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Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs for service communication.","welflau\u002Fai-dev-system","welflau","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F7010385?v=4","01M6HPTDGF18RFY07M229P8CTM","01M6HPTDMRMZCJPYBFEA9XVVYT",3,"MIT","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fexternal_plugins\u002Fcloud-infrastructure\u002Fskills\u002Fservice-mesh-observability\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000013","分析与可视化","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"mesh","service","service mesh observability","observability","service mesh","when","for","implementing","latency","up","use","monitoring","tracing","metrics","distributed tracing","communication","issues","visualization","debugging","distributed","implement","2026-11-10 10:12:30",false,"---\nname: service-mesh-observability\ndescription: Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs for service communication.\n---\n\n# Service Mesh Observability\n\nComplete guide to observability patterns for Istio, Linkerd, and service mesh deployments.\n\n## When to Use This Skill\n\n- Setting up distributed tracing across services\n- Implementing service mesh metrics and dashboards\n- Debugging latency and error issues\n- Defining SLOs for service communication\n- Visualizing service dependencies\n- Troubleshooting mesh connectivity\n\n## Core Concepts\n\n### 1. Three Pillars of Observability\n\n```\n┌─────────────────────────────────────────────────────┐\n│                  Observability                       │\n├─────────────────┬─────────────────┬─────────────────┤\n│     Metrics     │     Traces      │      Logs       │\n│                 │                 │                 │\n│ • Request rate  │ • Span context  │ • Access logs   │\n│ • Error rate    │ • Latency       │ • Error details │\n│ • Latency P50   │ • Dependencies  │ • Debug info    │\n│ • Saturation    │ • Bottlenecks   │ • Audit trail   │\n└─────────────────┴─────────────────┴─────────────────┘\n```\n\n### 2. Golden Signals for Mesh\n\n| Signal | Description | Alert Threshold |\n|--------|-------------|-----------------|\n| **Latency** | Request duration P50, P99 | P99 > 500ms |\n| **Traffic** | Requests per second | Anomaly detection |\n| **Errors** | 5xx error rate | > 1% |\n| **Saturation** | Resource utilization | > 80% |\n\n## Templates\n\n### Template 1: Istio with Prometheus & Grafana\n\n```yaml\n# Install Prometheus\napiVersion: v1\nkind: ConfigMap\nmetadata:\n  name: prometheus\n  namespace: istio-system\ndata:\n  prometheus.yml: |\n    global:\n      scrape_interval: 15s\n    scrape_configs:\n      - job_name: 'istio-mesh'\n        kubernetes_sd_configs:\n          - role: endpoints\n            namespaces:\n              names:\n                - istio-system\n        relabel_configs:\n          - source_labels: [__meta_kubernetes_service_name]\n            action: keep\n            regex: istio-telemetry\n---\n# ServiceMonitor for Prometheus Operator\napiVersion: monitoring.coreos.com\u002Fv1\nkind: ServiceMonitor\nmetadata:\n  name: istio-mesh\n  namespace: istio-system\nspec:\n  selector:\n    matchLabels:\n      app: istiod\n  endpoints:\n    - port: http-monitoring\n      interval: 15s\n```\n\n### Template 2: Key Istio Metrics Queries\n\n```promql\n# Request rate by service\nsum(rate(istio_requests_total{reporter=\"destination\"}[5m])) by (destination_service_name)\n\n# Error rate (5xx)\nsum(rate(istio_requests_total{reporter=\"destination\", response_code=~\"5..