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Triggers on requests like \"EKS review\", \"EKS best practices audit\", \"EKS operational assessment\", \"review my EKS cluster\", or \"EKS health check\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"aws","AWS (Amazon)","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Faws.png",[12,16,19,22],{"name":13,"slug":14,"type":15},"Operations","operations","tag",{"name":17,"slug":18,"type":15},"Audit","audit",{"name":20,"slug":21,"type":15},"Kubernetes","kubernetes",{"name":23,"slug":8,"type":15},"AWS",35,"https:\u002F\u002Fgithub.com\u002Faws\u002Ftools-for-devops-agent","2026-08-20T03:53:20.524374",null,30,[30,31,32,33,34,8,35,36,37,38,39,40,41,42,43,44,45,46],"agent-skills","agentic-ai","agents","ai-agents","aiops","aws-devops-agent","cloud-operations","custom-agents","devops","devops-agent-skills","frontier-agent","incident-response","operational-excellence","root-cause-analysis","skills","sre","support",{"repoUrl":25,"stars":24,"forks":28,"topics":48,"description":49},[30,31,32,33,34,8,35,36,37,38,39,40,41,42,43,44,45,46],"Open-source tools for AWS DevOps Agent - extend DevOps Agent with ready-to-use skills, custom agents, and other tools, for incident response, root cause analysis, and operational troubleshooting","https:\u002F\u002Fgithub.com\u002Faws\u002Ftools-for-devops-agent\u002Ftree\u002FHEAD\u002Fskills\u002Feks-operation-review","---\nname: eks-operation-review\ndescription: Comprehensive Amazon EKS operational review aligned with the AWS EKS\n  Best Practices Guide. Use this skill when a user asks to review, audit, or assess\n  EKS clusters for best practices compliance, operational readiness, security posture,\n  cost optimization, reliability, networking, scalability, or upgrade readiness.\n  Triggers on requests like \"EKS review\", \"EKS best practices audit\", \"EKS operational\n  assessment\", \"review my EKS cluster\", or \"EKS health check\".\nmetadata:\n  author: yakiratz-aws\n  version: \"1.0.0\"\n  aws-devops-agent-skills.agent-types: \"Chat tasks, Evaluation\"\n  aws-devops-agent-skills.aws-services: \"Amazon EKS\"\n  aws-devops-agent-skills.technical-domains: \"Containers\"\n---\n\n# EKS Operational Review\n\nConduct a comprehensive operational review of Amazon EKS clusters aligned with the\n[EKS Best Practices Guide](https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fintroduction.html).\n\n## When to Use\n\nActivate this skill when the user asks to:\n- Review, audit, or assess EKS clusters\n- Check EKS best practices compliance\n- Evaluate EKS security, cost, reliability, networking, or scalability\n- Perform an EKS operational readiness review\n- Investigate EKS cluster health or configuration\n\n## Step 1: Identify Target Clusters\n\nAsk the user which EKS clusters to review. Accept:\n- Specific cluster names and regions\n- \"all clusters\" in specific regions\n- \"all clusters in all regions\"\n\nUse the EKS topology data available in the Agent Space to identify clusters.\nQuery CloudWatch and AWS APIs to discover clusters:\n- List EKS clusters across the configured account regions\n- For each cluster, collect configuration details\n\n## Step 2: Collect Cluster Configuration\n\n**Data source priority**: If Kubernetes API access is available (via connected MCP servers such as kubernetes-mcp-server, EKS MCP server, or direct K8s API tools), use it FIRST to get live cluster state. K8s API provides the most accurate, real-time data. Fall back to AWS APIs and CloudWatch only for data not available via K8s API.\n\n**K8s API tools** (use first when available):\n- `resources_list` \u002F `resources_get` — list\u002Fread any K8s resource by apiVersion and kind\n- `pods_list` \u002F `pods_get` \u002F `pods_log` \u002F `pods_top` — pod operations\n- `nodes_top` — node resource usage\n- `events_list` — K8s events\n- `configuration_contexts_list` — available cluster contexts\n\nFor EACH cluster, gather the following data. **Try K8s API first, then AWS API as fallback**:\n\n### 2.1 EKS Cluster Config\n**AWS API** (no K8s equivalent): Kubernetes version, platform version, control plane logging, secrets encryption, endpoint access, authentication mode, access entries, Auto Mode, tags\n\n### 2.2 Node Groups & Compute\n**K8s API first**:\n- `resources_list(apiVersion=\"v1\", kind=\"Node\")` — live node list with labels, capacity, allocatable, conditions\n- `nodes_top` — actual CPU\u002Fmemory usage per node\n- `resources_list(apiVersion=\"karpenter.sh\u002Fv1\", kind=\"NodePool\")` — Karpenter NodePools\n- `resources_get(apiVersion=\"karpenter.sh\u002Fv1\", kind=\"NodePool\", name=\u003Cname>)` — full NodePool spec (consolidation, limits, disruption, requirements)\n- `resources_list(apiVersion=\"karpenter.k8s.aws\u002Fv1\", kind=\"EC2NodeClass\")` — EC2NodeClasses\n- `resources_get(apiVersion=\"karpenter.k8s.aws\u002Fv1\", kind=\"EC2NodeClass\", name=\u003Cname>)` — full spec (amiFamily, blockDeviceMappings, metadataOptions, subnets, SGs)\n\n**AWS API fallback**: Managed node groups (instance types, scaling config, AMI type, capacity type, AZ distribution)\n\n### 2.3 Add-ons\n**K8s API first**:\n- `resources_list(apiVersion=\"apps\u002Fv1\", kind=\"Deployment\", namespace=\"kube-system\")` — all system deployments with image versions\n- `resources_list(apiVersion=\"apps\u002Fv1\", kind=\"DaemonSet\", namespace=\"kube-system\")` — all system daemonsets with image versions\n\n**AWS API fallback**: EKS managed add-ons (name, version, status, health)\n\n### 2.4 Networking\n**K8s API first**:\n- `resources_get(apiVersion=\"apps\u002Fv1\", kind=\"DaemonSet\", name=\"aws-node\", namespace=\"kube-system\")` — VPC CNI config (env vars: ENABLE_PREFIX_DELEGATION, WARM_IP_TARGET, etc.)