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Use when users want to check service status, view metrics, monitor performance, or verify deployments are healthy.","Thamielis\u002F.agents","Thamielis","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F52717133?v=4","01M71NG040Z4RAKTDW6JVQTZA0","01M71NG04N9WFE1H3RH0BF6VDY",0,"MIT","https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fplugins\u002Frender\u002Fskills\u002Frender-monitor\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发","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],"render monitor","monitor","render","healthy","use","deployments","real-time","view","usage","metrics","Tools","status","cli","monitoring","logs","when","MCP","render mcp","time","performance","2026-11-10 13:02:02",false,"---\nname: render-monitor\ndescription: Monitor Render services in real-time. Check health, performance metrics, logs, and resource usage. Use when users want to check service status, view metrics, monitor performance, or verify deployments are healthy.\nlicense: MIT\ncompatibility: Requires Render MCP tools or CLI\nmetadata:\n  author: Render\n  version: \"1.0.0\"\n  category: monitoring\n---\n\n# Monitor Render Services\n\nReal-time monitoring of Render services including health checks, performance metrics, and logs.\n\n## When to Use This Skill\n\nActivate this skill when users want to:\n- Check if services are healthy\n- View performance metrics\n- Monitor logs\n- Verify a deployment is working\n- Investigate slow performance\n- Check database health\n\n## Prerequisites\n\n**MCP tools (preferred):** Test with `list_services()` - provides structured data\n\n**CLI (fallback):** `render --version` - use if MCP tools unavailable\n\n**Authentication:** For MCP, use an API key (set in the MCP config or via the `RENDER_API_KEY` env var, depending on tool). For CLI, verify with `render whoami -o json`.\n\n**Workspace:** `get_selected_workspace()` or `render workspace current -o json`\n\n> **Note:** MCP tools require the Render MCP server. If unavailable, use the CLI for status and logs; metrics and database queries require MCP.\n\n## MCP Setup (Per Tool)\n\nIf `list_services()` fails because MCP isn't configured, guide the user to set up the hosted Render MCP server. Ask which AI tool they're using, then provide the matching instructions below. Always use their API key.\n\n### Cursor\n\nWalk the user through these steps:\n\n1) Get a Render API key:\n```\nhttps:\u002F\u002Fdashboard.render.com\u002Fu\u002F*\u002Fsettings#api-keys\n```\n\n2) Add this to `~\u002F.cursor\u002Fmcp.json` (replace `\u003CYOUR_API_KEY>`):\n```json\n{\n  \"mcpServers\": {\n    \"render\": {\n      \"url\": \"https:\u002F\u002Fmcp.render.com\u002Fmcp\",\n      \"headers\": {\n        \"Authorization\": \"Bearer \u003CYOUR_API_KEY>\"\n      }\n    }\n  }\n}\n```\n\n3) Restart Cursor, then retry `list_services()`.\n\n### Claude Code\n\nWalk the user through these steps:\n\n1) Get a Render API key:\n```\nhttps:\u002F\u002Fdashboard.render.com\u002Fu\u002F*\u002Fsettings#api-keys\n```\n\n2) Add the MCP server with Claude Code (replace `\u003CYOUR_API_KEY>`):\n```bash\nclaude mcp add --transport http render https:\u002F\u002Fmcp.render.com\u002Fmcp --header \"Authorization: Bearer \u003CYOUR_API_KEY>\"\n```\n\n3) Restart Claude Code, then retry `list_services()`.