[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71SF62G3C6HCRE4CP75QDY7":3,"skill-same:01M71SF62G3C6HCRE4CP75QDY7":68},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":13,"repositoryHtmlUrl":51,"repositoryHomepageUrl":6,"ownerHtmlUrl":52,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":53,"install":54,"resources":67},"01M71SF62G3C6HCRE4CP75QDY7","grafana-dashboards",null,"Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational ...","javiertarazon\u002Fide-agente-free-jt7-","javiertarazon","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F153141207?v=4","01M71R52TB3S9HXKH6WSNT8A7V","01M71R52VG5KS2DKDDH4GDQ30A",0,"MIT","https:\u002F\u002Fgithub.com\u002Fjaviertarazon\u002Fide-agente-free-jt7-\u002Fblob\u002Frelease\u002Fv4.2.11-panel-pro\u002F.github\u002Fskills\u002Fgrafana-dashboards\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],"grafana","dashboards","grafana dashboards","application","Production","operational","use","system","manage","real-time","for","metrics","create","Real-Time Visualization","monitoring","unknown","when","time","visualization","community","2026-11-10 13:02:02",false,"---\nname: grafana-dashboards\ndescription: \"Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational ...\"\nrisk: unknown\nsource: community\n---\n\n# Grafana Dashboards\n\nCreate and manage production-ready Grafana dashboards for comprehensive system observability.\n\n## Do not use this skill when\n\n- The task is unrelated to grafana dashboards\n- You need a different domain or tool outside this scope\n\n## Instructions\n\n- Clarify goals, constraints, and required inputs.\n- Apply relevant best practices and validate outcomes.\n- Provide actionable steps and verification.\n- If detailed examples are required, open `resources\u002Fimplementation-playbook.md`.\n\n## Purpose\n\nDesign effective Grafana dashboards for monitoring applications, infrastructure, and business metrics.\n\n## Use this skill when\n\n- Visualize Prometheus metrics\n- Create custom dashboards\n- Implement SLO dashboards\n- Monitor infrastructure\n- Track business KPIs\n\n## Dashboard Design Principles\n\n### 1. Hierarchy of Information\n```\n┌─────────────────────────────────────┐\n│  Critical Metrics (Big Numbers)     │\n├─────────────────────────────────────┤\n│  Key Trends (Time Series)           │\n├─────────────────────────────────────┤\n│  Detailed Metrics (Tables\u002FHeatmaps) │\n└─────────────────────────────────────┘\n```\n\n### 2. RED Method (Services)\n- **Rate** - Requests per second\n- **Errors** - Error rate\n- **Duration** - Latency\u002Fresponse time\n\n### 3. USE Method (Resources)\n- **Utilization** - % time resource is busy\n- **Saturation** - Queue length\u002Fwait time\n- **Errors** - Error count\n\n## Dashboard Structure\n\n### API Monitoring Dashboard\n\n```json\n{\n  \"dashboard\": {\n    \"title\": \"API Monitoring\",\n    \"tags\": [\"api\", \"production\"],\n    \"timezone\": \"browser\",\n    \"refresh\": \"30s\",\n    \"panels\": [\n      {\n        \"title\": \"Request Rate\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"sum(rate(http_requests_total[5m])) by (service)\",\n            \"legendFormat\": \"{{service}}\"\n          }\n        ],\n        \"gridPos\": {\"x\": 0, \"y\": 0, \"w\": 12, \"h\": 8}\n      },\n      {\n        \"title\": \"Error Rate %\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"(sum(rate(http_requests_total{status=~\\\"5..