\n- `resources_get(apiVersion=\"v1\", kind=\"ConfigMap\", name=\"coredns\", namespace=\"kube-system\")` — CoreDNS Corefile\n- `resources_get(apiVersion=\"apps\u002Fv1\", kind=\"Deployment\", name=\"coredns\", namespace=\"kube-system\")` — CoreDNS replicas, resources, topology\n- `resources_list(apiVersion=\"networking.k8s.io\u002Fv1\", kind=\"NetworkPolicy\")` — network policies\n- `resources_list(apiVersion=\"v1\", kind=\"Service\")` — services and load balancers\n\n**AWS API** (no K8s equivalent): VPC CIDR, subnet IP availability, security groups, VPC endpoints, NAT gateways\n\n### 2.5 Security\n**K8s API first**:\n- `resources_list(apiVersion=\"rbac.authorization.k8s.io\u002Fv1\", kind=\"ClusterRoleBinding\")` — RBAC bindings (check cluster-admin, system:anonymous)\n- `resources_list(apiVersion=\"rbac.authorization.k8s.io\u002Fv1\", kind=\"ClusterRole\")` — roles with wildcard permissions\n- `resources_get(apiVersion=\"v1\", kind=\"ConfigMap\", name=\"aws-auth\", namespace=\"kube-system\")` — aws-auth status\n- `resources_list(apiVersion=\"v1\", kind=\"ServiceAccount\")` — check IRSA annotations (eks.amazonaws.com\u002Frole-arn)\n- `resources_list(apiVersion=\"v1\", kind=\"Namespace\")` — check Pod Security Standards labels (pod-security.kubernetes.io\u002Fenforce)\n\n**AWS API** (no K8s equivalent): Access entries, Pod Identity associations, IAM role policies, ECR scan config\n\n### 2.6 Workloads\n**K8s API first**:\n- `resources_list(apiVersion=\"apps\u002Fv1\", kind=\"Deployment\")` — all deployments\n- `resources_get(apiVersion=\"apps\u002Fv1\", kind=\"Deployment\", name=\u003Cname>, namespace=\u003Cns>)` — full spec: probes, resources, securityContext, topologySpreadConstraints, terminationGracePeriodSeconds\n- `resources_list(apiVersion=\"apps\u002Fv1\", kind=\"StatefulSet\")` — statefulsets\n- `resources_list(apiVersion=\"autoscaling\u002Fv2\", kind=\"HorizontalPodAutoscaler\")` — HPAs\n- `resources_list(apiVersion=\"policy\u002Fv1\", kind=\"PodDisruptionBudget\")` — PDBs\n- `pods_top` — actual pod resource usage vs requests\n- `pods_list(fieldSelector=\"status.phase!=Running,status.phase!=Succeeded\")` — failing pods\n- TopologySpreadConstraints for HA\n\n### 2.7 Storage\n**K8s API first**:\n- `resources_list(apiVersion=\"storage.k8s.io\u002Fv1\", kind=\"StorageClass\")` — check gp3 vs gp2, provisioner\n- `resources_list(apiVersion=\"v1\", kind=\"PersistentVolume\")` — PV status, reclaim policy\n- `resources_list(apiVersion=\"v1\", kind=\"PersistentVolumeClaim\")` — bound\u002Funbound PVCs\n- `resources_list(apiVersion=\"v1\", kind=\"ResourceQuota\")` — namespace quotas\n- `resources_list(apiVersion=\"v1\", kind=\"LimitRange\")` — default limits\n\n## Step 3: Collect Observability Data (7-Day Historical)\n\n### 3.1 CloudWatch Metrics (7 days)\n\n**Container Insights** (namespace: ContainerInsights):\n- node_cpu_utilization (Average, Maximum)\n- node_memory_utilization (Average, Maximum)\n- pod_cpu_utilization (Average)\n- pod_memory_utilization (Average)\n- node_filesystem_utilization (Average)\n- cluster_node_count (Average)\n- cluster_failed_node_count (Maximum)\n- pod_number_of_container_restarts (Sum)\n\n**EKS Control Plane** (namespace: AWS\u002FEKS):\n- apiserver_request_duration_seconds (Average)\n- apiserver_admission_webhook_rejection_count (Sum)\n- scheduler_pending_pods (Maximum)\n\n**EC2 Node Metrics** (namespace: AWS\u002FEC2, per instance):\n- CPUUtilization (Average, Maximum)\n- StatusCheckFailed (Maximum)\n\n### 3.2 CloudWatch Logs (7 days)\n\nQuery control plane logs for error patterns:\n- `ERROR` — general errors (count)\n- `429` — API server throttling\n- `OOMKilled` — memory limit issues\n- `FailedScheduling` — capacity\u002Fconstraint issues\n- `Evicted` — node pressure evictions\n\n### 3.3 CloudTrail Events (7 days)\n\nQuery EKS API events:\n- UpdateClusterConfig, UpdateNodegroupConfig — configuration changes\n- CreateAccessEntry — new access granted\n- DeleteCluster — cluster deletions\n- AccessDenied\u002FUnauthorizedAccess errors — security concerns\n\n### 3.4 EKS Upgrade Insights\n\nFetch upgrade readiness insights:\n- UPGRADE_READINESS category insights\n- MISCONFIGURATION category insights\n- Status, description, recommendations, affected resources for each\n\n## Step 4: Analyze Against Best Practices\n\nEvaluate ALL collected data against these 12 sections from the EKS Best Practices Guide.\nAssign severity to every finding: CRITICAL, HIGH, MEDIUM, LOW, or INFO.\n\n### 4.1 Security\nRef: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fsecurity.html\n\n**IAM & Access Management** (Ref: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fidentity-and-access-management.html):\n- Authentication mode: API recommended. CONFIG_MAP only → HIGH\n- Access Entries: minimize AmazonEKSClusterAdminPolicy. Cluster creator admin removed? → MEDIUM if not\n- aws-auth ConfigMap still in use → MEDIUM (migrate to Access Entries)\n- aws-auth maps to system:masters → HIGH\n- EKS Pod Identity: associations present? Roles least-privilege? Preferred over IRSA\n- IRSA: ServiceAccount annotations, OIDC provider, role policies\n- Cluster\u002Fnode role: least-privilege (no admin\u002Fwildcard)\n- RBAC: ClusterRoleBindings to cluster-admin minimized. system:anonymous → CRITICAL\n- Regional STS endpoint (not global sts.amazonaws.com)\n\n**Pod Security**: Pod Security Standards enforced, no privileged containers, SecurityContext set\n**Runtime Security**: Non-root containers, read-only root filesystems\n**Network Security**: NetworkPolicies present, VPC endpoints for private access\n**Multi-tenancy**: Namespace isolation, RBAC per namespace, ResourceQuotas\n**Detective Controls**: All 5 log types enabled, CloudTrail events, CloudWatch alarms\n**Infrastructure Security**: Private endpoint, IMDSv2 enforced (httpTokens=required), AMI currency\n**Data Encryption**: KMS envelope encryption, EBS encryption\n**Image Security**: ECR scan-on-push, image pull policies\n\n### 4.2 Reliability\nRef: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Freliability.html\n\n**Applications**: Probes (liveness\u002Freadiness\u002Fstartup), PDBs, TopologySpreadConstraints, graceful shutdown, resource requests\u002Flimits\n**Control Plane**: Version within N-2, all logs enabled, insights passing. 