\n\n### Codex\n\nWalk the user through these steps:\n\n1) Get a Render API key:\n```\nhttps:\u002F\u002Fdashboard.render.com\u002Fu\u002F*\u002Fsettings#api-keys\n```\n\n2) Set it in their shell:\n```bash\nexport RENDER_API_KEY=\"\u003CYOUR_API_KEY>\"\n```\n\n3) Add the MCP server with the Codex CLI:\n```bash\ncodex mcp add render --url https:\u002F\u002Fmcp.render.com\u002Fmcp --bearer-token-env-var RENDER_API_KEY\n```\n\n4) Restart Codex, then retry `list_services()`.\n\n### Other Tools\n\nIf the user is on another AI app, direct them to the Render MCP docs for that tool's setup steps and install method.\n\n### Workspace Selection\n\nAfter MCP is configured, have the user set the active Render workspace with a prompt like:\n\n```\nSet my Render workspace to [WORKSPACE_NAME]\n```\n\n---\n\n## Quick Health Check\n\nRun these 5 checks to assess service health:\n\n```\n# 1. Check service status\nlist_services()\n\n# 2. Check latest deploy\nlist_deploys(serviceId: \"\u003Cservice-id>\", limit: 1)\n\n# 3. Check for errors\nlist_logs(resource: [\"\u003Cservice-id>\"], level: [\"error\"], limit: 20)\n\n# 4. Check resource usage\nget_metrics(resourceId: \"\u003Cservice-id>\", metricTypes: [\"cpu_usage\", \"memory_usage\"])\n\n# 5. Check latency\nget_metrics(resourceId: \"\u003Cservice-id>\", metricTypes: [\"http_latency\"], httpLatencyQuantile: 0.95)\n```\n\n---\n\n## Service Health\n\n### Check Status\n\n```\nlist_services()\n```\n\n```\nget_service(serviceId: \"\u003Cid>\")\n```\n\n### Check Deployments\n\n```\nlist_deploys(serviceId: \"\u003Cservice-id>\", limit: 5)\n```\n\n| Status | Meaning |\n|--------|---------|\n| `live` | Deployment successful |\n| `build_in_progress` | Building |\n| `build_failed` | Build failed |\n| `deactivated` | Replaced by newer deploy |\n\n### Check Errors\n\n```\nlist_logs(resource: [\"\u003Cservice-id>\"], level: [\"error\"], limit: 50)\n```\n\n```\nlist_logs(resource: [\"\u003Cservice-id>\"], statusCode: [\"500\", \"502\", \"503\"], limit: 50)\n```\n\n---\n\n## Performance Metrics\n\n### CPU & Memory\n\n```\nget_metrics(\n  resourceId: \"\u003Cservice-id>\",\n  metricTypes: [\"cpu_usage\", \"memory_usage\", \"cpu_limit\", \"memory_limit\"]\n)\n```\n\n| Metric | Healthy | Warning | Critical |\n|--------|---------|---------|----------|\n| CPU | \u003C70% | 70-85% | >85% |\n| Memory | \u003C80% | 80-90% | >90% |\n\n### HTTP Latency\n\n```\nget_metrics(\n  resourceId: \"\u003Cservice-id>\",\n  metricTypes: [\"http_latency\"],\n  httpLatencyQuantile: 0.95\n)\n```\n\n| p95 Latency | Status |\n|-------------|--------|\n| \u003C200ms | Excellent |\n| 200-500ms | Good |\n| 500ms-1s | Concerning |\n| >1s | Problem |\n\n### Request Count\n\n```\nget_metrics(\n  resourceId: \"\u003Cservice-id>\",\n  metricTypes: [\"http_request_count\"]\n)\n```\n\n### Filter by Endpoint\n\n```\nget_metrics(\n  resourceId: \"\u003Cservice-id>\",\n  metricTypes: [\"http_latency\"],\n  httpPath: \"\u002Fapi\u002Fusers\"\n)\n```\n\nDetailed metrics guide: [references\u002Fmetrics-guide.md](references\u002Fmetrics-guide.md)\n\n---\n\n## Database Monitoring\n\n### PostgreSQL Status\n\n```\nlist_postgres_instances()\nget_postgres(postgresId: \"\u003Cpostgres-id>\")\n```\n\n### Connection Count\n\n```\nget_metrics(resourceId: \"\u003Cpostgres-id>\", metricTypes: [\"active_connections\"])\n```\n\n### Query Database\n\n```\nquery_render_postgres(\n  postgresId: \"\u003Cpostgres-id>\",\n  sql: \"SELECT state, count(*) FROM pg_stat_activity GROUP BY state\"\n)\n```\n\n### Find Slow Queries\n\n```\nquery_render_postgres(\n  postgresId: \"\u003Cpostgres-id>\",\n  sql: \"SELECT query, mean_exec_time FROM