\\\"}[5m])) \u002F sum(rate(http_requests_total[5m]))) * 100\",\n            \"legendFormat\": \"Error Rate\"\n          }\n        ],\n        \"alert\": {\n          \"conditions\": [\n            {\n              \"evaluator\": {\"params\": [5], \"type\": \"gt\"},\n              \"operator\": {\"type\": \"and\"},\n              \"query\": {\"params\": [\"A\", \"5m\", \"now\"]},\n              \"type\": \"query\"\n            }\n          ]\n        },\n        \"gridPos\": {\"x\": 12, \"y\": 0, \"w\": 12, \"h\": 8}\n      },\n      {\n        \"title\": \"P95 Latency\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"histogram_quantile(0.95, sum(rate(http_request_duration_seconds_bucket[5m])) by (le, service))\",\n            \"legendFormat\": \"{{service}}\"\n          }\n        ],\n        \"gridPos\": {\"x\": 0, \"y\": 8, \"w\": 24, \"h\": 8}\n      }\n    ]\n  }\n}\n```\n\n**Reference:** See `assets\u002Fapi-dashboard.json`\n\n## Panel Types\n\n### 1. Stat Panel (Single Value)\n```json\n{\n  \"type\": \"stat\",\n  \"title\": \"Total Requests\",\n  \"targets\": [{\n    \"expr\": \"sum(http_requests_total)\"\n  }],\n  \"options\": {\n    \"reduceOptions\": {\n      \"values\": false,\n      \"calcs\": [\"lastNotNull\"]\n    },\n    \"orientation\": \"auto\",\n    \"textMode\": \"auto\",\n    \"colorMode\": \"value\"\n  },\n  \"fieldConfig\": {\n    \"defaults\": {\n      \"thresholds\": {\n        \"mode\": \"absolute\",\n        \"steps\": [\n          {\"value\": 0, \"color\": \"green\"},\n          {\"value\": 80, \"color\": \"yellow\"},\n          {\"value\": 90, \"color\": \"red\"}\n        ]\n      }\n    }\n  }\n}\n```\n\n### 2. Time Series Graph\n```json\n{\n  \"type\": \"graph\",\n  \"title\": \"CPU Usage\",\n  \"targets\": [{\n    \"expr\": \"100 - (avg by (instance) (rate(node_cpu_seconds_total{mode=\\\"idle\\\"}[5m])) * 100)\"\n  }],\n  \"yaxes\": [\n    {\"format\": \"percent\", \"max\": 100, \"min\": 0},\n    {\"format\": \"short\"}\n  ]\n}\n```\n\n### 3. Table Panel\n```json\n{\n  \"type\": \"table\",\n  \"title\": \"Service Status\",\n  \"targets\": [{\n    \"expr\": \"up\",\n    \"format\": \"table\",\n    \"instant\": true\n  }],\n  \"transformations\": [\n    {\n      \"id\": \"organize\",\n      \"options\": {\n        \"excludeByName\": {\"Time\": true},\n        \"indexByName\": {},\n        \"renameByName\": {\n          \"instance\": \"Instance\",\n          \"job\": \"Service\",\n          \"Value\": \"Status\"\n        }\n      }\n    }\n  ]\n}\n```\n\n### 4. Heatmap\n```json\n{\n  \"type\": \"heatmap\",\n  \"title\": \"Latency Heatmap\",\n  \"targets\": [{\n    \"expr\": \"sum(rate(http_request_duration_seconds_bucket[5m])) by (le)\",\n    \"format\": \"heatmap\"\n  }],\n  \"dataFormat\": \"tsbuckets\",\n  \"yAxis\": {\n    \"format\": \"s\"\n  }\n}\n```\n\n## Variables\n\n### Query Variables\n```json\n{\n  \"templating\": {\n    \"list\": [\n      {\n        \"name\": \"namespace\",\n        \"type\": \"query\",\n        \"datasource\": \"Prometheus\",\n        \"query\": \"label_values(kube_pod_info, namespace)\",\n        \"refresh\": 1,\n        \"multi\": false\n      },\n      {\n        \"name\": \"service\",\n        \"type\": \"query\",\n        \"datasource\": \"Prometheus\",\n        \"query\": \"label_values(kube_service_info{namespace=\\\"$namespace\\\"}, service)\",\n        \"refresh\": 1,\n        \"multi\": true\n      }\n    ]\n  }\n}\n```\n\n### Use Variables in Queries\n```\nsum(rate(http_requests_total{namespace=\"$namespace\", service=~\"$service\"}[5m]))\n```\n\n## Alerts in Dashboards\n\n```json\n{\n  \"alert\": {\n    \"name\": \"High Error Rate\",\n    \"conditions\": [\n      {\n        \"evaluator\": {\n          \"params\": [5],\n          \"type\": \"gt\"\n        },\n        \"operator\": {\"type\": \"and\"},\n        \"query\": {\n          \"params\": [\"A\", \"5m\", \"now\"]\n        },\n        \"reducer\": {\"type\": \"avg\"},\n        \"type\": \"query\"\n      }\n    ],\n    \"executionErrorState\": \"alerting\",\n    \"for\": \"5m\",\n    \"frequency\": \"1m\",\n    \"message\": \"Error rate is above 5%\",\n    \"noDataState\": \"no_data\",\n    \"notifications\": [\n      {\"uid\": \"slack-channel\"}\n    ]\n  }\n}\n```\n\n## Dashboard Provisioning\n\n**dashboards.yml:**\n```yaml\napiVersion: 1\n\nproviders:\n  - name: 'default'\n    orgId: 1\n    folder: 'General'\n    type: file\n    disableDeletion: false\n    updateIntervalSeconds: 10\n    allowUiUpdates: true\n    options:\n      path: \u002Fetc\u002Fgrafana\u002Fdashboards\n```\n\n## Common Dashboard Patterns\n\n### Infrastructure Dashboard\n\n**Key Panels:**\n- CPU utilization per node\n- Memory usage per node\n- Disk I\u002FO\n- Network traffic\n- Pod count by namespace\n- Node status\n\n**Reference:** See `assets\u002Finfrastructure-dashboard.json`\n\n### Database Dashboard\n\n**Key Panels:**\n- Queries per second\n- Connection pool usage\n- Query latency (P50, P95, P99)\n- Active connections\n- Database size\n- Replication lag\n- Slow queries\n\n**Reference:** See `assets\u002Fdatabase-dashboard.json`\n\n### Application Dashboard\n\n**Key Panels:**\n- Request rate\n- Error rate\n- Response time (percentiles)\n- Active users\u002Fsessions\n- Cache hit rate\n- Queue length\n\n## Best Practices\n\n1. **Start with templates** (Grafana community dashboards)\n2. **Use consistent naming** for panels and variables\n3. **Group related metrics** in rows\n4. **Set appropriate time ranges** (default: Last 6 hours)\n5. **Use variables** for flexibility\n6. **Add panel descriptions** for context\n7. **Configure units** correctly\n8. **Set meaningful thresholds** for colors\n9. **Use consistent colors** across dashboards\n10. **Test with different time ranges**\n\n## Dashboard as Code\n\n### Terraform Provisioning\n\n```hcl\nresource \"grafana_dashboard\" \"api_monitoring\" {\n  config_json = file(\"${path.module}\u002Fdashboards\u002Fapi-monitoring.json\")\n  folder      = grafana_folder.monitoring.id\n}\n\nresource \"grafana_folder\" \"monitoring\" {\n  title = \"Production Monitoring\"\n}\n```\n\n### Ansible Provisioning\n\n```yaml\n- name: Deploy Grafana dashboards\n  copy:\n    src: \"{{ item }}\"\n    dest: \u002Fetc\u002Fgrafana\u002Fdashboards\u002F\n  with_fileglob:\n    - \"dashboards\u002F*.json\"\n  notify: restart grafana\n```\n\n## Reference Files\n\n- `assets\u002Fapi-dashboard.json` - API monitoring dashboard\n- `assets\u002Finfrastructure-dashboard.json` - Infrastructure dashboard\n- `assets\u002Fdatabase-dashboard.json` - Database monitoring dashboard\n- `references\u002Fdashboard-design.md` - Dashboard design guide\n\n## Related Skills\n\n- `prometheus-configuration` - For metric collection\n- `slo-implementation` - For SLO dashboards\n","# Grafana Dashboards\n\nCreate and manage production-ready Grafana dashboards for comprehensive system observability.\n\n## Do not use this skill when\n\n- The task is unrelated to grafana dashboards\n- You need a different domain or tool outside this scope\n\n## Instructions\n\n- Clarify goals, constraints, and required inputs.\n- Apply relevant best practices and validate outcomes.\n- Provide actionable steps and verification.\n- If detailed examples are required, open `resources\u002Fimplementation-playbook.md`.\n\n## Purpose\n\nDesign effective Grafana dashboards for monitoring applications, infrastructure, and business metrics.