7-day: API latency, throttling (429), webhook rejections, pending pods\n**Data Plane**: Multi-AZ (≥2, ideally 3), managed node groups, auto-scaling. 7-day: failed nodes, CPU\u002Fmemory saturation, StatusCheckFailed\n\n### 4.3 Karpenter\nRef: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fkarpenter.html\n\nPer NodePool: consolidationPolicy (WhenEmptyOrUnderutilized recommended), disruption budgets, instance diversity, Spot usage, AZ spread, resource limits\nPer EC2NodeClass: amiFamily, blockDeviceMappings, metadataOptions (httpTokens=required), subnet\u002FSG selectors, AMI age\n\n### 4.4 Cluster Autoscaler\nDeployment present, expander strategy, scale-down settings, balance-similar-node-groups, version compatibility\n\n### 4.5 EKS Auto Mode\nAuto mode enabled\u002Fdisabled, node pool configuration, disruption controls\n\n### 4.6 Networking\nRef: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fnetworking.html\n\nVPC CNI version and config, prefix delegation, subnet IP availability:\n- CRITICAL if any subnet \u003C50 IPs\n- HIGH if any subnet \u003C20% free\n- MEDIUM if total IPs \u003C 2x node count\nVPC CIDR size (\u002F16 recommended), CoreDNS config and scaling, VPC endpoints, NAT redundancy\n\n### 4.7 Scalability\nRef: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fscalability.html\n\nControl plane: API throttling (429 in logs), CRD count\nData plane: Node scaling headroom, instance diversity, Karpenter NodePool limits vs actual\nCluster services: CoreDNS scaled, metrics-server, addon versions\nWorkloads: HPA configured, resource requests set, pod restart count (>50 in 7d → MEDIUM, >200 → HIGH)\n\n**Data Plane Scaling** (Ref: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fscale-data-plane.html):\n- Automatic autoscaling configured (Karpenter preferred)\n- Instance type diversity (avoid single type)\n- T-series burstable in production → MEDIUM\n- AMI update automation (EKS optimized\u002FBottlerocket, age check)\n- Multiple EBS volumes for container state\n- Patching strategy (SSM Patch Manager, update operators)\n\n### 4.8 Cluster Upgrades\nRef: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fcluster-upgrades.html\n\nVersion currency: CRITICAL if N-3+, HIGH if N-2, MEDIUM if N-1\nEKS upgrade insights (UPGRADE_READINESS): list all with status, recommendations\nAddon compatibility, deprecated API usage, PDB coverage, node group update strategy\n\n### 4.9 Cost Optimization\nRef: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fcost-opt.html\n\n**Resource Utilization Summary** (from 7-day metrics):\n| Metric | 7-Day Avg | 7-Day Max | Assessment |\nUnder-utilized (\u003C30% CPU \u002F \u003C40% mem) → cost waste. Over-utilized (>70%) → saturation risk.\n\n**Recommendations**:\n1. Instance right-sizing: per-instance CPU\u002Fmemory vs capacity\n2. Spot adoption: Karpenter NodePool capacity-type, stateless workloads\n3. Graviton migration: x86 → arm64 families (~20% savings)\n4. Storage: gp2 → gp3, unused PV cleanup\n5. Karpenter consolidation: WhenEmpty → WhenEmptyOrUnderutilized\n6. Karpenter NodePool cost review: Spot vs On-Demand, instance sizes vs pod requests, limits vs actual, EBS cost\n7. Cost allocation tags\n8. Idle resources: 0-replica Deployments, orphaned PVCs\n9. Savings Plans for baseline on-demand\n10. Namespace resource quotas\n\n### 4.10–4.12 Conditional Sections\n- Windows Containers (if detected)\n- Hybrid Deployments (if detected)\n- AI\u002FML Workloads (if GPU node groups detected)\n\n## Step 5: Generate Report\n\n**Generate a separate shareable report artifact for EACH cluster reviewed.**\n\nArtifact naming: `eks-review-\u003Ccluster-name>-\u003CYYYY-MM-DD>.md`\nExample: `eks-review-prod-cluster-2026-04-29.md`\n\nFor each cluster, create the artifact as a Markdown document with these sections:\n\n### Report Header\n```\n# EKS Operational Review — \u003Ccluster-name>\nAccount: \u003Caccount-id> | Region: \u003Cregion> | Date: \u003CYYYY-MM-DD> | K8s Version: \u003Cversion>\n```\n\n### Executive Summary\n- Cluster health: ✅ HEALTHY \u002F ⚠️ WARNINGS \u002F ❌ CRITICAL\n- Finding counts by severity\n- Top 3 critical\u002Fhigh items\n\n### Add-ons Inventory\n| Add-on | Version | Type | Status | Notes |\n\n### Findings by Section\nFor each of the 12 sections above, present:\n| # | Finding | Severity | Current State | Recommendation |\n\n### CloudWatch Metrics (7-Day)\n| Metric | Category | 7-Day Avg | 7-Day Max | Status | Finding |\n\n### CloudWatch Logs Analysis (7-Day)\n| Pattern | Occurrences | Severity | Finding |\n\n### CloudTrail Events (7-Day)\nEvent summary + notable events + findings\n\n### EKS Upgrade Insights\nAll insights with status, description, recommendations\n\n### Resource Utilization & Cost\nUtilization summary table + specific cost optimization recommendations\n\n### Priority Matrix\n| # | Finding | Severity | Section | Effort | Impact |\nAll findings sorted by severity\n\n### Next Steps\n- Immediate (CRITICAL\u002FHIGH — 7 days)\n- Short-term (MEDIUM — 30 days)\n- Long-term (LOW — 90 days)\n\n### Appendix — Reference Links\n- Security: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fsecurity.html\n- IAM: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fidentity-and-access-management.html\n- Reliability: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Freliability.html\n- Networking: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fnetworking.html\n- Scalability: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fscalability.html\n- Data Plane Scaling: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fscale-data-plane.html\n- Cluster Upgrades: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fcluster-upgrades.html\n- Cost Optimization: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fcost-opt.html\n- Karpenter: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fkarpenter.html\n- Auto