optimizes AI/ML inference workloads on GKE, using GPUs, TPUs, and model servers. Use when deploying GKE inference servers, configuring GKE GPU resources for inference, or deploying LLMs on GKE. Don't use for migrating existing AI workloads to GKE (use google-cloud-solution-guided-gke-ai-migration), GKE RAG with Cloud SQL/AlloyDB (use google-cloud-solution-rag-enterprise-search-gke-sqldb), or batch/HPC (use gke-batch-hpc). /gke-inference by google](https://skilld.dev/gh/google/skills/gke-inference) - [ **/gke-manifest-generation**21k Generates and updates secure, production-ready Kubernetes YAML manifests optimized for GKE Autopilot and GKE Standard clusters. Use when creating or modifying GKE deployment manifests, configuring container security contexts, setting CPU/memory resource limits, defining readiness/liveness/startup probes, mounting secrets and volumes, configuring GKE Gateway API routes, targeting Spot VMs, or deploying AI model inference workloads (vLLM, TGI, Gemma). Don't use for live cluster operations, pod troubleshooting (use gke-workload-troubleshooting), or cluster infrastructure provisioning (use gke-cluster-creation). /gke-manifest-generation by google](https://skilld.dev/gh/google/skills/gke-manifest-generation) - [ **/gke-multitenancy**21k Plans and configures multi-tenancy on GKE. Covers namespace isolation, RBAC planning for teams, resource quotas, LimitRanges, network isolation, and cost allocation. Use when designing GKE multi-tenancy, configuring GKE namespaces, setting up resource quotas, or isolating GKE teams. Don't use for single-tenant cluster configuration or general deployment instructions (use gke-basics or gke-app-onboarding instead). /gke-multitenancy by google](https://skilld.dev/gh/google/skills/gke-multitenancy) - [ **/gke-networking**21k Plans, configures, and manages core GKE cluster networking. Covers private clusters, VPC-native configurations, DNS, node egress, Dataplane V2, and IP planning. Use when designing GKE networking layouts, configuring private clusters, setting up Dataplane V2, planning GKE IP ranges, or managing VPC- native cluster modes. Don't use for application ingress, load balancing, or service networking (use gke-service-networking instead). /gke-networking by google](https://skilld.dev/gh/google/skills/gke-networking) - [ **/gke-observability**21k Configures GKE observability, including Cloud Logging, Cloud Monitoring, and managed Prometheus. Use when configuring GKE monitoring, setting up GKE logging, or configuring Prometheus metrics collection, and to troubleshoot Managed Service for Prometheus (GMP) issues such as missing metrics, unhealthy scrape targets, PodMonitoring misconfiguration, rule/alert evaluation failures, and monitoring permission errors. Don't use to configure local application logging frameworks or external APMs outside GKE. /gke-observability by google](https://skilld.dev/gh/google/skills/gke-observability) - [ **/gke-platform-security**21k Plans, configures, and hardens platform-level Google Kubernetes Engine (GKE) cluster security. Covers cluster add-ons (Secret Manager enablement), RBAC hardening (disabling insecure bindings, audit tools), Binary Authorization, Secrets Encryption (--database-encryption-key), Security Posture (--security-posture), enabling Shielded Nodes, GKE Sandbox cluster enablement, GKE IAM roles, and cross-service authentication IAM patterns. Use when securing cluster control planes, hardening GKE RBAC, enabling Shielded Nodes, enabling GKE Sandbox runtime, enabling cluster-wide security add-ons, or managing GKE IAM roles. Don't use for Workload Identity (use gke-workload-identity) or workload-level security (SecretProviderClass, PSS, NetPol, gVisor pod runtimeClassName; use gke-workload-security). /gke-platform-security by google](https://skilld.dev/gh/google/skills/gke-platform-security) - [ **/gke-productionize**21k Orchestrates comprehensive production readiness reviews and assessments for GKE clusters and workloads across scalability, security, reliability, observability, backup/DR, and cost optimization. Use when asked to productionize, prepare, assess, audit, or review a GKE cluster or workload before going live to production. Don't use for deep-dive single-domain implementation (use specific domain skills like gke-workload-scaling, gke-platform-security, gke-workload-security, gke-service-networking, gke-reliability instead). /gke-productionize by google](https://skilld.dev/gh/google/skills/gke-productionize) - [ **/gke-reliability**21k Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for generating K8s YAML manifests (use gke-manifest-generation) or disaster recovery and cluster backups (use gke-backup-dr). /gke-reliability by google](https://skilld.dev/gh/google/skills/gke-reliability) - [ **/gke-service-networking**21k Configures GKE edge networking, traffic routing, load balancing, and private service endpoints. Use when configuring Gateway API manifests, standard Ingress, Cloud Armor WAF security policies, Container-Native Load Balancing (NEGs), Private Service Connect (PSC), or Google-managed SSL certificates on GKE, and to troubleshoot Ingress and load-balancer 502/5xx errors, backend health-check failures, connection draining, and TLS/SSL policy enforcement. Don't use for core cluster IP planning, Dataplane V2 network policies, or node NAT egress (use gke-networking instead). /gke-service-networking by google](https://skilld.dev/gh/google/skills/gke-service-networking) - [ **/gke-storage**21k Manages GKE storage, including PVCs, PersistentVolumes, and Filestore. Use when configuring GKE storage or creating PVCs. For GCS FUSE mounts, use google-cloud-storage-fuse. For diagnosing storage failures (volume attach/mount errors, disk performance/node storage pressure, or Cloud Storage FUSE OOM), use gke-storage-troubleshooting. Don't use for database administration or replication strategies outside volume provisioning context. /gke-storage by google](https://skilld.dev/gh/google/skills/gke-storage) - [ **/gke-upgrades**21k Plans, executes, and validates Google Kubernetes Engine (GKE) cluster upgrades and maintenance operations for both Standard and Autopilot clusters. Produces upgrade plans, pre/post-upgrade checklists, maintenance runbooks with gcloud commands, release channel strategy, and troubleshooting guides. Handles node pool upgrade strategies (surge, blue-green), version compatibility, PDB management, and workload-specific concerns (stateful, GPU, operators). Use this skill whenever the user mentions GKE upgrades, Kubernetes version bumps, node pool maintenance, GKE patching, cluster version management, release channel selection, maintenance windows, surge upgrades, stuck upgrades, or any GKE lifecycle management task — even casual mentions like "we need to upgrade our clusters" or "plan our next GKE maintenance" or "our upgrade is stuck." Don't use for GKE cluster creation, application onboarding, general networking/routing setup, or security policy configurations (use gke-basics or relevant GKE skills instead). /gke-upgrades by google](https://skilld.dev/gh/google/skills/gke-upgrades) - [ **/gke-workload-scaling**21k Manages scaling for GKE workloads using HPA and VPA. Use when configuring Horizontal Pod Autoscaler (HPA), configuring Vertical Pod Autoscaler (VPA), or applying best practices for GKE workload autoscaling. Do not use for cluster-level autoscaling (Cluster Autoscaler), static cluster sizing, or configuring node-level machine styles directly. /gke-workload-scaling by google](https://skilld.dev/gh/google/skills/gke-workload-scaling) - [ **/gke-workload-security**21k Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running security audits (\`audit\_cluster.sh\`), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (\`gVisor\`), enforcing Pod Security Standards (\`restricted\` labeling) and pod securityContext, and mounting Secret Manager secrets via CSI (\`SecretProviderClass\`). Use when auditing workload security posture, isolating namespaces, applying pod security standards, or configuring network policies and secret volume mounts. Don't use for Workload Identity (use gke-workload-identity), cluster-wide control plane security, RBAC hardening, Binary Authorization, Shielded Nodes, or enabling platform-level GKE add-ons (use gke-platform-security instead). /gke-workload-security by google](https://skilld.dev/gh/google/skills/gke-workload-security) - [ **/gke-workload-troubleshooting**21k Diagnoses GKE workload failures (CrashLoopBackOff, OOMKilled, ImagePullBackOff, Pending, etc.) via logs and events. Use when pods fail to start or crash repeatedly. Don't use for GKE cluster infrastructure provisioning, node pool creation, or non-Kubernetes Google Cloud services. /gke-workload-troubleshooting by google](https://skilld.dev/gh/google/skills/gke-workload-troubleshooting) - [ **/google-ads-api-account-diagnostics**21k Diagnoses Google Ads account performance issues such as conversion loss (value or volume), low lead flow/volume, and lost impression share (opportunities) due to ad rank, bids, or budgets. Use when troubleshooting sudden performance drops, analyzing campaign impression share metrics, investigating low lead flow, or searching for bidding and budget constraints. Don't use for setting up new campaigns, uploading conversion events directly, or general Google Mobile Ads SDK integration issues (use gma-android-integrate instead). /google-ads-api-account-diagnostics by google](https://skilld.dev/gh/google/skills/google-ads-api-account-diagnostics) - [ **/google-ads-api-mcp-setup**21k Guides developers through downloading, configuring, and installing the official open-source Google Ads MCP Server. Use this skill when a user wants to connect their AI assistant (such as Gemini, Claude Code, or Cursor) to their Google Ads account to query campaigns or retrieve reporting metrics using natural language. /google-ads-api-mcp-setup by google](https://skilld.dev/gh/google/skills/google-ads-api-mcp-setup) - [ **/google-ads-api-quickstart**21k Guides developers through Google Ads API quickstart: credential setup, choosing from 6 client libraries/REST, configuring environments, and running a "retrieve campaigns" script. Troubleshoots common setup errors: USER\_PERMISSION\_DENIED, login\_customer\_id issues, and DEVELOPER\_TOKEN\_NOT\_APPROVED. Use this skill when: - The user asks how to get started with the Google Ads API. - The user needs to set up Google Ads credentials or developer tokens. - The user wants to write a quickstart/example script for Google Ads. - The user encounters errors like USER\_PERMISSION\_DENIED or DEVELOPER\_TOKEN\_NOT\_APPROVED. /google-ads-api-quickstart by google](https://skilld.dev/gh/google/skills/google-ads-api-quickstart) - [ **/google-agents-cli-onboarding**21k Onboarding entrypoint for agents-cli in Agent Platform. It should be used when the user wants to "create a new agent", "develop an agent", "build an agent using ADK", "run the agent locally", "debug agent code", "test an agent", "evaluate an agent", "deploy an agent", "publish an agent", "monitor an agent", or needs the ADK (Agent Development Kit) development lifecycle. /google-agents-cli-onboarding by google](https://skilld.dev/gh/google/skills/google-agents-cli-onboarding) - [ **/google-analytics-admin-api-basics**21k Manages Google Analytics account and property settings, enables the Analytics Admin API via the Cloud CLI, lists accounts and properties, and manages data streams, custom dimensions, conversion events, and integrations. Use when you need to programmatically configure Google Analytics accounts, provision properties, manage data retention, configure Measurement Protocol secrets, or manage Firebase and Google Ads links. /google-analytics-admin-api-basics by google](https://skilld.dev/gh/google/skills/google-analytics-admin-api-basics) - [ **/google-analytics-data-api-basics**21k Manages Google Analytics reporting data, enables the Analytics Data API via the Cloud CLI, and creates reports using the Google Analytics Data API (v1beta). Use when you need to interact with Google Analytics properties, run customized analytics reports, query metrics (like activeUsers, screenPageViews) and dimensions (like city, date), check metrics and dimensions compatibility, or verify API enablement. Don't use for Google Analytics Admin API operations (e.g., creating properties, managing users) or for front-end tracking installation. /google-analytics-data-api-basics by google](https://skilld.dev/gh/google/skills/google-analytics-data-api-basics) - [ **/google-cloud-filestore-autoscale**21k Inspects Google Cloud Filestore capacity and utilization, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization). Use when monitoring Filestore instance headroom, resizing instance shares, configuring automated growth/shrink thresholds (custom thresholds apply globally across projects in session memory), or preventing out-of-space outages. Don't use for Cloud Storage (GCS) buckets, Persistent Disk block storage, or NetApp Volumes. /google-cloud-filestore-autoscale by google](https://skilld.dev/gh/google/skills/google-cloud-filestore-autoscale) - [ **/google-cloud-global-frontend-configuration**21k Guides agents through a 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 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, MIGs, GKE, Cloud Run) to use as backends. - Generating production-grade Terraform HCL or gcloud CLI scripts for global external Application Load Balancers. - Actuating deployments via Infrastructure Manager or bash scripts, including 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). /google-cloud-global-frontend-configuration by google](https://skilld.dev/gh/google/skills/google-cloud-global-frontend-configuration) - [ **/google-cloud-networking-observability**21k Investigates Google Cloud networking issues by analyzing GCP logs, metrics, and diagnostics. Use when investigating dropped network traffic, packet drops, drop reasons, VPC Flow Logs (including Private Service Connect / PSC, serverless / App Engine Direct VPC, and cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics. Don't use for generic VM management or non-observability tasks. /google-cloud-networking-observability by google](https://skilld.dev/gh/google/skills/google-cloud-networking-observability) - [ **/google-cloud-recipe-auth**21k 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. /google-cloud-recipe-auth by google](https://skilld.dev/gh/google/skills/google-cloud-recipe-auth) - [ **/google-cloud-recipe-foundation-builder**21k Deploys a baseline landing zone foundation for a Google Cloud Organization, establishing security guardrails using Organization Policies, resource hierarchy folders and projects, billing association, and centralized logging and monitoring. Deploys Google Cloud's recommended security controls and architecture. Use when setting up a new Google Cloud Organization or establishing a secure, enterprise-grade landing zone foundation. Don't use for individual project onboarding (use google-cloud-recipe-onboarding or product-specific skills instead). /google-cloud-recipe-foundation-builder