GITHUB AGENT SKILLS / 技能收录
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我们从 GitHub 持续收录、审核并分类优质的 Agent Skills，按职业与使用场景整理，复制一行命令即可安装到 Claude Code、Cursor 等智能体。
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Microsoft
@microsoft
openclaw
@openclaw
Anthropic
@anthropics
OpenAI
@openai
The Apache Software Foundation
@apache
GitHub
@github
AutoGPT
@Significant-Gravitas
Garry Tan
@garrytan全部 Skills 463411
gke-workload-identity
Configures and diagnoses Workload Identity Federation for GKE authentication failures for Pods (403 "iam.serviceAccounts.getAccessToken" / permission denied, "could not find default credentials", or GKE metadata server unreachable) by verifying cluster and node-pool Workload Identity configuration, the Kubernetes ServiceAccount (KSA) to IAM binding (direct principal binding and legacy Google ServiceAccount impersonation), target-resource IAM roles, and gke-metadata-server health. Use when setting up KSA/GSA bindings (`roles/iam.workloadIdentityUser`, `iam.gke.io/gcp-service-account`) or when a Pod cannot authenticate to Google Cloud APIs. Don't use for in-cluster Kubernetes RBAC errors (API-server authorization), general workload crashes (use gke-workload-troubleshooting), or Pod Security Standards and NetworkPolicies (use gke-workload-security).
gke-multitenancy
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).
compute-on-demand-reservations
Inspects, verifies, and manages Google Compute Engine (GCE) On-Demand reservations and analyzes consumed versus available reserved capacity. Use when checking active reservation capacity, determining whether reserved VMs are available or exhausted, verifying reservation targeting (automatic versus specific reservation), or sharing reservations across projects. Don't use for Spot capacity advice (use gcloud compute advice capacity --provisioning-model=SPOT) or future calendar bookings (use compute-future-reservations).
cloud-operator
Google Cloud (GCP) assistant and operator via the autocloud MCP server. Use for any GCP request: how-to, resources, Terraform/Kubernetes/Helm, rollouts, incidents, costs. Invoke it before answering a GCP question from your own knowledge or documentation search, and before proposing an architecture or backend, even when no cloud is named. Invoke it before reading or editing local *.tf or Kubernetes YAML. Don't use for non-GCP tasks or local machine setup like installing gcloud and setting up GCP.
google-cloud-waf-reliability
Evaluates, designs, and improves the reliability, resilience, availability, fault tolerance, and disaster recovery (DR) of Google Cloud workloads based on the design principles and recommendations in the Reliability pillar of the Google Cloud Well-Architected Framework. Use when the user asks about reliability-related topics like workload uptime, designing for high availability (HA) or DR, setting and meeting RTO/RPO targets, SRE best practices, backup strategies, multi-region failover, or fault-tolerant architecture on Google Cloud. Don't use for other Well-Architected Framework pillars such as Cost Optimization, Operational Excellence, or Security, or for hands-on resource deployment and live incident troubleshooting.
cloud-monitoring-alert-configuration
Configures Cloud Monitoring alerting policies using Terraform and PromQL across Cloud Run, Google Kubernetes Engine (GKE), Compute Engine, AI Hypercomputer reservations, Vertex AI Agent Engine, and generic Google Cloud resources. Use when creating, reviewing, migrating, or deduplicating Terraform alerting policies for latency, traffic, error rates, saturation, host or reservation maintenance, GPU XID insights, or AI agent telemetry. Don't use for standalone PromQL query authoring without alerting, log querying, or billing cost audits.
application-integration-authoring
Builds, versions, publishes, tests, and executes Google Cloud Application Integration workflows through the REST API and Python discovery client, and promotes versions across environments. Use when listing integrations, downloading or uploading integration versions as JSON, configuring API triggers or config variables, publishing drafts, invoking integrations, or automating CI/CD promotion. Do not use for initial region provisioning and IAM setup (use application-integration-basics) or diagnosing failed runs and logs (use application-integration-troubleshooting).
google-cloud-waf-security
Evaluates Google Cloud workloads and provides actionable recommendations for identity management, access control, permissions and roles, network and perimeter security, data security and encryption, security logging and threat detection, software supply chain hardening, AI security, data privacy, regulatory compliance, and cloud sovereignty. The recommendations are aligned with the Security, Privacy, and Compliance pillar of the Google Cloud Well-Architected Framework (WAF). Use when the user asks about firewall rules, zero trust, shared responsibility and shared fate, audit logging, security monitoring, threat mitigation, shift-left CI/CD security, Secure AI Framework (SAIF), data residency, or hardening Google Cloud resources. Don't use for other Well-Architected Framework pillars (Cost Optimization, Operational Excellence, Reliability, Performance Optimization, or Sustainability).
google-cloud-solution-build-deploy-agents
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-architecture
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-agentic-ai-bidirectional-streaming
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-global-frontend-configuration
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-filestore-nfs-browser
Inspects, searches, and reads files and POSIX metadata on Filestore (NFS) instances on Google Cloud without local NFS client packages or root privileges. Use when browsing Filestore shares, searching files, reading remote logs, or inspecting file attributes; don't use for Cloud Storage buckets, Cloud NetApp Volumes, Persistent Disks, or modifying/deleting files.
google-cloud-filestore-log-troubleshooting
Diagnoses and resolves Filestore client mount failures on Google Cloud, permission errors (EACCES), and network timeouts (ETIMEDOUT). Use when an NFS mount hangs or fails from a Compute Engine VM, GKE pod, Cloud Run service, or Vertex AI workload, when `mount.nfs` reports "Connection timed out" or "access denied by server", when checking whether VPC ingress firewall rules or `nfsExportOptions` allow a client IP, or when a previously working Filestore share suddenly stops mounting after an administrative change. Don't use for Cloud Storage (GCS) buckets, Persistent Disk, or Cloud NetApp Volumes, and don't use for Filestore capacity scaling or backup and export-policy auditing.
google-cloud-filestore-autoscale
Inspects Filestore capacity and utilization on Google Cloud, 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-auditing
Audits Filestore instances on Google Cloud across projects for disaster recovery readiness (missing or stale backups), security access governance (overly permissive NFS export rules, 0.0.0.0/0 exposure, missing ROOT_SQUASH), and reliability compliance (Physical Zone Isolation PZI and Physical Zone Separation PZS). Use when assessing storage health posture, auditing NFS export permissions, identifying unprotected file shares, or validating zone failure domains. Don't use for Cloud Storage buckets, Persistent Disk, or NetApp Volumes.
gcloud
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.
datalineage-summary
Summarizes data lineage graphs on Google Cloud to help users debug data quality issues and understand data provenance for BigQuery and Cloud Storage. 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).