Mode: https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fautomode.html\n\n## Severity Definitions\n\n| Severity | Definition | SLA |\n|----------|-----------|-----|\n| CRITICAL | Immediate risk to availability, security, or data integrity | Fix within 24-48 hours |\n| HIGH | Significant gap that could lead to incidents | Fix within 1 week |\n| MEDIUM | Notable improvement opportunity | Plan within 30 days |\n| LOW | Minor optimization or hardening | Address when convenient |\n| INFO | Observation, no action required | N\u002FA |\n",{"data":53,"body":61},{"name":4,"description":6,"metadata":54},{"author":55,"version":56,"aws-devops-agent-skills":57},"yakiratz-aws","1.0.0",{"agent-types":58,"aws-services":59,"technical-domains":60},"Chat tasks, Evaluation","Amazon EKS","Containers",{"type":62,"children":63},"root",[64,73,90,97,102,132,138,143,161,166,179,185,196,206,294,306,313,323,329,338,406,416,422,430,455,464,470,478,536,545,551,559,617,626,632,640,724,730,738,796,802,808,818,861,871,889,899,912,918,923,981,987,992,1015,1021,1026,1044,1050,1055,1061,1072,1090,1138,1197,1203,1213,1237,1243,1253,1258,1264,1269,1275,1280,1286,1296,1301,1319,1325,1335,1340,1356,1389,1395,1405,1410,1416,1426,1436,1445,1499,1505,1523,1529,1537,1556,1561,1567,1579,1585,1603,1609,1614,1620,1625,1631,1636,1642,1647,1653,1658,1664,1669,1675,1680,1686,1691,1697,1715,1721,1825,1831],{"type":65,"tag":66,"props":67,"children":69},"element","h1",{"id":68},"eks-operational-review",[70],{"type":71,"value":72},"text","EKS Operational Review",{"type":65,"tag":74,"props":75,"children":76},"p",{},[77,79,88],{"type":71,"value":78},"Conduct a comprehensive operational review of Amazon EKS clusters aligned with the\n",{"type":65,"tag":80,"props":81,"children":85},"a",{"href":82,"rel":83},"https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fintroduction.html",[84],"nofollow",[86],{"type":71,"value":87},"EKS Best Practices Guide",{"type":71,"value":89},".",{"type":65,"tag":91,"props":92,"children":94},"h2",{"id":93},"when-to-use",[95],{"type":71,"value":96},"When to Use",{"type":65,"tag":74,"props":98,"children":99},{},[100],{"type":71,"value":101},"Activate this skill when the user asks to:",{"type":65,"tag":103,"props":104,"children":105},"ul",{},[106,112,117,122,127],{"type":65,"tag":107,"props":108,"children":109},"li",{},[110],{"type":71,"value":111},"Review, audit, or assess EKS clusters",{"type":65,"tag":107,"props":113,"children":114},{},[115],{"type":71,"value":116},"Check EKS best practices compliance",{"type":65,"tag":107,"props":118,"children":119},{},[120],{"type":71,"value":121},"Evaluate EKS security, cost, reliability, networking, or scalability",{"type":65,"tag":107,"props":123,"children":124},{},[125],{"type":71,"value":126},"Perform an EKS operational readiness review",{"type":65,"tag":107,"props":128,"children":129},{},[130],{"type":71,"value":131},"Investigate EKS cluster health or configuration",{"type":65,"tag":91,"props":133,"children":135},{"id":134},"step-1-identify-target-clusters",[136],{"type":71,"value":137},"Step 1: Identify Target Clusters",{"type":65,"tag":74,"props":139,"children":140},{},[141],{"type":71,"value":142},"Ask the user which EKS clusters to review. 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Links",{"type":65,"tag":103,"props":1722,"children":1723},{},[1724,1734,1744,1754,1764,1774,1784,1794,1804,1814],{"type":65,"tag":107,"props":1725,"children":1726},{},[1727,1729],{"type":71,"value":1728},"Security: ",{"type":65,"tag":80,"props":1730,"children":1732},{"href":1068,"rel":1731},[84],[1733],{"type":71,"value":1068},{"type":65,"tag":107,"props":1735,"children":1736},{},[1737,1739],{"type":71,"value":1738},"IAM: ",{"type":65,"tag":80,"props":1740,"children":1742},{"href":1084,"rel":1741},[84],[1743],{"type":71,"value":1084},{"type":65,"tag":107,"props":1745,"children":1746},{},[1747,1749],{"type":71,"value":1748},"Reliability: ",{"type":65,"tag":80,"props":1750,"children":1752},{"href":1209,"rel":1751},[84],[1753],{"type":71,"value":1209},{"type":65,"tag":107,"props":1755,"children":1756},{},[1757,1759],{"type":71,"value":1758},"Networking: ",{"type":65,"tag":80,"props":1760,"children":1762},{"href":1292,"rel":1761},[84],[1763],{"type":71,"value":1292},{"type":65,"tag":107,"props":1765,"children":1766},{},[1767,1769],{"type":71,"value":1768},"Scalability: ",{"type":65,"tag":80,"props":1770,"children":1772},{"href":1331,"rel":1771},[84],[1773],{"type":71,"value":1331},{"type":65,"tag":107,"props":1775,"children":1776},{},[1777,1779],{"type":71,"value":1778},"Data Plane Scaling: ",{"type":65,"tag":80,"props":1780,"children":1782},{"href":1351,"rel":1781},[84],[1783],{"type":71,"value":1351},{"type":65,"tag":107,"props":1785,"children":1786},{},[1787,1789],{"type":71,"value":1788},"Cluster Upgrades: ",{"type":65,"tag":80,"props":1790,"children":1792},{"href":1401,"rel":1791},[84],[1793],{"type":71,"value":1401},{"type":65,"tag":107,"props":1795,"children":1796},{},[1797,1799],{"type":71,"value":1798},"Cost Optimization: ",{"type":65,"tag":80,"props":1800,"children":1802},{"href":1422,"rel":1801},[84],[1803],{"type":71,"value":1422},{"type":65,"tag":107,"props":1805,"children":1806},{},[1807,1809],{"type":71,"value":1808},"Karpenter: ",{"type":65,"tag":80,"props":1810,"children":1812},{"href":1249,"rel":1811},[84],[1813],{"type":71,"value":1249},{"type":65,"tag":107,"props":1815,"children":1816},{},[1817,1819],{"type":71,"value":1818},"Auto Mode: ",{"type":65,"tag":80,"props":1820,"children":1823},{"href":1821,"rel":1822},"https:\u002F\u002Fdocs.aws.amazon.com\u002Feks\u002Flatest\u002Fbest-practices\u002Fautomode.html",[84],[1824],{"type":71,"value":1821},{"type":65,"tag":91,"props":1826,"children":1828},{"id":1827},"severity-definitions",[1829],{"type":71,"value":1830},"Severity