by google](https://skilld.dev/gh/google/skills/google-cloud-recipe-foundation-builder) - [ **/google-cloud-recipe-onboarding**21k Guides a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource. Use when a new developer wants to initialize their first Google Cloud project, configure billing, and verify deployment. Don't use for enterprise organization setup (use Google Cloud Setup guided flow for that instead). Don't use for complex multi-project architectures. /google-cloud-recipe-onboarding by google](https://skilld.dev/gh/google/skills/google-cloud-recipe-onboarding) - [ **/google-cloud-slo-alert-configuration**21k Configures PromQL-based Service Level Objective (SLO) alerting policies for Google Cloud resources registered in App Hub or individually specified. Generates Terraform output. Use when the user asks to configure an SLO or Service Level Objective. Don't use for standard alerting policies. /google-cloud-slo-alert-configuration by google](https://skilld.dev/gh/google/skills/google-cloud-slo-alert-configuration) - [ **/google-cloud-solution-agentic-ai-bidirectional-streaming**21k Guides agents to interactively discover customer requirements for live, bidirectional multi-agent AI systems that process continuous streams of multimodal data for real-time technical guidance and safety monitoring. Generates a custom Google Cloud solution that uses opinionated best practices and architecture guidance. Use when users need agentic assistance to design and create a multi-product solution in the cloud for live bidirectional multimodal streaming workloads. Don't use for simple text-based chat applications or workloads without real-time streaming requirements. /google-cloud-solution-agentic-ai-bidirectional-streaming by google](https://skilld.dev/gh/google/skills/google-cloud-solution-agentic-ai-bidirectional-streaming) - [ **/google-cloud-solution-agentic-ai-borderless-data-lakehouse**21k Discovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead). /google-cloud-solution-agentic-ai-borderless-data-lakehouse by google](https://skilld.dev/gh/google/skills/google-cloud-solution-agentic-ai-borderless-data-lakehouse) - [ **/google-cloud-solution-agentic-ai-data-science-workflow**21k Designs a tailored multi-product agentic data science architecture on Google Cloud that incorporates opinionated best practices. Use when architecting multi-product solutions for agent-based data analytics or ML workloads. Don't use for simple queries, non-agentic pipelines, general cloud reviews, or writing agent code. /google-cloud-solution-agentic-ai-data-science-workflow by google](https://skilld.dev/gh/google/skills/google-cloud-solution-agentic-ai-data-science-workflow) - [ **/google-cloud-solution-agentic-analytics-spark-knowledge-catalog**21k Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse instead). /google-cloud-solution-agentic-analytics-spark-knowledge-catalog by google](https://skilld.dev/gh/google/skills/google-cloud-solution-agentic-analytics-spark-knowledge-catalog) - [ **/google-cloud-solution-architecture**21k Interactively discovers requirements and designs holistic, multi-product system architectures, solution blueprints, and deployment recommendations for complex workloads on Google Cloud. Use when designing end-to-end cloud solutions, selecting and integrating Google Cloud services, generating architecture diagrams, or conducting requirements discovery for new cloud workloads or migrations. Don't use for single-product tasks (use product-specific skills), initial onboarding or authentication (use google-cloud-recipe-\*), Well-Architected Framework reviews or audits (use google-cloud-waf-\*), or workloads covered by specialized solution skills. /google-cloud-solution-architecture by google](https://skilld.dev/gh/google/skills/google-cloud-solution-architecture) - [ **/google-cloud-solution-build-deploy-agents**21k Designs, builds, and deploys AI agents or multi-agent systems on Google Cloud. Provides an interactive workflow to gather requirements, recommend a tailored architecture, and generate deployment instructions. Use when designing or implementing agentic systems on Google Cloud. Don't use for general Google Cloud solution architecture (use google-cloud-solution-architecture instead) or for narrow tasks targeting a single product without agent context. /google-cloud-solution-build-deploy-agents by google](https://skilld.dev/gh/google/skills/google-cloud-solution-build-deploy-agents) - [ **/google-cloud-solution-guided-gke-ai-migration**21k Guides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl. Use when the user has an existing AI inference workload (on Cloud Run, the Gemini API, Gemini Enterprise Agent Platform, or a custom VM) and wants to move it to self-hosted inference on GKE, or asks follow-up questions during such a migration (hardware sizing, model staging, manifest generation, validation, traffic cutover). DO NOT use for brand new GKE inference deployments with no existing workload to migrate (use gke-inference instead). DO NOT use if the user intends to automate the migration via the Gemini Cloud Assist MCP server. /google-cloud-solution-guided-gke-ai-migration by google](https://skilld.dev/gh/google/skills/google-cloud-solution-guided-gke-ai-migration) - [ **/google-cloud-solution-n-tier-serverless-web-app**21k Assists in designing and implementing secure n-tier serverless web applications and microservices on Google Cloud. Use when users need architecture designs, security checklists, Terraform code, or deployment guidance for multi-tier serverless apps, regional data residency / European sovereignty compliance, zero-trust private VPC networking, or Private Service Connect. Don't use for VM, GKE, or non-Google Cloud architectures. /google-cloud-solution-n-tier-serverless-web-app by google](https://skilld.dev/gh/google/skills/google-cloud-solution-n-tier-serverless-web-app) - [ **/google-cloud-solution-rag-enterprise-search-gke-sqldb**21k Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. Use when users need a vector-enabled SQL database as the store and index for the embedding vectors, an open model and open-source inferencing framework, and Kubernetes containers to host all the application components. DON'T use this skill for fully-managed RAG, or SaaS search services, or when a non-SQL vector database is required. /google-cloud-solution-rag-enterprise-search-gke-sqldb by google](https://skilld.dev/gh/google/skills/google-cloud-solution-rag-enterprise-search-gke-sqldb) - [ **/google-cloud-storage-basics**21k Stores, 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 storage classes (Standard, Nearline, Coldline, Archive), manage lifecycle and cost, protect data (versioning, CMEK, retention, Bucket Lock, holds, soft delete), host static websites, trigger Pub/Sub notifications, mount buckets (gcsfuse), or optimize performance. Covers gcloud storage / gsutil, JSON/XML APIs, client libraries, Terraform, and Cloud Storage MCP servers. Don't use for non-Storage MCP servers, block storage (Persistent Disk), BigQuery, or databases (Cloud SQL, Spanner, Bigtable, Firestore). /google-cloud-storage-basics by google](https://skilld.dev/gh/google/skills/google-cloud-storage-basics) - [ **/google-cloud-storage-fuse**21k Mounts Cloud Storage buckets as a POSIX file system with Cloud Storage FUSE (gcsfuse). Use when interacting 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 file, stat, and list caches, tune mount flags (--implicit-dirs) or config-file settings, apply workload profiles, keep ML checkpointing safe (rename