\"}[5m]))\n  \u002F sum(rate(istio_requests_total{reporter=\"destination\"}[5m])) * 100\n\n# P99 latency\nhistogram_quantile(0.99,\n  sum(rate(istio_request_duration_milliseconds_bucket{reporter=\"destination\"}[5m]))\n  by (le, destination_service_name))\n\n# TCP connections\nsum(istio_tcp_connections_opened_total{reporter=\"destination\"}) by (destination_service_name)\n\n# Request size\nhistogram_quantile(0.99,\n  sum(rate(istio_request_bytes_bucket{reporter=\"destination\"}[5m]))\n  by (le, destination_service_name))\n```\n\n### Template 3: Jaeger Distributed Tracing\n\n```yaml\n# Jaeger installation for Istio\napiVersion: install.istio.io\u002Fv1alpha1\nkind: IstioOperator\nspec:\n  meshConfig:\n    enableTracing: true\n    defaultConfig:\n      tracing:\n        sampling: 100.0  # 100% in dev, lower in prod\n        zipkin:\n          address: jaeger-collector.istio-system:9411\n---\n# Jaeger deployment\napiVersion: apps\u002Fv1\nkind: Deployment\nmetadata:\n  name: jaeger\n  namespace: istio-system\nspec:\n  selector:\n    matchLabels:\n      app: jaeger\n  template:\n    metadata:\n      labels:\n        app: jaeger\n    spec:\n      containers:\n        - name: jaeger\n          image: jaegertracing\u002Fall-in-one:1.50\n          ports:\n            - containerPort: 5775   # UDP\n            - containerPort: 6831   # Thrift\n            - containerPort: 6832   # Thrift\n            - containerPort: 5778   # Config\n            - containerPort: 16686  # UI\n            - containerPort: 14268  # HTTP\n            - containerPort: 14250  # gRPC\n            - containerPort: 9411   # Zipkin\n          env:\n            - name: COLLECTOR_ZIPKIN_HOST_PORT\n              value: \":9411\"\n```\n\n### Template 4: Linkerd Viz Dashboard\n\n```bash\n# Install Linkerd viz extension\nlinkerd viz install | kubectl apply -f -\n\n# Access dashboard\nlinkerd viz dashboard\n\n# CLI commands for observability\n# Top requests\nlinkerd viz top deploy\u002Fmy-app\n\n# Per-route metrics\nlinkerd viz routes deploy\u002Fmy-app --to deploy\u002Fbackend\n\n# Live traffic inspection\nlinkerd viz tap deploy\u002Fmy-app --to deploy\u002Fbackend\n\n# Service edges (dependencies)\nlinkerd viz edges deployment -n my-namespace\n```\n\n### Template 5: Grafana Dashboard JSON\n\n```json\n{\n  \"dashboard\": {\n    \"title\": \"Service Mesh Overview\",\n    \"panels\": [\n      {\n        \"title\": \"Request Rate\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"sum(rate(istio_requests_total{reporter=\\\"destination\\\"}[5m])) by (destination_service_name)\",\n            \"legendFormat\": \"{{destination_service_name}}\"\n          }\n        ]\n      },\n      {\n        \"title\": \"Error Rate\",\n        \"type\": \"gauge\",\n        \"targets\": [\n          {\n            \"expr\": \"sum(rate(istio_requests_total{response_code=~\\\"5..\\\"}[5m])) \u002F sum(rate(istio_requests_total[5m])) * 100\"\n          }\n        ],\n        \"fieldConfig\": {\n          \"defaults\": {\n            \"thresholds\": {\n              \"steps\": [\n                {\"value\": 0, \"color\": \"green\"},\n                {\"value\": 1, \"color\": \"yellow\"},\n                {\"value\": 5, \"color\": \"red\"}\n              ]\n            }\n          }\n        }\n      },\n      {\n        \"title\": \"P99 Latency\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"histogram_quantile(0.99, sum(rate(istio_request_duration_milliseconds_bucket{reporter=\\\"destination\\\"}[5m])) by (le, destination_service_name))\",\n            \"legendFormat\": \"{{destination_service_name}}\"\n          }\n        ]\n      },\n      {\n        \"title\": \"Service Topology\",\n        \"type\": \"nodeGraph\",\n        \"targets\": [\n          {\n            \"expr\": \"sum(rate(istio_requests_total{reporter=\\\"destination\\\"}[5m])) by (source_workload, destination_service_name)\"\n          }\n        ]\n      }\n    ]\n  }\n}\n```\n\n### Template 6: Kiali Service Mesh Visualization\n\n```yaml\n# Kiali installation\napiVersion: kiali.io\u002Fv1alpha1\nkind: Kiali\nmetadata:\n  name: kiali\n  namespace: istio-system\nspec:\n  auth:\n    strategy: anonymous  # or openid, token\n  deployment:\n    accessible_namespaces:\n      - \"**\"\n  external_services:\n    prometheus:\n      url: http:\u002F\u002Fprometheus.istio-system:9090\n    tracing:\n      url: http:\u002F\u002Fjaeger-query.istio-system:16686\n    grafana:\n      url: http:\u002F\u002Fgrafana.istio-system:3000\n```\n\n### Template 