pg_stat_statements ORDER BY mean_exec_time DESC LIMIT 10\"\n)\n```\n\n### Key-Value Store\n\n```\nlist_key_value()\nget_key_value(keyValueId: \"\u003Ckv-id>\")\n```\n\n---\n\n## Log Monitoring\n\n### Recent Logs\n\n```\nlist_logs(resource: [\"\u003Cservice-id>\"], limit: 100)\n```\n\n### Error Logs\n\n```\nlist_logs(resource: [\"\u003Cservice-id>\"], level: [\"error\"], limit: 50)\n```\n\n### Search Logs\n\n```\nlist_logs(resource: [\"\u003Cservice-id>\"], text: [\"timeout\", \"error\"], limit: 50)\n```\n\n### Filter by Time\n\n```\nlist_logs(\n  resource: [\"\u003Cservice-id>\"],\n  startTime: \"2024-01-15T10:00:00Z\",\n  endTime: \"2024-01-15T11:00:00Z\"\n)\n```\n\n### Stream Logs (CLI)\n\n```bash\nrender logs -r \u003Cservice-id> --tail -o text\n```\n\n---\n\n## Quick Reference\n\n### MCP Tools\n\n```\n# Services\nlist_services()\nget_service(serviceId: \"\u003Cid>\")\nlist_deploys(serviceId: \"\u003Cid>\", limit: 5)\n\n# Logs\nlist_logs(resource: [\"\u003Cid>\"], level: [\"error\"], limit: 100)\nlist_logs(resource: [\"\u003Cid>\"], text: [\"search\"], limit: 50)\n\n# Metrics\nget_metrics(resourceId: \"\u003Cid>\", metricTypes: [\"cpu_usage\", \"memory_usage\"])\nget_metrics(resourceId: \"\u003Cid>\", metricTypes: [\"http_latency\"], httpLatencyQuantile: 0.95)\nget_metrics(resourceId: \"\u003Cid>\", metricTypes: [\"http_request_count\"])\n\n# Database\nlist_postgres_instances()\nget_postgres(postgresId: \"\u003Cid>\")\nquery_render_postgres(postgresId: \"\u003Cid>\", sql: \"SELECT ...\")\nget_metrics(resourceId: \"\u003Cpostgres-id>\", metricTypes: [\"active_connections\"])\n\n# Key-Value\nlist_key_value()\nget_key_value(keyValueId: \"\u003Cid>\")\n```\n\n### CLI Commands (Fallback)\n\nUse these if MCP tools are unavailable:\n\n```bash\n# Service status\nrender services -o json\nrender services instances \u003Cservice-id>\n\n# Deployments\nrender deploys list \u003Cservice-id> -o json\n\n# Logs\nrender logs -r \u003Cservice-id> --tail -o text          # Stream logs\nrender logs -r \u003Cservice-id> --level error -o json   # Error logs\nrender logs -r \u003Cservice-id> --type deploy -o json   # Build logs\n\n# Database\nrender psql \u003Cdatabase-id>                           # Connect to PostgreSQL\n\n# SSH for live debugging\nrender ssh \u003Cservice-id>\n```\n\n### Healthy Service Indicators\n\n| Indicator | Healthy | Warning | Critical |\n|-----------|---------|---------|----------|\n| Deploy Status | `live` | `update_in_progress` | `build_failed` |\n| Error Rate | \u003C0.1% | 0.1-1% | >1% |\n| p95 Latency | \u003C500ms | 500ms-2s | >2s |\n| CPU Usage | \u003C70% | 70-90% | >90% |\n| Memory Usage | \u003C80% | 80-95% | >95% |\n\n---\n\n## References\n\n- **Metrics guide:** [references\u002Fmetrics-guide.md](references\u002Fmetrics-guide.md)\n\n## Related Skills\n\n- **deploy:** Deploy new applications to Render\n- **debug:** Diagnose and fix deployment failures\n","# Monitor Render Services\n\nReal-time monitoring of Render services including health checks, performance metrics, and logs.\n\n## When to Use This Skill\n\nActivate this skill when users want to:\n- Check if services are healthy\n- View performance metrics\n- Monitor logs\n- Verify a deployment is working\n- Investigate slow performance\n- Check database health\n\n## Prerequisites\n\n**MCP tools (preferred):** Test with `list_services()` - provides structured data\n\n**CLI (fallback):** `render --version` - use if MCP tools unavailable\n\n**Authentication:** For MCP, use an API key (set in the MCP config or via the `RENDER_API_KEY` env var, depending on tool). For CLI, verify with `render whoami -o json`.