atomicity, hierarchical namespace/HNS, close-time finalization, concurrent writers), or diagnose slow training, low throughput, or bill spikes with gcsfuse metrics. Covers mount semantics, gcsfuse CLI and config files, GKE gcsfuse CSI driver (Workload Identity principal:// bindings, profile StorageClasses, sidecar sizing), and Cloud Run volume mounts. Don't use for bucket administration or data management without a mount (google-cloud-storage-basics) or fully POSIX-compliant shared file systems (Filestore, Managed Lustre; use gke-storage). /google-cloud-storage-fuse by google](https://skilld.dev/gh/google/skills/google-cloud-storage-fuse) - [ **/google-cloud-waf-cost-optimization**21k Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud. /google-cloud-waf-cost-optimization by google](https://skilld.dev/gh/google/skills/google-cloud-waf-cost-optimization) - [ **/google-cloud-waf-operational-excellence**21k Generates operations-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify operational requirements, and provide actionable recommendations for deployment, monitoring, and incident management. /google-cloud-waf-operational-excellence by google](https://skilld.dev/gh/google/skills/google-cloud-waf-operational-excellence) - [ **/google-cloud-waf-performance-optimization**21k Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity. /google-cloud-waf-performance-optimization by google](https://skilld.dev/gh/google/skills/google-cloud-waf-performance-optimization) - [ **/google-cloud-waf-reliability**21k Generates guidance for reliability, resilience, availability, redundancy, fault-tolerance, and disaster recovery (DR) for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework. Use when the user asks to evaluate, design, or improve the reliability, resilience, availability, or disaster recovery capabilities of Google Cloud workloads. /google-cloud-waf-reliability by google](https://skilld.dev/gh/google/skills/google-cloud-waf-reliability) - [ **/google-cloud-waf-security**21k Generates security-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate workloads, identify security requirements, and provide actionable recommendations for IAM, network security, data protection, and operational security. /google-cloud-waf-security by google](https://skilld.dev/gh/google/skills/google-cloud-waf-security) - [ **/google-cloud-waf-sustainability**21k Provides recommendations for environmental sustainability, carbon footprint reduction, and energy efficiency based on the Sustainability pillar of the Google Cloud Well-Architected Framework (WAF). Use when the user asks to assess, design, or optimize Google Cloud workloads for sustainability—including the shared responsibility model, selecting low-carbon regions (CFE%), reducing resource and AI/ML energy waste, designing efficient software and storage lifecycles, or measuring and tracking emissions using Google Cloud Carbon Footprint. Don't use for financial cost reduction (use google-cloud-waf-cost-optimization), latency and throughput tuning (use google-cloud-waf-performance-optimization), or high availability and disaster recovery (use google-cloud-waf-reliability). /google-cloud-waf-sustainability by google](https://skilld.dev/gh/google/skills/google-cloud-waf-sustainability) - [ **/google-mobile-ads-android-migrate-to-next-gen**21k Migrates Android applications from the old, legacy Google Mobile Ads (GMA) SDK (com.google.android.gms:play-services-ads) to the new GMA Next-Gen SDK (com.google.android.libraries.ads.mobile.sdk:ads-mobile-sdk). Provides comprehensive mapping tables for imports, classes, and method signatures to help determine migration steps. Use when migrating an existing Android codebase from the old, legacy GMA SDK to GMA Next-Gen SDK. /google-mobile-ads-android-migrate-to-next-gen by google](https://skilld.dev/gh/google/skills/google-mobile-ads-android-migrate-to-next-gen) - [ **/google-mobile-ads-banner**21k Provides instructions to implement, integrate, or configure Google Mobile Ads (GMA) banner ads in Android, iOS, or Unity mobile applications. Use when the task involves setting up banner ads in a mobile application. Don't use for other ad formats like interstitial or rewarded ads. /google-mobile-ads-banner by google](https://skilld.dev/gh/google/skills/google-mobile-ads-banner) - [ **/google-mobile-ads-get-started**21k Provides instructions for integrating the Google Mobile Ads (GMA) SDK. Use this skill when the user wants to get started with, install, integrate, set up, or configure the SDK for AdMob or Ad Manager, GMA Next-Gen SDK or mobile ads framework in an Android, iOS, or Unity application. /google-mobile-ads-get-started by google](https://skilld.dev/gh/google/skills/google-mobile-ads-get-started) - [ **/google-mobile-ads-interstitial**21k Provides instructions for implementing, integrating, or configuring Google Mobile Ads (GMA) SDK interstitial ads in Android, iOS, or Unity mobile applications. Use when the task involves setting up interstitial ads. Don't use for "rewarded interstitial" ads. /google-mobile-ads-interstitial by google](https://skilld.dev/gh/google/skills/google-mobile-ads-interstitial) - [ **/google-mobile-ads-rewarded**21k Provides instructions for implementing, integrating, or configuring Google Mobile Ads (GMA) SDK rewarded ads in Android, iOS, or Unity mobile applications. Use when the task involves setting up rewarded ads. Don't use for "rewarded interstitial" ads. /google-mobile-ads-rewarded by google](https://skilld.dev/gh/google/skills/google-mobile-ads-rewarded) - [ **/iam-helper-for-policy-simulator**21k Safely simulates and applies Google Cloud IAM v1 (Allow) policy changes. Uses the Policy Simulator to replay historical access logs against proposed policies to prevent breaking active workloads before applying the changes. Use when simulating or applying IAM v1 allow policies across Projects, Folders, or Organizations. Don't use for analyzing IAM v2 deny policies, VPC Service Controls, or performing general policy troubleshooting. /iam-helper-for-policy-simulator by google](https://skilld.dev/gh/google/skills/iam-helper-for-policy-simulator) - [ **/iam-helper-for-privileged-access-management**21k Manages the end-to-end lifecycle of on-demand, temporary access using Privileged Access Manager (PAM). Use when a user asks to create, read, update, or delete PAM entitlements, request temporary access, or approve/deny pending PAM grants. Do NOT use for permanent IAM policy bindings, troubleshooting IAM permission errors, or general Google Cloud resource provisioning. /iam-helper-for-privileged-access-management by google](https://skilld.dev/gh/google/skills/iam-helper-for-privileged-access-management) - [ **/ima-dai-sdk**21k Integrates the Google Interactive Media Ads (IMA) Dynamic Ad Insertion (DAI) SDK into websites, web apps, mobile apps, or TV apps. Use when: - A video player needs to load and play HLS or DASH streams in web apps, Android apps, iOS apps, tvOS apps, Cast (CAF) receivers, or Roku channels. - The app needs to make use of a Google DAI livestream event asset key, or content source CMS ID, video ID for video on demand. Don't use this skill to load and play a VAST or VMAP URL. /ima-dai-sdk by google](https://skilld.dev/gh/google/skills/ima-dai-sdk) - [ **/ima-sdk-client-side**21k Supports Interactive Media Ads (IMA) SDK. Use this skill for client-side ad insertion when you are requesting video ads for websites, apps, TVs or other platforms using VAST or VMAP. Do not use for Dynamic Ad Insertion (DAI), SSAI, or SGAI. /ima-sdk-client-side by