Definitions",{"type":65,"tag":1832,"props":1833,"children":1834},"table",{},[1835,1859],{"type":65,"tag":1836,"props":1837,"children":1838},"thead",{},[1839],{"type":65,"tag":1840,"props":1841,"children":1842},"tr",{},[1843,1849,1854],{"type":65,"tag":1844,"props":1845,"children":1846},"th",{},[1847],{"type":71,"value":1848},"Severity",{"type":65,"tag":1844,"props":1850,"children":1851},{},[1852],{"type":71,"value":1853},"Definition",{"type":65,"tag":1844,"props":1855,"children":1856},{},[1857],{"type":71,"value":1858},"SLA",{"type":65,"tag":1860,"props":1861,"children":1862},"tbody",{},[1863,1882,1900,1918,1936],{"type":65,"tag":1840,"props":1864,"children":1865},{},[1866,1872,1877],{"type":65,"tag":1867,"props":1868,"children":1869},"td",{},[1870],{"type":71,"value":1871},"CRITICAL",{"type":65,"tag":1867,"props":1873,"children":1874},{},[1875],{"type":71,"value":1876},"Immediate risk to availability, security, or data integrity",{"type":65,"tag":1867,"props":1878,"children":1879},{},[1880],{"type":71,"value":1881},"Fix within 24-48 hours",{"type":65,"tag":1840,"props":1883,"children":1884},{},[1885,1890,1895],{"type":65,"tag":1867,"props":1886,"children":1887},{},[1888],{"type":71,"value":1889},"HIGH",{"type":65,"tag":1867,"props":1891,"children":1892},{},[1893],{"type":71,"value":1894},"Significant gap that could lead to incidents",{"type":65,"tag":1867,"props":1896,"children":1897},{},[1898],{"type":71,"value":1899},"Fix within 1 week",{"type":65,"tag":1840,"props":1901,"children":1902},{},[1903,1908,1913],{"type":65,"tag":1867,"props":1904,"children":1905},{},[1906],{"type":71,"value":1907},"MEDIUM",{"type":65,"tag":1867,"props":1909,"children":1910},{},[1911],{"type":71,"value":1912},"Notable improvement opportunity",{"type":65,"tag":1867,"props":1914,"children":1915},{},[1916],{"type":71,"value":1917},"Plan within 30 days",{"type":65,"tag":1840,"props":1919,"children":1920},{},[1921,1926,1931],{"type":65,"tag":1867,"props":1922,"children":1923},{},[1924],{"type":71,"value":1925},"LOW",{"type":65,"tag":1867,"props":1927,"children":1928},{},[1929],{"type":71,"value":1930},"Minor optimization or hardening",{"type":65,"tag":1867,"props":1932,"children":1933},{},[1934],{"type":71,"value":1935},"Address when convenient",{"type":65,"tag":1840,"props":1937,"children":1938},{},[1939,1944,1949],{"type":65,"tag":1867,"props":1940,"children":1941},{},[1942],{"type":71,"value":1943},"INFO",{"type":65,"tag":1867,"props":1945,"children":1946},{},[1947],{"type":71,"value":1948},"Observation, no action required",{"type":65,"tag":1867,"props":1950,"children":1951},{},[1952],{"type":71,"value":1953},"N\u002FA",{"items":1955,"total":2056},[1956,1972,1987,2001,2017,2033,2040],{"slug":1957,"name":1957,"fn":1958,"description":1959,"org":1960,"tags":1961,"stars":24,"repoUrl":25,"updatedAt":1971},"aws-health-events","analyze AWS Health events for incidents","ALWAYS use this skill in the beginning of any incident investigation, root cause analysis, or operational troubleshooting. This skill retrieves and analyzes AWS Health events (service issues, scheduled changes, and account notifications) to identify AWS-side events that may explain or correlate with observed operational issues. Activate this skill when investigating an issue and you observe service degradation, elevated error rates, latency spikes, connection failures, throttling, capacity issues, deployment-related failures, alarms, or any operational event or issue. This skill searches AWS Health events by service, time window, region, and status to surface active or recent service disruptions, scheduled maintenance, and account-specific notifications that inform the current investigation. Also activate when a user requests a health event summary or report for their account over a specified time period.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1962,1963,1966,1968],{"name":23,"slug":8,"type":15},{"name":1964,"slug":1965,"type":15},"Debugging","debugging",{"name":1967,"slug":41,"type":15},"Incident Response",{"name":1969,"slug":1970,"type":15},"Monitoring","monitoring","2026-08-20T03:53:41.178955",{"slug":1973,"name":1973,"fn":1974,"description":1975,"org":1976,"tags":1977,"stars":24,"repoUrl":25,"updatedAt":1986},"aws-vpc-dns-investigation","investigate VPC DNS resolution issues","Use this skill when a name is not resolving as expected inside a VPC, or before applying a DNS control-plane change. Activate on symptoms such as NXDOMAIN or SERVFAIL from an EC2 instance, a hostname resolving to a public address when a private endpoint was expected, an AWS service endpoint that stopped resolving after a VPC endpoint or Route 53 change, an application reaching the wrong IP, resolution that works from one instance but not another, IPv6 or dualstack resolution differences, a suspected on-premises forwarding or hybrid DNS problem, or a request to check whether enabling private DNS, adding a Resolver rule, associating a private hosted zone, attaching DNS Firewall, or associating a Route 53 Profile would break anything. It drives the aws-vpc-dns-diagnostics MCP server to observe live resolution from inside the subnet and to simulate a proposed change before it is applied.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1978,1979,1980,1983],{"name":23,"slug":8,"type":15},{"name":1964,"slug":1965,"type":15},{"name":1981,"slug":1982,"type":15},"DNS","dns",{"name":1984,"slug":1985,"type":15},"Networking","networking","2026-08-20T03:53:46.027593",{"slug":1988,"name":1988,"fn":1989,"description":1990,"org":1991,"tags":1992,"stars":24,"repoUrl":25,"updatedAt":2000},"crm-production-investigation-guidelines","investigate CRM production incidents","Guidelines for investigating production incidents in the CRM application. Use when triaging any alert or incident involving the CRM REST API, SQS queues, Lambda functions, or Aurora DSQL database in this AWS account. Ensures thorough root cause analysis using AWS-native observability tools.