7: OpenTelemetry Integration\n\n```yaml\n# OpenTelemetry Collector for mesh\napiVersion: v1\nkind: ConfigMap\nmetadata:\n  name: otel-collector-config\ndata:\n  config.yaml: |\n    receivers:\n      otlp:\n        protocols:\n          grpc:\n            endpoint: 0.0.0.0:4317\n          http:\n            endpoint: 0.0.0.0:4318\n      zipkin:\n        endpoint: 0.0.0.0:9411\n\n    processors:\n      batch:\n        timeout: 10s\n\n    exporters:\n      jaeger:\n        endpoint: jaeger-collector:14250\n        tls:\n          insecure: true\n      prometheus:\n        endpoint: 0.0.0.0:8889\n\n    service:\n      pipelines:\n        traces:\n          receivers: [otlp, zipkin]\n          processors: [batch]\n          exporters: [jaeger]\n        metrics:\n          receivers: [otlp]\n          processors: [batch]\n          exporters: [prometheus]\n---\n# Istio Telemetry v2 with OTel\napiVersion: telemetry.istio.io\u002Fv1alpha1\nkind: Telemetry\nmetadata:\n  name: mesh-default\n  namespace: istio-system\nspec:\n  tracing:\n    - providers:\n        - name: otel\n      randomSamplingPercentage: 10\n```\n\n## Alerting Rules\n\n```yaml\napiVersion: monitoring.coreos.com\u002Fv1\nkind: PrometheusRule\nmetadata:\n  name: mesh-alerts\n  namespace: istio-system\nspec:\n  groups:\n    - name: mesh.rules\n      rules:\n        - alert: HighErrorRate\n          expr: |\n            sum(rate(istio_requests_total{response_code=~\"5..\"}[5m])) by (destination_service_name)\n            \u002F sum(rate(istio_requests_total[5m])) by (destination_service_name) > 0.05\n          for: 5m\n          labels:\n            severity: critical\n          annotations:\n            summary: \"High error rate for {{ $labels.destination_service_name }}\"\n\n        - alert: HighLatency\n          expr: |\n            histogram_quantile(0.99, sum(rate(istio_request_duration_milliseconds_bucket[5m]))\n            by (le, destination_service_name)) > 1000\n          for: 5m\n          labels:\n            severity: warning\n          annotations:\n            summary: \"High P99 latency for {{ $labels.destination_service_name }}\"\n\n        - alert: MeshCertExpiring\n          expr: |\n            (certmanager_certificate_expiration_timestamp_seconds - time()) \u002F 86400 \u003C 7\n          labels:\n            severity: warning\n          annotations:\n            summary: \"Mesh certificate expiring in less than 7 days\"\n```\n\n## Best Practices\n\n### Do's\n- **Sample appropriately** - 100% in dev, 1-10% in prod\n- **Use trace context** - Propagate headers consistently\n- **Set up alerts** - For golden signals\n- **Correlate metrics\u002Ftraces** - Use exemplars\n- **Retain strategically** - Hot\u002Fcold storage tiers\n\n### Don'ts\n- **Don't over-sample** - Storage costs add up\n- **Don't ignore cardinality** - Limit label values\n- **Don't skip dashboards** - Visualize dependencies\n- **Don't forget costs** - Monitor observability costs\n\n## Resources\n\n- [Istio Observability](https:\u002F\u002Fistio.io\u002Flatest\u002Fdocs\u002Ftasks\u002Fobservability\u002F)\n- [Linkerd Observability](https:\u002F\u002Flinkerd.io\u002F2.14\u002Ffeatures\u002Fdashboard\u002F)\n- [OpenTelemetry](https:\u002F\u002Fopentelemetry.io\u002F)\n- [Kiali](https:\u002F\u002Fkiali.io\u002F)\n","# Service Mesh Observability\n\nComplete guide to observability patterns for Istio, Linkerd, and service mesh deployments.