google](https://skilld.dev/gh/google/skills/ima-sdk-client-side) - [ **/managed-airflow-dag-authoring**21k Provides guidance for authoring Apache Airflow DAGs in 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. /managed-airflow-dag-authoring by google](https://skilld.dev/gh/google/skills/managed-airflow-dag-authoring) - [ **/managed-airflow-migrations**21k 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 and scanning patterns for breaking changes. Use when migrating the DAG code to newer Airflow version. Don't use when checking DAG run failures unrelated to code migration. /managed-airflow-migrations by google](https://skilld.dev/gh/google/skills/managed-airflow-migrations) - [ **/spanner-basics**21k Assists in provisioning instances and databases, designing performant schemas, and querying data in Spanner. Use when designing primary keys, writing SQL queries or client library code, or diagnosing performance issues. /spanner-basics by google](https://skilld.dev/gh/google/skills/spanner-basics) - [ **/workload-manager-basics**21k Use this skill to manage Google Cloud Workload Manager evaluations, rules, scanned resources, and validation results by using public client libraries and the REST API. Use when you need to inspect workload best-practice rules, create and run evaluations for Google Cloud general best practices, SAP, SQL Server, or custom organizational rules, review violations, export results to BigQuery, or automate Workload Manager through client libraries because no service-specific public CLI or MCP server is available. Don't use for general Google Compute Engine instance management, VPC configuration, or standard IAM auditing. /workload-manager-basics by google](https://skilld.dev/gh/google/skills/workload-manager-basics) ### [google/mantis](https://skilld.dev/gh/google/mantis) A modular, stack-agnostic toolkit for AI coding agents to autonomously find, reproduce, and patch vulnerabilities. 21 skills 1.7k `npx skilld add google/mantis` - [ **/mantis-advise**1.7k Proactive security advisor and architectural remediation assistant for secure code development. Use to query threat models, historical vulnerability lineages, verified patch patterns, triaged false positives, and learned trajectory invariants before code edits or to generate architectural remediation plans for confirmed findings. Don't use for automated multi-pass red-team exploitation or fuzzing. /mantis-advise by google](https://skilld.dev/gh/google/mantis/mantis-advise) - [ **/mantis-architecture**1.7k Synthesizes raw learnings and codebase analysis into an interlinked Markdown Knowledge Base (KB). Use at the beginning of a loop to build or update architecture.md, entities, and vulnerabilities. Don't use for generating threat models or formulating execution plans. /mantis-architecture by google](https://skilld.dev/gh/google/mantis/mantis-architecture) - [ **/mantis-calibrate**1.7k Calculates the final risk score based on empirical evidence and architectural impact. Use when findings have been fully processed by previous stages and you need to append final risk scores to the finding files. Don't use for discovering new vulnerabilities or writing patches. /mantis-calibrate by google](https://skilld.dev/gh/google/mantis/mantis-calibrate) - [ **/mantis-chain**1.7k Analyzes individual security findings to identify and construct complex exploit chains. Use after validation stages to see if multiple low-severity bugs can be combined into a higher impact vulnerability. Don't use for initial codebase auditing or writing patch code. /mantis-chain by google](https://skilld.dev/gh/google/mantis/mantis-chain) - [ **/mantis-configure**1.7k Configures and validates Mantis pipeline environments, sandbox mechanisms, and AI models. Use to set up workflow.json, auto-detect host capabilities, switch between sandboxes (static-only, gvisor, microsandbox, gce), select AI models, and run fast 1-2s preflight tests. Don't use for scanning source code or running attack campaigns. /mantis-configure by google](https://skilld.dev/gh/google/mantis/mantis-configure) - [ **/mantis-critic**1.7k Assesses the production viability of findings, filtering out debug-only features and assertion traps. Use when findings have been validated and you need to confirm they are triggerable in production release builds (with assertions disabled). Don't use for writing reproduction scripts or patches. /mantis-critic by google](https://skilld.dev/gh/google/mantis/mantis-critic) - [ **/mantis-dedupe**1.7k Consolidates raw security findings to eliminate redundant reports. Use when raw findings have been generated by the researcher and need consolidation before review. Don't use for initial code auditing or patch generation. /mantis-dedupe by google](https://skilld.dev/gh/google/mantis/mantis-dedupe) - [ **/mantis-history**1.7k Analyzes the repository's version control system (VCS) history to extract past vulnerabilities, security fixes, and vulnerability patterns. Use as an initial pre-processing step to build a historical vulnerabilities database (workspace/historical\_learnings.jsonl) that informs subsequent stages about past issues and fixes. Don't use for code reviews, writing test scripts, or patching code. /mantis-history by google](https://skilld.dev/gh/google/mantis/mantis-history) - [ **/mantis-launch**1.7k Launches automated vulnerability review campaigns on target files or repositories. Use to initiate Mantis vulnerability review pipelines with automated preflight checks, environment auto-configuration, and runtime overrides (sandboxes, models, endpoints). Don't use for configuring settings without scanning or for manual single-stage reviews. /mantis-launch by google](https://skilld.dev/gh/google/mantis/mantis-launch) - [ **/mantis-meta-agent**1.7k Acts as the persistent supervisor, launching and monitoring the automated review campaign. Use when running a long-running, continuous security review campaign that needs autonomous coordination. Don't use for executing individual review stages directly. /mantis-meta-agent by google](https://skilld.dev/gh/google/mantis/mantis-meta-agent) - [ **/mantis-patch**1.7k Generates minimal security fixes using transactional isolation (shadow directories or file backups), applies patches, and verifies them. Use when security findings are successfully reproduced and need patches applied and verified. Don't use for initial vulnerability research or reproduction payload generation. /mantis-patch by google](https://skilld.dev/gh/google/mantis/mantis-patch) - [ **/mantis-pipeline-adapter**1.7k Interactively guides the design and implementation of custom deterministic orchestrator harnesses. Use when a user wants to build their own pipeline to wrap and run Mantis skills reliably. Don't use for executing the default pipeline directly. /mantis-pipeline-adapter by google](https://skilld.dev/gh/google/mantis/mantis-pipeline-adapter) - [ **/mantis-plan**1.7k Formulates a targeted defensive security reviewing plan based on the active threat model and historical learnings. Use when starting a security review campaign to map the codebase boundaries and generate a roadmap (workspace/plan.json). Don't use for executing code reviews, writing test scripts, or patching code. /mantis-plan by google](https://skilld.dev/gh/google/mantis/mantis-plan) - [ **/mantis-reflect**1.7k Extracts learnings from execution trajectories at the end of a Mantis loop. Use to parse agent conversations, extract successes, failures, and false assumptions, and append them to workspace/learnings.jsonl. Don't use for analyzing