\n\n## Use this skill when\n\n- Visualize Prometheus metrics\n- Create custom dashboards\n- Implement SLO dashboards\n- Monitor infrastructure\n- Track business KPIs\n\n## Dashboard Design Principles\n\n### 1. Hierarchy of Information\n```\n┌─────────────────────────────────────┐\n│  Critical Metrics (Big Numbers)     │\n├─────────────────────────────────────┤\n│  Key Trends (Time Series)           │\n├─────────────────────────────────────┤\n│  Detailed Metrics (Tables\u002FHeatmaps) │\n└─────────────────────────────────────┘\n```\n\n### 2. RED Method (Services)\n- **Rate** - Requests per second\n- **Errors** - Error rate\n- **Duration** - Latency\u002Fresponse time\n\n### 3. USE Method (Resources)\n- **Utilization** - % time resource is busy\n- **Saturation** - Queue length\u002Fwait time\n- **Errors** - Error count\n\n## Dashboard Structure\n\n### API Monitoring Dashboard\n\n```json\n{\n  \"dashboard\": {\n    \"title\": \"API Monitoring\",\n    \"tags\": [\"api\", \"production\"],\n    \"timezone\": \"browser\",\n    \"refresh\": \"30s\",\n    \"panels\": [\n      {\n        \"title\": \"Request Rate\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"sum(rate(http_requests_total[5m])) by (service)\",\n            \"legendFormat\": \"{{service}}\"\n          }\n        ],\n        \"gridPos\": {\"x\": 0, \"y\": 0, \"w\": 12, \"h\": 8}\n      },\n      {\n        \"title\": \"Error Rate %\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"(sum(rate(http_requests_total{status=~\\\"5..\\\"}[5m])) \u002F sum(rate(http_requests_total[5m]))) * 100\",\n            \"legendFormat\": \"Error Rate\"\n          }\n        ],\n        \"alert\": {\n          \"conditions\": [\n            {\n              \"evaluator\": {\"params\": [5], \"type\": \"gt\"},\n              \"operator\": {\"type\": \"and\"},\n              \"query\": {\"params\": [\"A\", \"5m\", \"now\"]},\n              \"type\": \"query\"\n            }\n          ]\n        },\n        \"gridPos\": {\"x\": 12, \"y\": 0, \"w\": 12, \"h\": 8}\n      },\n      {\n        \"title\": \"P95 Latency\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"histogram_quantile(0.95, sum(rate(http_request_duration_seconds_bucket[5m])) by (le, service))\",\n            \"legendFormat\": \"{{service}}\"\n          }\n        ],\n        \"gridPos\": {\"x\": 0, \"y\": 8, \"w\": 24, \"h\": 8}\n      }\n    ]\n  }\n}\n```\n\n**Reference:** See `assets\u002Fapi-dashboard.json`\n\n## Panel Types\n\n### 1. Stat Panel (Single Value)\n```json\n{\n  \"type\": \"stat\",\n  \"title\": \"Total Requests\",\n  \"targets\": [{\n    \"expr\": \"sum(http_requests_total)\"\n  }],\n  \"options\": {\n    \"reduceOptions\": {\n      \"values\": false,\n      \"calcs\": [\"lastNotNull\"]\n    },\n    \"orientation\": \"auto\",\n    \"textMode\": \"auto\",\n    \"colorMode\": \"value\"\n  },\n  \"fieldConfig\": {\n    \"defaults\": {\n      \"thresholds\": {\n        \"mode\": \"absolute\",\n        \"steps\": [\n          {\"value\": 0, \"color\": \"green\"},\n          {\"value\": 80, \"color\": \"yellow\"},\n          {\"value\": 90, \"color\": \"red\"}\n        ]\n      }\n    }\n  }\n}\n```\n\n### 2. Time Series Graph\n```json\n{\n  \"type\": \"graph\",\n  \"title\": \"CPU Usage\",\n  \"targets\": [{\n    \"expr\": \"100 - (avg by (instance) (rate(node_cpu_seconds_total{mode=\\\"idle\\\"}[5m])) * 100)\"\n  }],\n  \"yaxes\": [\n    {\"format\": \"percent\", \"max\": 100, \"min\": 0},\n    {\"format\": \"short\"}\n  ]\n}\n```\n\n### 3. Table Panel\n```json\n{\n  \"type\": \"table\",\n  \"title\": \"Service Status\",\n  \"targets\": [{\n    \"expr\": \"up\",\n    \"format\": \"table\",\n    \"instant\": true\n  }],\n  \"transformations\": [\n    {\n      \"id\": \"organize\",\n      \"options\": {\n        \"excludeByName\": {\"Time\": true},\n        \"indexByName\": {},\n        \"renameByName\": {\n          \"instance\": \"Instance\",\n          \"job\": \"Service\",\n          \"Value\": \"Status\"\n        }\n      }\n    }\n  ]\n}\n```\n\n### 4. Heatmap\n```json\n{\n  \"type\": \"heatmap\",\n  \"title\": \"Latency Heatmap\",\n  \"targets\": [{\n    \"expr\": \"sum(rate(http_request_duration_seconds_bucket[5m])) by (le)\",\n    \"format\": \"heatmap\"\n  }],\n  \"dataFormat\": \"tsbuckets\",\n  \"yAxis\": {\n    \"format\": \"s\"\n  }\n}\n```\n\n## Variables\n\n### Query Variables\n```json\n{\n  \"templating\": {\n    \"list\": [\n      {\n        \"name\": \"namespace\",\n        \"type\": \"query\",\n        \"datasource\": \"Prometheus\",\n        \"query\": \"label_values(kube_pod_info, namespace)\",\n        \"refresh\": 1,\n        \"multi\": false\n      },\n      {\n        \"name\": \"service\",\n        \"type\": \"query\",\n        \"datasource\": \"Prometheus\",\n        \"query\": \"label_values(kube_service_info{namespace=\\\"$namespace\\\"}, service)\",\n        \"refresh\": 1,\n        \"multi\": true\n      }\n    ]\n  }\n}\n```\n\n### Use Variables in Queries\n```\nsum(rate(http_requests_total{namespace=\"$namespace\", service=~\"$service\"}[5m]))\n```\n\n## Alerts in Dashboards\n\n```json\n{\n  \"alert\": {\n    \"name\": \"High Error Rate\",\n    \"conditions\": [\n      {\n        \"evaluator\": {\n          \"params\": [5],\n          \"type\": \"gt\"\n        },\n        \"operator\": {\"type\": \"and\"},\n        \"query\": {\n          \"params\": [\"A\", \"5m\", \"now\"]\n        },\n        \"reducer\": {\"type\": \"avg\"},\n        \"type\": \"query\"\n      }\n    ],\n    \"executionErrorState\": \"alerting\",\n    \"for\": \"5m\",\n    \"frequency\": \"1m\",\n    \"message\": \"Error rate is above 5%\",\n    \"noDataState\": \"no_data\",\n    \"notifications\": [\n      {\"uid\": \"slack-channel\"}\n    ]\n  }\n}\n```\n\n## Dashboard Provisioning\n\n**dashboards.yml:**\n```yaml\napiVersion: 1\n\nproviders:\n  - name: 'default'\n    orgId: 1\n    folder: 'General'\n    type: file\n    disableDeletion: false\n    updateIntervalSeconds: 10\n    allowUiUpdates: true\n    options:\n      path: \u002Fetc\u002Fgrafana\u002Fdashboards\n```\n\n## Common Dashboard Patterns\n\n### Infrastructure Dashboard\n\n**Key Panels:**\n- CPU utilization per node\n- Memory usage per node\n- Disk I\u002FO\n- Network traffic\n- Pod count by namespace\n- Node status\n\n**Reference:** See `assets\u002Finfrastructure-dashboard.json`\n\n### Database Dashboard\n\n**Key Panels:**\n- Queries per second\n- Connection pool usage\n- Query latency (P50, P95, P99)\n- Active connections\n- Database size\n- Replication lag\n- Slow queries\n\n**Reference:** See `assets\u002Fdatabase-dashboard.json`\n\n### Application Dashboard\n\n**Key Panels:**\n- Request rate\n- Error rate\n- Response time (percentiles)\n- Active users\u002Fsessions\n- Cache hit rate\n- Queue length\n\n## Best Practices\n\n1. **Start with templates** (Grafana community dashboards)\n2. **Use consistent naming** for panels and variables\n3. **Group related metrics** in rows\n4. **Set appropriate time ranges** (default: Last 6 hours)\n5. **Use variables** for flexibility\n6. **Add panel descriptions** for context\n7. **Configure units** correctly\n8. **Set meaningful thresholds** for colors\n9. **Use consistent colors** across dashboards\n10. **Test