\n\n## When to Use This Skill\n\n- Setting up distributed tracing across services\n- Implementing service mesh metrics and dashboards\n- Debugging latency and error issues\n- Defining SLOs for service communication\n- Visualizing service dependencies\n- Troubleshooting mesh connectivity\n\n## Core Concepts\n\n### 1. Three Pillars of Observability\n\n```\n┌─────────────────────────────────────────────────────┐\n│                  Observability                       │\n├─────────────────┬─────────────────┬─────────────────┤\n│     Metrics     │     Traces      │      Logs       │\n│                 │                 │                 │\n│ • Request rate  │ • Span context  │ • Access logs   │\n│ • Error rate    │ • Latency       │ • Error details │\n│ • Latency P50   │ • Dependencies  │ • Debug info    │\n│ • Saturation    │ • Bottlenecks   │ • Audit trail   │\n└─────────────────┴─────────────────┴─────────────────┘\n```\n\n### 2. Golden Signals for Mesh\n\n| Signal | Description | Alert Threshold |\n|--------|-------------|-----------------|\n| **Latency** | Request duration P50, P99 | P99 > 500ms |\n| **Traffic** | Requests per second | Anomaly detection |\n| **Errors** | 5xx error rate | > 1% |\n| **Saturation** | Resource utilization | > 80% |\n\n## Templates\n\n### Template 1: Istio with Prometheus & Grafana\n\n```yaml\n# Install Prometheus\napiVersion: v1\nkind: ConfigMap\nmetadata:\n  name: prometheus\n  namespace: istio-system\ndata:\n  prometheus.yml: |\n    global:\n      scrape_interval: 15s\n    scrape_configs:\n      - job_name: 'istio-mesh'\n        kubernetes_sd_configs:\n          - role: endpoints\n            namespaces:\n              names:\n                - istio-system\n        relabel_configs:\n          - source_labels: [__meta_kubernetes_service_name]\n            action: keep\n            regex: istio-telemetry\n---\n# ServiceMonitor for Prometheus Operator\napiVersion: monitoring.coreos.com\u002Fv1\nkind: ServiceMonitor\nmetadata:\n  name: istio-mesh\n  namespace: istio-system\nspec:\n  selector:\n    matchLabels:\n      app: istiod\n  endpoints:\n    - port: http-monitoring\n      interval: 15s\n```\n\n### Template 2: Key Istio Metrics Queries\n\n```promql\n# Request rate by service\nsum(rate(istio_requests_total{reporter=\"destination\"}[5m])) by (destination_service_name)\n\n# Error rate (5xx)\nsum(rate(istio_requests_total{reporter=\"destination\", response_code=~\"5..\"}[5m]))\n  \u002F sum(rate(istio_requests_total{reporter=\"destination\"}[5m])) * 100\n\n# P99 latency\nhistogram_quantile(0.99,\n  sum(rate(istio_request_duration_milliseconds_bucket{reporter=\"destination\"}[5m]))\n  by (le, destination_service_name))\n\n# TCP connections\nsum(istio_tcp_connections_opened_total{reporter=\"destination\"}) by (destination_service_name)\n\n# Request size\nhistogram_quantile(0.99,\n  sum(rate(istio_request_bytes_bucket{reporter=\"destination\"}[5m]))\n  by (le, destination_service_name))\n```\n\n### Template 3: Jaeger Distributed Tracing\n\n```yaml\n# Jaeger installation for Istio\napiVersion: install.istio.io\u002Fv1alpha1\nkind: IstioOperator\nspec:\n  meshConfig:\n    enableTracing: true\n    defaultConfig:\n      tracing:\n        sampling: 100.0  # 100% in dev, lower in prod\n        zipkin:\n          address: jaeger-collector.istio-system:9411\n---\n# Jaeger deployment\napiVersion: apps\u002Fv1\nkind: Deployment\nmetadata:\n  name: jaeger\n  namespace: istio-system\nspec:\n  selector:\n    matchLabels:\n      app: jaeger\n  template:\n    metadata:\n      labels:\n        app: jaeger\n    spec:\n      containers:\n        - name: jaeger\n          image: jaegertracing\u002Fall-in-one:1.50\n          ports:\n            - containerPort: 5775   # UDP\n            - containerPort: 6831   # Thrift\n            - containerPort: 6832   # Thrift\n            - containerPort: 5778   # Config\n            - containerPort: 16686  # UI\n            - containerPort: 14268  # HTTP\n            - containerPort: 14250  # gRPC\n            - containerPort: 9411   # Zipkin\n          env:\n            - name: COLLECTOR_ZIPKIN_HOST_PORT\n              value: \":9411\"\n```\n\n### Template 4: Linkerd Viz Dashboard\n\n```bash\n# Install Linkerd viz extension\nlinkerd viz install | kubectl apply -f -\n\n# Access dashboard\nlinkerd viz dashboard\n\n# CLI commands for observability\n# Top requests\nlinkerd viz top deploy\u002Fmy-app\n\n# Per-route metrics\nlinkerd viz routes deploy\u002Fmy-app --to deploy\u002Fbackend\n\n# Live traffic inspection\nlinkerd viz tap deploy\u002Fmy-app --to