source code or writing patches. /mantis-reflect by google](https://skilld.dev/gh/google/mantis/mantis-reflect) - [ **/mantis-report**1.7k Generates a human-readable security review packet compiled from confirmed findings and exploit chains. Use at the end of a review cycle to produce stakeholder-facing documentation. Don't use for auditing code or verifying patches directly. /mantis-report by google](https://skilld.dev/gh/google/mantis/mantis-report) - [ **/mantis-reproduce**1.7k Generates and runs crash reproducers to verify security flaws. Use when viable findings exist and you need to write and execute a script or payload to verify the crash. Don't use for code auditing or patching. /mantis-reproduce by google](https://skilld.dev/gh/google/mantis/mantis-reproduce) - [ **/mantis-researcher**1.7k Audits production source code files based on the strategy in workspace/plan.json. Use when a review plan exists and you need to perform static analysis and deep-dive reviews of targeted files. Don't use for planning, deduplicating, or writing patches. /mantis-researcher by google](https://skilld.dev/gh/google/mantis/mantis-researcher) - [ **/mantis-review**1.7k Independently reviews findings and filters out false positives. Use when consolidated findings need validation against the actual source code. Don't use for reproducing crashes or patching code. /mantis-review by google](https://skilld.dev/gh/google/mantis/mantis-review) - [ **/mantis-structural-index**1.7k Builds a content-addressed semantic-unit index from source code for structural context. Use when a pinned or live codebase is available and structural cross-reference data would improve research quality. Don't use for findings analysis, patching, or reporting. /mantis-structural-index by google](https://skilld.dev/gh/google/mantis/mantis-structural-index) - [ **/mantis-summarize**1.7k Pre-processes the repository by generating security-focused summaries (mantis-summary.md) for each directory to make planning and research more efficient. Use when starting a review campaign to map the codebase before threat modeling and planning. Don't use for executing code reviews, writing test scripts, or patching code. /mantis-summarize by google](https://skilld.dev/gh/google/mantis/mantis-summarize) - [ **/mantis-threat-model**1.7k Synthesizes trust boundaries, attack surfaces, and attacker profiles into a living threat model. Use as Stage B of the Knowledge Base generation process, reading architecture and entity definitions from the KB. Don't use for analyzing source code or extracting raw learnings from JSONL files. /mantis-threat-model by google](https://skilld.dev/gh/google/mantis/mantis-threat-model) ### [google/adk-python](https://skilld.dev/gh/google/adk-python) An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. 16 skills 22k `npx skilld add google/adk-python` - [ **/adk-agent-builder**22k Builds ADK (Agent Development Kit) Python agents: LLM agents with tools, graph workflows of function and agent nodes, conditional routing, fan-out and join, schema-validated delegation between agents, human-in-the-loop pauses, and pytest coverage for all of it. Use when asked to create an agent or a workflow, add a tool to one, branch or loop between nodes, run steps in parallel, pause for user approval, or test an agent. Don't use for explaining how ADK works internally or designing its core components (use \`adk-architecture\`), for an agent that already runs but misbehaves (use \`adk-debug\`), for authoring a sample under \`contributing/\` (use \`adk-sample-creator\`), or for naming, typing, and formatting conventions (use \`adk-style\`). /adk-agent-builder by google](https://skilld.dev/gh/google/adk-python/adk-agent-builder) - [ **/adk-architecture**22k Explains how the ADK runtime fits together: the node and graph execution model, Context and Event flow, checkpoint and resume, tracing, and the rules governing the public API surface. Use when answering "how does X work" about ADK internals, tracing where an event or a piece of state comes from, deciding where a new capability belongs, reviewing a change to BaseNode, Workflow, Runner, Agent, Event or Context, working out why a node re-ran or stayed waiting after a resume, or judging whether a change breaks the public API. Don't use for assembling an agent from existing pieces (use adk-agent-builder), diagnosing one failing run or test (use adk-debug), or formatting and naming conventions (use adk-style). /adk-architecture by google](https://skilld.dev/gh/google/adk-python/adk-architecture) - [ **/adk-debug**22k Diagnoses misbehaving ADK agents by inspecting sessions, events, tool calls, and the exact request that reached the model. Covers the \`adk run\` CLI and the \`adk web\` dev server with its session, trace, and debug HTTP endpoints. Use when an agent returns the wrong answer, ignores a tool or swallows a tool error, hangs, loops, emits raw JSON instead of calling tools, is not discovered by \`adk web\`, when a sub-agent cannot see the parent conversation, or when you need the LLM request/response, token counts, or logs for a run. Don't use for how ADK is designed internally (use \`adk-architecture\`), for building a new agent or workflow (use \`adk-agent-builder\`), for environment or dependency setup failures (use \`adk-setup\`), or for lint and style nits (use \`adk-style\`). /adk-debug by google](https://skilld.dev/gh/google/adk-python/adk-debug) - [ **/adk-git**22k Writes commit messages and pull request descriptions for the adk-python repository: Conventional Commits types and scopes, subject lines that say why a change was made, and the linked-issue and testing-plan sections the PR template requires. Use when writing or rewording a commit message, squashing commits before a pull request, drafting a PR description, or checking that a change is shaped to land. Don't use for generic git mechanics such as rebasing, resolving conflicts, cherry-picking, or branch surgery; those need no skill. Don't use to judge the content of a change (use adk-review) or for code style and naming (use adk-style). /adk-git by google](https://skilld.dev/gh/google/adk-python/adk-git) - [ **/adk-review**22k Reviews the uncommitted changes in an adk-python working tree and reports correctness, design, public-API stability, test, sample and documentation gaps as a prioritized findings report, fixing them only when asked. Use when the user asks to review local changes, wants a self-review before opening a pull request, asks whether a change breaks the public API or needs tests, samples or docs, or asks what is wrong with the current diff. Required for changes to public APIs, core architecture (Runner, Workflow, BaseNode), new features and major refactors. Don't use for a single style nit (use adk-style), for diagnosing a failing test or a misbehaving agent at runtime (use adk-debug), or for wording a commit message or PR description (use adk-git). /adk-review by google](https://skilld.dev/gh/google/adk-python/adk-review) - [ **/adk-sample-creator**22k Creates a new sample agent in the ADK Python repository — the sample directory, its \`agent.py\`, and its \`README.md\` — following the conventions the existing samples already use. Use when the user wants to add a sample or example demonstrating a feature or agent pattern (dynamic nodes, fan-out/fan-in, a standalone tool-using agent), asks where a new sample belongs under \`contributing/samples/\`, or wants an existing sample's README brought up to the standard structure. Don't use for building a real working agent for the user's