with different time ranges**\n\n## Dashboard as Code\n\n### Terraform Provisioning\n\n```hcl\nresource \"grafana_dashboard\" \"api_monitoring\" {\n  config_json = file(\"${path.module}\u002Fdashboards\u002Fapi-monitoring.json\")\n  folder      = grafana_folder.monitoring.id\n}\n\nresource \"grafana_folder\" \"monitoring\" {\n  title = \"Production Monitoring\"\n}\n```\n\n### Ansible Provisioning\n\n```yaml\n- name: Deploy Grafana dashboards\n  copy:\n    src: \"{{ item }}\"\n    dest: \u002Fetc\u002Fgrafana\u002Fdashboards\u002F\n  with_fileglob:\n    - \"dashboards\u002F*.json\"\n  notify: restart grafana\n```\n\n## Reference Files\n\n- `assets\u002Fapi-dashboard.json` - API monitoring dashboard\n- `assets\u002Finfrastructure-dashboard.json` - Infrastructure dashboard\n- `assets\u002Fdatabase-dashboard.json` - Database monitoring dashboard\n- `references\u002Fdashboard-design.md` - Dashboard design guide\n\n## Related Skills\n\n- `prometheus-configuration` - For metric collection\n- `slo-implementation` - For SLO dashboards\n",{"name":5,"risk":38,"source":42,"description":7},"release\u002Fv4.2.11-panel-pro","a92ea02bcf7e2b3dbaf46d49696c29a3cb490d4f",".github\u002Fskills\u002Fgrafana-dashboards","https:\u002F\u002Fgithub.com\u002Fjaviertarazon\u002Fide-agente-free-jt7-","https:\u002F\u002Fgithub.com\u002Fjaviertarazon","2026-07-12 07:10:45",{"source":8,"skillName":5,"commands":55,"prompt":65,"zipAvailable":66},[56,59,62],{"tool":57,"command":58},"npx","npx skills add javiertarazon\u002Fide-agente-free-jt7- --skill grafana-dashboards",{"tool":60,"command":61},"bunx","bunx skills add javiertarazon\u002Fide-agente-free-jt7- --skill grafana-dashboards",{"tool":63,"command":64},"pnpm","pnpm dlx skills add javiertarazon\u002Fide-agente-free-jt7- --skill grafana-dashboards","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fjaviertarazon\u002Fide-agente-free-jt7-\u002Fblob\u002Frelease\u002Fv4.2.11-panel-pro\u002F.github\u002Fskills\u002Fgrafana-dashboards\u002FSKILL.md",true,[],[69,94,120,139,154,176],{"skillNo":70,"name":71,"nameZh":6,"description":72,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":73,"categories":74,"keywords":78,"publishedAt":43},"01M71TQ7Q6Z10VWF3C2H5X1KW9","zustand-store-ts","Create Zustand stores with TypeScript, subscribeWithSelector middleware, and proper state\u002Faction separation. Use when building React state management, creating global stores, or implementing reacti...","https:\u002F\u002Fgithub.com\u002Fjaviertarazon\u002Fide-agente-free-jt7-\u002Fblob\u002Frelease\u002Fv4.2.11-panel-pro\u002F.github\u002Fskills\u002Fzustand-store-ts\u002FSKILL.md",[75],{"categoryNo":76,"categoryName":77,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000009","前端开发",[79,80,81,42,82,83,29,84,39,38,85,86,87,35,88,89,90,91,92,93],"zustand","store","zustand store ts","middleware","implementing","react state management","react","with","state","state management","typescript","action","management","separation","global",{"skillNo":95,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":98,"categories":99,"keywords":103,"publishedAt":43},"01M71TQ5EAR40G6W0MV5ZDVEZT","zoom-automation","Automate Zoom meeting creation, management, recordings, webinars, and participant tracking via Rube MCP (Composio). Always search tools first for current schemas.","https:\u002F\u002Fgithub.com\u002Fjaviertarazon\u002Fide-agente-free-jt7-\u002Fblob\u002Frelease\u002Fv4.2.11-panel-pro\u002F.github\u002Fskills\u002Fzoom-automation\u002FSKILL.md",[100],{"categoryNo":101,"categoryName":102,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[104,105,106,42,107,33,108,109,110,38,111,112,113,114,115,116,117,118,91,119],"zoom