deploy\u002Fbackend\n\n# Service edges (dependencies)\nlinkerd viz edges deployment -n my-namespace\n```\n\n### Template 5: Grafana Dashboard JSON\n\n```json\n{\n  \"dashboard\": {\n    \"title\": \"Service Mesh Overview\",\n    \"panels\": [\n      {\n        \"title\": \"Request Rate\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"sum(rate(istio_requests_total{reporter=\\\"destination\\\"}[5m])) by (destination_service_name)\",\n            \"legendFormat\": \"{{destination_service_name}}\"\n          }\n        ]\n      },\n      {\n        \"title\": \"Error Rate\",\n        \"type\": \"gauge\",\n        \"targets\": [\n          {\n            \"expr\": \"sum(rate(istio_requests_total{response_code=~\\\"5..\\\"}[5m])) \u002F sum(rate(istio_requests_total[5m])) * 100\"\n          }\n        ],\n        \"fieldConfig\": {\n          \"defaults\": {\n            \"thresholds\": {\n              \"steps\": [\n                {\"value\": 0, \"color\": \"green\"},\n                {\"value\": 1, \"color\": \"yellow\"},\n                {\"value\": 5, \"color\": \"red\"}\n              ]\n            }\n          }\n        }\n      },\n      {\n        \"title\": \"P99 Latency\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"histogram_quantile(0.99, sum(rate(istio_request_duration_milliseconds_bucket{reporter=\\\"destination\\\"}[5m])) by (le, destination_service_name))\",\n            \"legendFormat\": \"{{destination_service_name}}\"\n          }\n        ]\n      },\n      {\n        \"title\": \"Service Topology\",\n        \"type\": \"nodeGraph\",\n        \"targets\": [\n          {\n            \"expr\": \"sum(rate(istio_requests_total{reporter=\\\"destination\\\"}[5m])) by (source_workload, destination_service_name)\"\n          }\n        ]\n      }\n    ]\n  }\n}\n```\n\n### Template 6: Kiali Service Mesh Visualization\n\n```yaml\n# Kiali installation\napiVersion: kiali.io\u002Fv1alpha1\nkind: Kiali\nmetadata:\n  name: kiali\n  namespace: istio-system\nspec:\n  auth:\n    strategy: anonymous  # or openid, token\n  deployment:\n    accessible_namespaces:\n      - \"**\"\n  external_services:\n    prometheus:\n      url: http:\u002F\u002Fprometheus.istio-system:9090\n    tracing:\n      url: http:\u002F\u002Fjaeger-query.istio-system:16686\n    grafana:\n      url: http:\u002F\u002Fgrafana.istio-system:3000\n```\n\n### Template 7: OpenTelemetry Integration\n\n```yaml\n# OpenTelemetry Collector for mesh\napiVersion: v1\nkind: ConfigMap\nmetadata:\n  name: otel-collector-config\ndata:\n  config.yaml: |\n    receivers:\n      otlp:\n        protocols:\n          grpc:\n            endpoint: 0.0.0.0:4317\n          http:\n            endpoint: 0.0.0.0:4318\n      zipkin:\n        endpoint: 0.0.0.0:9411\n\n    processors:\n      batch:\n        timeout: 10s\n\n    exporters:\n      jaeger:\n        endpoint: jaeger-collector:14250\n        tls:\n          insecure: true\n      prometheus:\n        endpoint: 0.0.0.0:8889\n\n    service:\n      pipelines:\n        traces:\n          receivers: [otlp, zipkin]\n          processors: [batch]\n          exporters: [jaeger]\n        metrics:\n          receivers: [otlp]\n          processors: [batch]\n          exporters: [prometheus]\n---\n# Istio Telemetry v2 with OTel\napiVersion: telemetry.istio.io\u002Fv1alpha1\nkind: Telemetry\nmetadata:\n  name: mesh-default\n  namespace: istio-system\nspec:\n  tracing:\n    - providers:\n        - name: otel\n      randomSamplingPercentage: 10\n```\n\n## Alerting Rules\n\n```yaml\napiVersion: monitoring.coreos.com\u002Fv1\nkind: PrometheusRule\nmetadata:\n  name: mesh-alerts\n  namespace: istio-system\nspec:\n  groups:\n    - name: mesh.rules\n      rules:\n        - alert: HighErrorRate\n          expr: |\n            sum(rate(istio_requests_total{response_code=~\"5..