own project (use \`adk-agent-builder\`), or for checking whether the Python blocks in a Markdown file run (use \`adk-verify-snippets\`). /adk-sample-creator by google](https://skilld.dev/gh/google/adk-python/adk-sample-creator) - [ **/adk-setup**22k Sets up a local ADK Python development environment in a git clone of the open-source adk-python repository: a uv virtual environment, all dependency extras, pre-commit hooks, and a first unit-test run. Runs only when explicitly requested, never on its own. Use when asked to set up, bootstrap, or repair a development checkout, install project dependencies, fix a missing or broken .venv, or prepare a machine for contributing a pull request. Don't use for debugging a running agent (use adk-debug), for commit and pull-request mechanics (use adk-git), or for re-running formatters on a checkout that is already set up (pre-commit run --all-files). /adk-setup by google](https://skilld.dev/gh/google/adk-python/adk-setup) - [ **/adk-style**22k Python style and codebase conventions for ADK (Agent Development Kit): private-by-default file visibility, imports, type hints, Pydantic v2 models, formatting, docstrings, logging, async I/O, file and test layout, and unit test structure. Use when writing or editing ADK source or tests, deciding whether a new file or symbol should be public or private, naming or placing a test file, fixing a formatter, linter, or type-check failure (pyink, isort, ruff, mypy, addlicense, compliance-checks), or asking whether code matches house style. Don't use for reviewing a whole changeset (use adk-review), writing a developer guide or design doc for a code unit (use adk-unit-guide or adk-unit-design), building or configuring agents (use adk-agent-builder), or installing the toolchain (use adk-setup). /adk-style by google](https://skilld.dev/gh/google/adk-python/adk-style) - [ **/adk-unit-design**22k Writes an as-built architecture document for one ADK code unit — purpose, execution flow, data flow, cross-class dependencies, extension points, and the parts that must not change — to \`docs/design/{topic}/{unit}/index.md\`. It describes the code as implemented, not a proposed design, and its reader is a developer about to change or extend that unit. Use when asked to "write a design doc for {file}", "document the architecture of {class}", "document the extension points of {unit}", or after adding a core class, node type, or plugin base. Don't use for documentation aimed at developers who only call the unit from their own application — that is a usage guide with runnable examples under \`docs/guides/\` (use \`adk-unit-guide\`). Don't use to answer a framework-wide architecture question (use \`adk-architecture\`). /adk-unit-design by google](https://skilld.dev/gh/google/adk-python/adk-unit-design) - [ **/adk-unit-guide**22k Writes a hands-on developer guide for one ADK code unit — a minimal runnable example, how it works, a configuration-option table, advanced uses, limitations, and links to related samples — to \`docs/guides/{topic}/{unit}/index.md\`, then lists it in the index at \`docs/guides/README.md\`. Its reader is a developer calling the unit from their own application, at more depth than the published adk.dev documentation carries. Use when asked to "write a unit guide for {class}", "document how to use {feature}", "add a guide for {file}", or after shipping a user-facing class, node, or plugin. Don't use for internals documentation aimed at someone changing or extending the unit — that is a design document under \`docs/design/\` (use \`adk-unit-design\`). Don't use to write a runnable sample under \`contributing/samples/\` (use \`adk-sample-creator\`). /adk-unit-guide by google](https://skilld.dev/gh/google/adk-python/adk-unit-guide) - [ **/adk-verify-snippets**22k Checks that every Python code block in a Markdown file actually compiles and runs, by extracting each block to a temporary file, executing it in an isolated subprocess, and writing a pass/fail report with per-snippet coverage. Use when the user asks to verify, test, or validate the code samples in a README, a guide, or a documentation page; wants to know which snippets in a Markdown file are broken or out of date; or asks for a snippet verification report. Don't use for running the project's test suite (run pytest directly), for checking code style or formatting (use \`adk-style\`), or for authoring a new runnable sample agent (use \`adk-sample-creator\`). /adk-verify-snippets by google](https://skilld.dev/gh/google/adk-python/adk-verify-snippets) - [ **/bigquery-ai-ml**22k Skill for BigQuery AI and Machine Learning queries using standard SQL and \`AI.\*\` functions (preferred over dedicated tools). /bigquery-ai-ml by google](https://skilld.dev/gh/google/adk-python/bigquery-ai-ml) - [ **/bigquery-graph**22k Skill for Graph Query Language (GQL) or SQL/PGQ queries against a property graph. Includes path finding, multi-hop traversal, topological connection, shortest path, node reachability, edge connectivity, and semantic graph queries. /bigquery-graph by google](https://skilld.dev/gh/google/adk-python/bigquery-graph) - [ **/calc-skill**22k A math calculation skill that runs Python scripts to perform arithmetic. /calc-skill by google](https://skilld.dev/gh/google/adk-python/calc-skill) - [ **/text-skill**22k A text processing skill that formats strings using shell scripts. /text-skill by google](https://skilld.dev/gh/google/adk-python/text-skill) - [ **/weather-skill**22k A skill that provides weather information based on reference data and scripts. /weather-skill by google](https://skilld.dev/gh/google/adk-python/weather-skill) ### [google/adk-kotlin](https://skilld.dev/gh/google/adk-kotlin) 11 skills 258 `npx skilld add google/adk-kotlin` - [ **/cast-fireball**258 Casts a fireball at a specified target. /cast-fireball by google](https://skilld.dev/gh/google/adk-kotlin/cast-fireball) - [ **/echoskill**258 A simple skill that echoes provided arguments. /echoskill by google](https://skilld.dev/gh/google/adk-kotlin/echoskill) - [ **/invalid2**258 Description /invalid2 by google](https://skilld.dev/gh/google/adk-kotlin/invalid2) - [ **/pyskill**258 A simple skill that prints provided arguments using Python. /pyskill by google](https://skilld.dev/gh/google/adk-kotlin/pyskill) - [ **/root-only-skill**258 A skill living directly under the assets root. /root-only-skill by google](https://skilld.dev/gh/google/adk-kotlin/root-only-skill) - [ **/skill-name-mismatch**258 Name field does not match the directory name. /skill-name-mismatch by google](https://skilld.dev/gh/google/adk-kotlin/skill-name-mismatch) - [ **/skill-unauthorized**258 Skill that has a directory outside the allow-list. /skill-unauthorized by google](https://skilld.dev/gh/google/adk-kotlin/skill-unauthorized) - [ **/skill1**258 Description 1 /skill1 by google](https://skilld.dev/gh/google/adk-kotlin/skill1) - [ **/skill2**258 Description 2 /skill2 by google](https://skilld.dev/gh/google/adk-kotlin/skill2) - [ **/summon-familiar**258 Summons a magical creature to assist you. /summon-familiar by google](https://skilld.dev/gh/google/adk-kotlin/summon-familiar) - [ **/valid-skill**258 A valid skill for testing. /valid-skill by google](https://skilld.dev/gh/google/adk-kotlin/valid-skill) ### [google/agents-cli](https://skilld.dev/gh/google/agents-cli) The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying AI agents on Google Cloud. 