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1993,1994,1997,1998,1999],{"name":23,"slug":8,"type":15},{"name":1995,"slug":1996,"type":15},"CRM","crm",{"name":1964,"slug":1965,"type":15},{"name":1967,"slug":41,"type":15},{"name":13,"slug":14,"type":15},"2026-08-20T03:53:23.532781",{"slug":2002,"name":2002,"fn":2003,"description":2004,"org":2005,"tags":2006,"stars":24,"repoUrl":25,"updatedAt":2016},"database-migration-service-expertise","troubleshoot AWS Database Migration Service","AWS Database Migration Service (DMS) operational review and troubleshooting skill. Conducts best practices validation, health assessments, performance diagnostics, cost optimization reviews, and migration cutover guidance. Triggers on requests like \"DMS review\", \"DMS health check\", \"DMS troubleshooting\", \"migration assessment\", \"DMS best practices audit\", \"DMS cost optimization\", \"replication instance review\", \"CDC latency issue\", or \"DMS task failure\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2007,2008,2011,2012,2015],{"name":23,"slug":8,"type":15},{"name":2009,"slug":2010,"type":15},"Database","database",{"name":1964,"slug":1965,"type":15},{"name":2013,"slug":2014,"type":15},"Migration","migration",{"name":13,"slug":14,"type":15},"2026-08-20T03:53:23.927999",{"slug":2018,"name":2018,"fn":2019,"description":2020,"org":2021,"tags":2022,"stars":24,"repoUrl":25,"updatedAt":2032},"database-rds-devops","diagnose Aurora MySQL and PostgreSQL databases","Database-level data-plane diagnostics for Aurora MySQL and Aurora PostgreSQL. Executes predefined read-only health check queries via RDS Data API to analyze buffer pool, connections, locks, replication, storage, performance, and index efficiency. Requires the rds-aidba MCP server for database-internal access beyond what CloudWatch and RDS APIs provide.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2023,2024,2025,2026,2029],{"name":23,"slug":8,"type":15},{"name":2009,"slug":2010,"type":15},{"name":1964,"slug":1965,"type":15},{"name":2027,"slug":2028,"type":15},"MySQL","mysql",{"name":2030,"slug":2031,"type":15},"PostgreSQL","postgresql","2026-08-20T03:53:41.560344",{"slug":4,"name":4,"fn":5,"description":6,"org":2034,"tags":2035,"stars":24,"repoUrl":25,"updatedAt":26},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2036,2037,2038,2039],{"name":17,"slug":18,"type":15},{"name":23,"slug":8,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},{"slug":2041,"name":2041,"fn":2042,"description":2043,"org":2044,"tags":2045,"stars":24,"repoUrl":25,"updatedAt":2055},"enrich-with-aws-security-agent","investigate security root causes in AWS","Automatically load this skill when investigating application outages, service degradation, or errors that could have security-related root causes — including unexplained downtime, authentication or authorization failures, injection attacks, data exposure, or suspicious application behavior. Query AWS Security Agent CloudWatch logs to retrieve detailed code review findings with actionable, low-level details (file, line number, vulnerability type) that customers can directly fix.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2046,2049,2050,2051,2052],{"name":2047,"slug":2048,"type":15},"Auth","auth",{"name":23,"slug":8,"type":15},{"name":1964,"slug":1965,"type":15},{"name":1967,"slug":41,"type":15},{"name":2053,"slug":2054,"type":15},"Security","security","2026-08-20T03:53:23.097965",15,{"items":2058,"total":2223},[2059,2077,2092,2105,2120,2130,2143,2159,2173,2186,2197,2209],{"slug":2060,"name":2060,"fn":2061,"description":2062,"org":2063,"tags":2064,"stars":2074,"repoUrl":2075,"updatedAt":2076},"agents-build","add capabilities to existing agent projects","Use to extend an existing agent project with memory, app integration, VPC, multi-agent, migration, model, browser, code interpreter, payments, or resource removal. Triggers: \"add memory\", \"remember across sessions\", \"call agent from app\", \"invoke agent from code\", \"agent auth\", \"streaming\", \"VPC\", \"VPC connectivity\", \"can't reach from VPC\", \"multi-agent\", \"A2A\", \"A2A auth\", \"orchestrator not delegating\", \"specialist not called\", \"migrate Bedrock Agent\", \"migration issue\", \"change model\", \"browser tool\", \"code interpreter\", \"delete agent\", \"tear down\", \"agentcore remove\", \"cross-account memory\", \"add payments capability to my agent\", \"wire payments plugin\", \"integrate x402 payments with the agent I'm building\", \"add MPP payments\", \"Machine Payments Protocol\". External APIs via Gateway: use agents-connect. New project: use agents-get-started. CLI\u002Fdev-server errors: use agents-debug. Runtime x402\u002FMPP payments: use agents-pay. Migration-specific Strands vs LangGraph routes here.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2065,2067,2070,2071],{"name":2066,"slug":32,"type":15},"Agents",{"name":2068,"slug":2069,"type":15},"Automation","automation",{"name":23,"slug":8,"type":15},{"name":2072,"slug":2073,"type":15},"Engineering","engineering",1822,"https:\u002F\u002Fgithub.com\u002Faws\u002Fagent-toolkit-for-aws","2026-08-20T03:27:06.137661",{"slug":2078,"name":2078,"fn":2079,"description":2080,"org":2081,"tags":2082,"stars":2074,"repoUrl":2075,"updatedAt":2091},"agents-connect","connect agents to external services","Use when connecting your agent to external APIs, tools, or services via Gateway, or restricting tool access with Cedar policies. Handles gateway setup, target types, outbound auth (OAuth, API key, IAM), credentials, and Cedar policy authoring. Triggers on: \"connect to API\", \"add gateway\", \"connect to MCP server\", \"Lambda tools\", \"OpenAPI\", \"gateway target\", \"Cedar policy\", \"restrict tools\", \"policy engine\", \"gateway auth error\", \"store API key\", \"outbound credential\", \"env var API key\", \"API key None after deploy\", \"credential not available after deploy\", \"should this be a gateway target\", \"give my agent tools\", \"add tools to agent\". Not for inbound auth (who can call your agent) — use agents-harden. Not for debugging agent behavior — use agents-debug. Not for VPC networking errors (agent can't reach APIs due to VPC) — use agents-build. Not for creating or hosting a new MCP server project — use agents-get-started.