\"}[5m])) by (destination_service_name)\n            \u002F sum(rate(istio_requests_total[5m])) by (destination_service_name) > 0.05\n          for: 5m\n          labels:\n            severity: critical\n          annotations:\n            summary: \"High error rate for {{ $labels.destination_service_name }}\"\n\n        - alert: HighLatency\n          expr: |\n            histogram_quantile(0.99, sum(rate(istio_request_duration_milliseconds_bucket[5m]))\n            by (le, destination_service_name)) > 1000\n          for: 5m\n          labels:\n            severity: warning\n          annotations:\n            summary: \"High P99 latency for {{ $labels.destination_service_name }}\"\n\n        - alert: MeshCertExpiring\n          expr: |\n            (certmanager_certificate_expiration_timestamp_seconds - time()) \u002F 86400 \u003C 7\n          labels:\n            severity: warning\n          annotations:\n            summary: \"Mesh certificate expiring in less than 7 days\"\n```\n\n## Best Practices\n\n### Do's\n- **Sample appropriately** - 100% in dev, 1-10% in prod\n- **Use trace context** - Propagate headers consistently\n- **Set up alerts** - For golden signals\n- **Correlate metrics\u002Ftraces** - Use exemplars\n- **Retain strategically** - Hot\u002Fcold storage tiers\n\n### Don'ts\n- **Don't over-sample** - Storage costs add up\n- **Don't ignore cardinality** - Limit label values\n- **Don't skip dashboards** - Visualize dependencies\n- **Don't forget costs** - Monitor observability costs\n\n## Resources\n\n- [Istio Observability](https:\u002F\u002Fistio.io\u002Flatest\u002Fdocs\u002Ftasks\u002Fobservability\u002F)\n- [Linkerd Observability](https:\u002F\u002Flinkerd.io\u002F2.14\u002Ffeatures\u002Fdashboard\u002F)\n- [OpenTelemetry](https:\u002F\u002Fopentelemetry.io\u002F)\n- [Kiali](https:\u002F\u002Fkiali.io\u002F)\n",{"name":5,"description":7},"main","18d0e63d1313ca87098f614aa7c1e2dcf6de79c7","backend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fexternal_plugins\u002Fcloud-infrastructure\u002Fskills\u002Fservice-mesh-observability",1,"https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system","https:\u002F\u002Fgithub.com\u002Fwelflau","2026-11-10 11:14:25",{"source":8,"skillName":5,"commands":57,"prompt":67,"zipAvailable":68},[58,61,64],{"tool":59,"command":60},"npx","npx skills add welflau\u002Fai-dev-system --skill service-mesh-observability",{"tool":62,"command":63},"bunx","bunx skills add welflau\u002Fai-dev-system --skill service-mesh-observability",{"tool":65,"command":66},"pnpm","pnpm dlx skills add welflau\u002Fai-dev-system --skill service-mesh-observability","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fexternal_plugins\u002Fcloud-infrastructure\u002Fskills\u002Fservice-mesh-observability\u002FSKILL.md",true,[],[71,102,133,158,184,208],{"skillNo":72,"name":73,"nameZh":6,"description":74,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":75,"licenseFileUrl":76,"sourceHtmlUrl":77,"categories":78,"keywords":82,"publishedAt":44},"01M6HSTDP4M3JFXEBK91VFB4PA","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fplugins\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fplugins\u002Fweb-artifacts-builder\u002FSKILL.md",[79],{"categoryNo":80,"categoryName":81,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000009","前端开发",[83,84,85,86,87,88,89,90,91,92,93,94,95,96,33,97,98,99,100,29,101],"web artifacts builder","web","artifacts","artifacts builder","builder","frontend","css","components","react","routing","state management","state","file","Tailwind","single-file","simple","ui components","multi","single",{"skillNo":103,"name":104,"nameZh":6,"description":105,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":75,"licenseFileUrl":106,"sourceHtmlUrl":107,"categories":108,"keywords":118,"publishedAt":44},"01M6HSDXH0JSP8R3QTNY9XZ8HN","frontend-design","Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML\u002FCSS layouts, or when