8 skills 6k `npx skilld add google/agents-cli` - [ **/agents-cli-langchain**6k Use when working in this project — adding tools, editing the agent, running, evaluating, serving or deploying it — or when guidance mentions ADK, LlmAgent, google.adk, adk web, or an ADK runner. This project is LangChain/LangGraph scaffolded by agents-cli, so ADK-specific instructions do not apply. /agents-cli-langchain by google](https://skilld.dev/gh/google/agents-cli/agents-cli-langchain) - [ **/google-agents-cli-adk-code**6k This skill should be used when the user wants to "write agent code", "build an agent with ADK", "add a tool", "create a callback", "define an agent", "use state management" — in a project that needs ADK (Agent Development Kit) API patterns and code examples. It provides a quick reference for agent types, tool definitions, orchestration patterns, callbacks, state management, the graph Workflow API, and reference recipes to study. Do NOT use for scaffolding (use google-agents-cli-scaffold) or deployment (use google-agents-cli-deploy). /google-agents-cli-adk-code by google](https://skilld.dev/gh/google/agents-cli/google-agents-cli-adk-code) - [ **/google-agents-cli-deploy**6k This skill should be used when the user wants to "deploy an agent", "deploy my ADK agent", "set up CI/CD", "configure secrets", "troubleshoot a deployment", or needs guidance on Agent Runtime, Cloud Run, or GKE deployment targets, or binding an agent to an Agent Gateway. Covers deployment workflows, service accounts, rollback, and production infrastructure. Applies to any framework agents-cli deploys (ADK, LangChain, ...). Part of the agents-cli skills suite. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), evaluation (use google-agents-cli-eval), or project scaffolding (use google-agents-cli-scaffold). /google-agents-cli-deploy by google](https://skilld.dev/gh/google/agents-cli/google-agents-cli-deploy) - [ **/google-agents-cli-eval**6k This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Agent Platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold). /google-agents-cli-eval by google](https://skilld.dev/gh/google/agents-cli/google-agents-cli-eval) - [ **/google-agents-cli-observability**6k This skill should be used when the user wants to "set up tracing", "monitor my agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring deployed agents, including ADK (Agent Development Kit) agents. Covers Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations (AgentOps, Phoenix, MLflow, etc.), and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment setup (use google-agents-cli-deploy) or API code patterns (use google-agents-cli-adk-code). /google-agents-cli-observability by google](https://skilld.dev/gh/google/agents-cli/google-agents-cli-observability) - [ **/google-agents-cli-publish**6k This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini Enterprise", "publish to Gemini Enterprise", or needs guidance on the agents-cli publish gemini-enterprise command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy). /google-agents-cli-publish by google](https://skilld.dev/gh/google/agents-cli/google-agents-cli-publish) - [ **/google-agents-cli-scaffold**6k This skill should be used when the user wants to "create an agent project", "start a new ADK project", "build me a new agent", "add CI/CD to my project", "add deployment", "enhance my project", or "upgrade my project". Part of the agents-cli skills suite. Covers \`agents-cli scaffold create\`, \`scaffold enhance\`, and \`scaffold upgrade\` commands, template options, deployment targets, and the prototype-first workflow. Do NOT use for writing agent code (ADK projects: use google-agents-cli-adk-code) or deployment operations (use google-agents-cli-deploy). /google-agents-cli-scaffold by google](https://skilld.dev/gh/google/agents-cli/google-agents-cli-scaffold) - [ **/google-agents-cli-workflow**6k This skill should be used when the user wants to "develop an agent", "build an agent using ADK", "run the agent locally", "debug agent code", "test an agent", "deploy an agent", "publish an agent", "monitor an agent", or needs the ADK (Agent Development Kit) development lifecycle and coding guidelines. Entrypoint for building ADK agents. Always active — provides the full workflow (scaffold, build, evaluate, deploy, publish, observe), code preservation rules, model selection guidance, and troubleshooting steps for ADK or any agent development. /google-agents-cli-workflow by google](https://skilld.dev/gh/google/agents-cli/google-agents-cli-workflow) ### [google/meridian](https://skilld.dev/gh/google/meridian) Meridian is an MMM framework that enables advertisers to set up and run their own in-house models. 5 skills 1.6k `npx skilld add google/meridian` - [ **/meridianbudgetoptimization**1.6k Loads a fitted Meridian model and runs budget optimization scenarios. Use when the user wants to load a saved model and find the optimal budget allocation or target ROI spending. Don't use for visualizing model performance (use meridian-result-visualization) or building/fitting the model (use meridian-model-building). /meridianbudgetoptimization by google](https://skilld.dev/gh/google/meridian/meridianbudgetoptimization) - [ **/meridiandocconsultant**1.6k Assists users with questions about Meridian Marketing Mix Modeling concepts, parameters, and best practices by finding and consulting the relevant documentation. Use when the user asks for explanations or guidance on Meridian topics. Don't use for writing code or running models directly. /meridiandocconsultant by google](https://skilld.dev/gh/google/meridian/meridiandocconsultant) - [ **/meridianmodelbuilding**1.6k Guides users through building a Meridian Marketing Mix Modeling (MMM) model. Use when a user wants to load data, map columns, configure ModelSpec, run Exploratory Data Analysis (EDA), fit a model, and save the model. Don't use for visualizing results or creating a scenario planner. /meridianmodelbuilding by google](https://skilld.dev/gh/google/meridian/meridianmodelbuilding) - [ **/meridianresultvisualization**1.6k Loads a fitted Meridian model and generates standard visualization reports: Model Results Summary. Use when the user wants to load a saved model and view results (model performance, fit, health). Don't use for running budget optimization (use meridian-budget-optimization) or building/fitting the model (use meridian-model-building). /meridianresultvisualization by google](https://skilld.dev/gh/google/meridian/meridianresultvisualization) - [ **/meridianscenarioplanner**1.6k Generates Scenario Planner data from a fitted Meridian model and exports it for Looker Studio dashboard creation via Colab handoff. Use when the user wants to generate scenario planning data, budget grids, or Looker Studio dashboards from a saved model. Don't use for visualizing model results (use meridian-result-visualization) or running standard budget optimization (use meridian-budget-optimization). /meridianscenarioplanner by google](https://skilld.dev/gh/google/meridian/meridianscenarioplanner) ### [google/sam](https://skilld.dev/gh/google/sam) The Open-Source Agent Mesh 1 skill 951 `npx skilld add google/sam` - [ **/sam-mesh**951 Use when local tools cannot provide a needed capability and a SAM agent mesh can: inspect mesh state, discover reachable services/tools, describe and call namespaced remote MCP tools, reach OpenAI-compatible inference models hosted by mesh peers, and hand work to A2A agents on the mesh through the official a2a CLI. Also use to set up, join, or reconnect a sam-node when its MCP tools are not callable yet. /sam-mesh by google](https://skilld.dev/gh/google/sam) Skills published by Google. Checked GitHub just now