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2083,2084,2087,2090],{"name":2066,"slug":32,"type":15},{"name":2085,"slug":2086,"type":15},"API Development","api-development",{"name":2088,"slug":2089,"type":15},"Authentication","authentication",{"name":23,"slug":8,"type":15},"2026-07-16T06:00:38.866147",{"slug":2093,"name":2093,"fn":2094,"description":2095,"org":2096,"tags":2097,"stars":2074,"repoUrl":2075,"updatedAt":2104},"agents-debug","debug agent and environment issues","Use when your agent or environment is broken — wrong answers, errors, timeouts, tool failures, or CLI issues. Reads traces and logs to diagnose root causes. Also checks prerequisites when the CLI itself isn't working. Triggers on: \"agent not working\", \"wrong answer\", \"agent error\", \"tool call failing\", \"debug agent\", \"check logs\", \"read traces\", \"broken\", \"500 error\", \"424 error\", \"model access denied\", \"command not found\", \"stuck in DELETING\", \"maxVms exceeded\", \"cold start diagnosis\", \"cold start slow\", \"agentcore create error\", \"create failed\", \"exit code 7\", \"connection refused local dev\". Not for deploy failures — use agents-deploy. Not for performance tuning without errors — use agents-optimize. Not for VPC configuration — use agents-build. Not for observability setup or missing logs — use agents-optimize.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2098,2099,2100,2101],{"name":2066,"slug":32,"type":15},{"name":23,"slug":8,"type":15},{"name":1964,"slug":1965,"type":15},{"name":2102,"slug":2103,"type":15},"Observability","observability","2026-07-16T06:00:44.679093",{"slug":2106,"name":2106,"fn":2107,"description":2108,"org":2109,"tags":2110,"stars":2074,"repoUrl":2075,"updatedAt":2119},"agents-deploy","deploy AI agents to AWS","Use when deploying your agent to AWS, or when a deploy has failed. Handles pre-flight validation, CDK\u002FIAM\u002Fquota error diagnosis, version management, rollback, and canary deployments. Triggers on: \"deploy my agent\", \"agentcore deploy\", \"deploy failed\", \"CDK error\", \"rollback\", \"canary deploy\", \"pin version\", \"redeploy\", \"deploy stuck\". Not for production hardening — use agents-harden. Not for adding capabilities before deploy — use agents-build or agents-connect. Not for VPC configuration errors — use agents-build.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2111,2112,2113,2116],{"name":2066,"slug":32,"type":15},{"name":23,"slug":8,"type":15},{"name":2114,"slug":2115,"type":15},"CI\u002FCD","ci-cd",{"name":2117,"slug":2118,"type":15},"Deployment","deployment","2026-07-12T08:42:55.059577",{"slug":2121,"name":2121,"fn":2122,"description":2123,"org":2124,"tags":2125,"stars":2074,"repoUrl":2075,"updatedAt":2129},"agents-get-started","scaffold and deploy new agent projects","Use when a developer wants to create a new agent project or get started with AgentCore. Handles framework selection, project scaffolding, first deploy, and first invocation. Triggers on: \"build an agent\", \"create an agent\", \"get started\", \"new project\", \"agentcore create\", \"which framework\", \"Strands vs LangGraph\", \"hello world agent\", \"first agent\", \"create MCP server\", \"host MCP server\", \"agentcore dev\", \"dev server\", \"what port\", \"local development\". Not for adding capabilities to existing projects — use agents-build or agents-connect. Strands vs LangGraph in a migration context routes to agents-build, not here. Connecting to an existing MCP server routes to agents-connect, not here.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2126,2127,2128],{"name":2066,"slug":32,"type":15},{"name":23,"slug":8,"type":15},{"name":2117,"slug":2118,"type":15},"2026-07-12T08:42:51.963247",{"slug":2131,"name":2131,"fn":2132,"description":2133,"org":2134,"tags":2135,"stars":2074,"repoUrl":2075,"updatedAt":2142},"agents-harden","harden agents for production","Use when preparing your agent for production — IAM scoping, inbound auth (JWT, SigV4), secrets management, cold start optimization, session lifecycle, rate limiting, input validation, and quota guidance. Triggers on: \"production checklist\", \"harden agent\", \"production ready\", \"secure agent\", \"inbound auth\", \"going live\", \"cold start optimization\", \"session lifecycle\", \"StopRuntimeSession\", \"quota\", \"throttling\", \"maxVms\", \"rate limit\", \"security audit of outbound API calls\", \"gateway target audit for production\", \"restrict who can call\", \"lock down endpoint\", \"only our app can call\". Not for Cedar tool-restriction policies — use agents-connect. Not for quality measurement — use agents-optimize. Not for outbound credential storage or API key wiring — use agents-connect. Not for A2A agent-to-agent auth — use agents-build. Cold start observation and diagnosis (not optimization) routes to agents-debug.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2136,2137,2138,2141],{"name":2066,"slug":32,"type":15},{"name":23,"slug":8,"type":15},{"name":2139,"slug":2140,"type":15},"Best Practices","best-practices",{"name":2053,"slug":2054,"type":15},"2026-07-16T06:00:42.174705",{"slug":2144,"name":2144,"fn":2145,"description":2146,"org":2147,"tags":2148,"stars":2074,"repoUrl":2075,"updatedAt":2158},"agents-optimize","optimize agent quality and performance","Use when measuring or improving agent quality and performance — set up evaluators, online monitoring, CI\u002FCD quality gates, observability, or cost optimization. Triggers on: \"evaluate my agent\", \"add evaluator\", \"measure quality\", \"quality gate\", \"run evals\", \"agent too slow\", \"why is it slow\", \"reduce latency\", \"set up observability\", \"CloudWatch dashboard\", \"how much does my agent cost\", \"cost optimization\", \"logs not showing up\", \"logs missing\", \"spans not found\", \"eval failing\", \"eval error\", \"dev traces\", \"local traces\", \"agentcore dev traces\", \"traces to CloudWatch\". Not for debugging errors or crashes — use agents-debug. Slow but correct routes here; broken routes to debug.