styling\u002Fbeautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fplugins\u002Ffrontend-design\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fplugins\u002Ffrontend-design\u002FSKILL.md",[109,110,113],{"categoryNo":80,"categoryName":81,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":111,"categoryName":112,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":114,"categoryName":115,"taxonomyType":116,"taxonomyTypeDesc":117},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[88,119,120,89,84,90,91,121,122,123,85,124,125,126,33,127,128,129,130,131,132,28],"design","frontend design","react components","create","code","examples","applications","landing","ui design","pages","aesthetics","web ui","with","generic",{"skillNo":134,"name":135,"nameZh":6,"description":136,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":75,"licenseFileUrl":137,"sourceHtmlUrl":138,"categories":139,"keywords":141,"publishedAt":44},"01M6HSA77QYVP7A72HREGTDN2C","algorithmic-art","Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fplugins\u002Falgorithmic-art\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fplugins\u002Falgorithmic-art\u002FSKILL.md",[140],{"categoryNo":111,"categoryName":112,"taxonomyType":20,"taxonomyTypeDesc":21},[142,143,144,122,123,145,146,147,148,33,149,150,151,152,131,153,154,155,156,157,28],"algorithmic art","Art","algorithmic","flow","js","work","interactive","generative art","exploration","systems","users","Existing","request","generative","copyright","fields",{"skillNo":159,"name":160,"nameZh":6,"description":161,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":75,"licenseFileUrl":162,"sourceHtmlUrl":163,"categories":164,"keywords":166,"publishedAt":44},"01M6HS9HE0X390Y6RQKTY1YNGJ","theme-factory","Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors\u002Ffonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fexternal_plugins\u002Ftheme-factory\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fexternal_plugins\u002Ftheme-factory\u002FSKILL.md",[165],{"categoryNo":111,"categoryName":112,"taxonomyType":20,"taxonomyTypeDesc":21},[167,168,169,170,171,172,85,173,174,175,126,176,177,128,178,131,179,180,181,29,182,183],"theme factory","factory","theme","docs","toolkit","generate","SET","fly","slides","styling","artifact","themes","you","fonts","can","apply","new",{"skillNo":185,"name":186,"nameZh":6,"description":187,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":188,"categories":189,"keywords":193,"publishedAt":44},"01M6HS74GASM6FJ77F83EY679E","browsing","Use when you need direct browser control - teaches Chrome DevTools Protocol for controlling existing browser sessions, multi-tab management, form automation, and content extraction via use_browser MCP tool","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fexternal_plugins\u002Fsuperpowers-chrome\u002Fskills\u002Fbrowsing\u002FSKILL.md",[190],{"categoryNo":191,"categoryName":192,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[186,194,195,196,197,198,199,200,201,202,203,33,204,205,206,207,100,179,29,153],"MCP","automation","chrome","sessions","protocol","browser","devtools","chrome devtools","tool","direct","browser control","control","via","form",{"skillNo":209,"name":210,"nameZh":6,"description":211,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":75,"licenseFileUrl":212,"sourceHtmlUrl":213,"categories":214,"keywords":221,"publishedAt":44},"01M6HS6BZT2CKDNQ6YF20DXN4T","slack-gif-creator","Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like \"make me a GIF of X doing Y for Slack.\"","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fexternal_plugins\u002Fslack-gif-creator\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fwelflau\u002Fai-dev-system\u002Fblob\u002Fmain\u002Fbackend\u002Fskills\u002Fmarketplace\u002Fcodebuddy-plugins-official\u002Fexternal_plugins\u002Fslack-gif-creator\u002FSKILL.md",[215,218],{"categoryNo":216,"categoryName":217,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000005","邮件与沟通",{"categoryNo":219,"categoryName":220,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",[222,223,224,225,226,227,228,229,230,33,231,152,232,233,234,29,154,28],"slack gif creator","slack","gif","creator","validation","Tools","constraints","Animation","knowledge","me","make","Utilities","concepts"]