automation","zoom","automation","creation","search","schemas","MCP","first","via","meeting","search tools","tracking","webinars","composio","recordings","Tools",{"skillNo":121,"name":122,"nameZh":6,"description":123,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":124,"categories":125,"keywords":127,"publishedAt":43},"01M71TQ29B1EYBCEAP1ZBGXQ1A","zoho-crm-automation","Automate Zoho CRM tasks via Rube MCP (Composio): create\u002Fupdate records, search contacts, manage leads, and convert leads. Always search tools first for current schemas.","https:\u002F\u002Fgithub.com\u002Fjaviertarazon\u002Fide-agente-free-jt7-\u002Fblob\u002Frelease\u002Fv4.2.11-panel-pro\u002F.github\u002Fskills\u002Fzoho-crm-automation\u002FSKILL.md",[126],{"categoryNo":101,"categoryName":102,"taxonomyType":20,"taxonomyTypeDesc":21},[128,129,106,130,131,132,42,133,134,33,31,108,109,135,110,38,136,137,138,35],"crm automation","zoho crm automation","crm","zoho crm","zoho","leads","manage leads","records","convert","tasks","contacts",{"skillNo":140,"name":141,"nameZh":6,"description":142,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":143,"categories":144,"keywords":146,"publishedAt":43},"01M71TPZPMN60DH0XV58KVHY23","zendesk-automation","Automate Zendesk tasks via Rube MCP (Composio): tickets, users, organizations, replies. Always search tools first for current schemas.","https:\u002F\u002Fgithub.com\u002Fjaviertarazon\u002Fide-agente-free-jt7-\u002Fblob\u002Frelease\u002Fv4.2.11-panel-pro\u002F.github\u002Fskills\u002Fzendesk-automation\u002FSKILL.md",[145],{"categoryNo":101,"categoryName":102,"taxonomyType":20,"taxonomyTypeDesc":21},[147,106,148,42,33,108,109,110,149,38,137,150,151,111,112,152,114,117,119,153],"zendesk automation","zendesk","organizations","replies","users","tickets","automate",{"skillNo":155,"name":156,"nameZh":6,"description":157,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":158,"categories":159,"keywords":160,"publishedAt":43},"01M71TPXDWKHKG4N6TVEPXWD0N","zapier-make-patterns","No-code automation democratizes workflow building. Zapier and Make (formerly Integromat) let non-developers automate business processes without writing code. But no-code doesn't mean no-complexity ...","https:\u002F\u002Fgithub.com\u002Fjaviertarazon\u002Fide-agente-free-jt7-\u002Fblob\u002Frelease\u002Fv4.2.11-panel-pro\u002F.github\u002Fskills\u002Fzapier-make-patterns\u002FSKILL.md",[],[161,162,163,164,165,166,167,168,169,106,170,38,171,172,173,174,175,153],"zapier make patterns","zapier","patterns","make","No-Code","complexity","writing","spawner","business","workflow","code","integromat","apache","processes","but",{"skillNo":177,"name":178,"nameZh":6,"description":179,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":180,"categories":181,"keywords":185,"publishedAt":43},"01M71TPT5T10WXNKW9G7ZXZ27W","youtube-summarizer","Extract transcripts from YouTube videos and generate comprehensive, detailed summaries using intelligent analysis frameworks","https:\u002F\u002Fgithub.com\u002Fjaviertarazon\u002Fide-agente-free-jt7-\u002Fblob\u002Frelease\u002Fv4.2.11-panel-pro\u002F.github\u002Fskills\u002Fyoutube-summarizer\u002FSKILL.md",[182],{"categoryNo":183,"categoryName":184,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",[186,187,188,189,42,190,191,192,193,194,195,196,171,197,198,199,200,201,202,203],"summarizer","youtube","youtube summarizer","Video","content-analysis","frameworks","copilot","2025","github-copilot","extract transcripts","analysis","codex","cli","summaries","github","generate","summarization","2026"]