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2149,2150,2151,2154,2155],{"name":2066,"slug":32,"type":15},{"name":23,"slug":8,"type":15},{"name":2152,"slug":2153,"type":15},"Evals","evals",{"name":2102,"slug":2103,"type":15},{"name":2156,"slug":2157,"type":15},"Performance","performance","2026-07-12T08:42:56.488105",{"slug":2160,"name":2160,"fn":2161,"description":2162,"org":2163,"tags":2164,"stars":2074,"repoUrl":2075,"updatedAt":2172},"agents-pay","handle x402 payments for agent tasks","Use when THIS agent needs to pay for x402-protected content at runtime: hitting a paywall mid-task, settling it via AgentCore Payments, and applying operator-defined spend limits. Covers payment setup, policy, session budgets, and troubleshooting. Triggers on: \"my agent hit a 402 while calling an API\", \"a tool call returned 402 Payment Required\", \"my agent needs to pay for x402-protected content\", \"let the agent pay for content, capped at $5 per session\", \"set a spend limit for the agent\", \"ProcessPayment failed\", or \"why did my agent refuse to pay\". Not for BUILDING payment capability for end users, including wallets and framework middleware; use agents-build and references\u002Fpayments.md. For non-paid APIs via Gateway use agents-connect. For inbound auth use agents-harden. For project scaffolding use agents-get-started.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2165,2166,2167,2170],{"name":2066,"slug":32,"type":15},{"name":2068,"slug":2069,"type":15},{"name":2168,"slug":2169,"type":15},"Payments","payments",{"name":2171,"slug":2171,"type":15},"x402","2026-08-10T04:16:31.844309",{"slug":2174,"name":2174,"fn":2175,"description":2176,"org":2177,"tags":2178,"stars":2074,"repoUrl":2075,"updatedAt":2185},"amazon-aurora-mysql","manage Amazon Aurora MySQL clusters","Amazon Aurora MySQL — creates, modifies, and advises on Aurora MySQL clusters specifically (MySQL-compatible engine, Aurora serverless, parallel query). Trigger for Aurora MySQL cluster operations, ACU sizing, I\u002FO-Optimized storage, commitment pricing, or MySQL upgrade planning. Aurora MySQL uses full (VPC-based) configuration — express configuration is PostgreSQL-only. For Aurora PostgreSQL, use amazon-aurora-postgresql instead. Contains safety guardrails and response templates that override defaults.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2179,2180,2181,2182],{"name":23,"slug":8,"type":15},{"name":2009,"slug":2010,"type":15},{"name":2027,"slug":2028,"type":15},{"name":2183,"slug":2184,"type":15},"Serverless","serverless","2026-07-12T08:43:13.27939",{"slug":2187,"name":2187,"fn":2188,"description":2189,"org":2190,"tags":2191,"stars":2074,"repoUrl":2075,"updatedAt":2196},"amazon-aurora-postgresql","configure Amazon Aurora PostgreSQL clusters","Amazon Aurora PostgreSQL — creates, modifies, and advises on Aurora PostgreSQL clusters specifically (PostgreSQL-compatible engine, Aurora serverless, express configuration, pgvector, Babelfish). Trigger for Aurora PostgreSQL cluster operations, express-configuration quick-start, ACU sizing, I\u002FO-Optimized storage, commitment pricing, or PostgreSQL upgrade planning. For Aurora MySQL, use amazon-aurora-mysql instead. Contains safety guardrails, express-first routing, and response templates that override defaults.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2192,2193,2194,2195],{"name":23,"slug":8,"type":15},{"name":2009,"slug":2010,"type":15},{"name":2030,"slug":2031,"type":15},{"name":2183,"slug":2184,"type":15},"2026-07-16T06:00:34.789624",{"slug":2198,"name":2198,"fn":2199,"description":2200,"org":2201,"tags":2202,"stars":2074,"repoUrl":2075,"updatedAt":2208},"amazon-bedrock","build generative AI apps with Amazon Bedrock","Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore (including the Harness managed agent loop). Use when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, migrating\u002Fporting\u002Fconverting a Bedrock Agent (including inline agents) to an AgentCore Harness, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). ALSO USE for prompt caching, quota health checks and throttling diagnosis, cost attribution, migrating between Claude model generations, chunking strategies, API selection (Converse vs InvokeModel), and model selection. Also covers AgentCore Payments setup (x402, microtransactions, Payment Manager, Coinbase CDP, Stripe Privy, 402 Payment Required, paid endpoint). NOT for custom model training, Rekognition, or Comprehend.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2203,2204,2205],{"name":2066,"slug":32,"type":15},{"name":23,"slug":8,"type":15},{"name":2206,"slug":2207,"type":15},"LLM","llm","2026-08-07T04:38:13.03499",{"slug":2210,"name":2210,"fn":2211,"description":2212,"org":2213,"tags":2214,"stars":2074,"repoUrl":2075,"updatedAt":2222},"amazon-braket","run quantum computing workflows on AWS","Runs quantum computing workflows on AWS through Amazon Braket — discovering devices (QPUs and simulators) and their availability, building gate-model circuits and analog Hamiltonian programs, submitting quantum tasks, program sets and hybrid jobs, looking up prices, and capping spend with spending limits. Applies to any request about quantum computing, quantum hardware, quantum simulation, AHS, OpenQASM, or running a quantum algorithm on AWS.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2215,2216,2219],{"name":23,"slug":8,"type":15},{"name":2217,"slug":2218,"type":15},"Quantum Computing","quantum-computing",{"name":2220,"slug":2221,"type":15},"Simulation","simulation","2026-08-20T03:53:19.377174",139]