\n\n**Workspace:** `get_selected_workspace()` or `render workspace current -o json`\n\n> **Note:** MCP tools require the Render MCP server. If unavailable, use the CLI for status and logs; metrics and database queries require MCP.\n\n## MCP Setup (Per Tool)\n\nIf `list_services()` fails because MCP isn't configured, guide the user to set up the hosted Render MCP server. Ask which AI tool they're using, then provide the matching instructions below. Always use their API key.\n\n### Cursor\n\nWalk the user through these steps:\n\n1) Get a Render API key:\n```\nhttps:\u002F\u002Fdashboard.render.com\u002Fu\u002F*\u002Fsettings#api-keys\n```\n\n2) Add this to `~\u002F.cursor\u002Fmcp.json` (replace `\u003CYOUR_API_KEY>`):\n```json\n{\n  \"mcpServers\": {\n    \"render\": {\n      \"url\": \"https:\u002F\u002Fmcp.render.com\u002Fmcp\",\n      \"headers\": {\n        \"Authorization\": \"Bearer \u003CYOUR_API_KEY>\"\n      }\n    }\n  }\n}\n```\n\n3) Restart Cursor, then retry `list_services()`.\n\n### Claude Code\n\nWalk the user through these steps:\n\n1) Get a Render API key:\n```\nhttps:\u002F\u002Fdashboard.render.com\u002Fu\u002F*\u002Fsettings#api-keys\n```\n\n2) Add the MCP server with Claude Code (replace `\u003CYOUR_API_KEY>`):\n```bash\nclaude mcp add --transport http render https:\u002F\u002Fmcp.render.com\u002Fmcp --header \"Authorization: Bearer \u003CYOUR_API_KEY>\"\n```\n\n3) Restart Claude Code, then retry `list_services()`.\n\n### Codex\n\nWalk the user through these steps:\n\n1) Get a Render API key:\n```\nhttps:\u002F\u002Fdashboard.render.com\u002Fu\u002F*\u002Fsettings#api-keys\n```\n\n2) Set it in their shell:\n```bash\nexport RENDER_API_KEY=\"\u003CYOUR_API_KEY>\"\n```\n\n3) Add the MCP server with the Codex CLI:\n```bash\ncodex mcp add render --url https:\u002F\u002Fmcp.render.com\u002Fmcp --bearer-token-env-var RENDER_API_KEY\n```\n\n4) Restart Codex, then retry `list_services()`.\n\n### Other Tools\n\nIf the user is on another AI app, direct them to the Render MCP docs for that tool's setup steps and install method.\n\n### Workspace Selection\n\nAfter MCP is configured, have the user set the active Render workspace with a prompt like:\n\n```\nSet my Render workspace to [WORKSPACE_NAME]\n```\n\n---\n\n## Quick Health Check\n\nRun these 5 checks to assess service health:\n\n```\n# 1. Check service status\nlist_services()\n\n# 2. Check latest deploy\nlist_deploys(serviceId: \"\u003Cservice-id>\", limit: 1)\n\n# 3. Check for errors\nlist_logs(resource: [\"\u003Cservice-id>\"], level: [\"error\"], limit: 20)\n\n# 4. Check resource usage\nget_metrics(resourceId: \"\u003Cservice-id>\", metricTypes: [\"cpu_usage\", \"memory_usage\"])\n\n# 5. Check latency\nget_metrics(resourceId: \"\u003Cservice-id>\", metricTypes: [\"http_latency\"], httpLatencyQuantile: 0.95)\n```\n\n---\n\n## Service Health\n\n### Check Status\n\n```\nlist_services()\n```\n\n```\nget_service(serviceId: \"\u003Cid>\")\n```\n\n### Check Deployments\n\n```\nlist_deploys(serviceId: \"\u003Cservice-id>\", limit: 5)\n```\n\n| Status | Meaning |\n|--------|---------|\n| `live` | Deployment successful |\n| `build_in_progress` | Building |\n| `build_failed` | Build failed |\n| `deactivated` | Replaced by newer deploy |\n\n### Check Errors\n\n```\nlist_logs(resource: [\"\u003Cservice-id>\"], level: [\"error\"], limit: 50)\n```\n\n```\nlist_logs(resource: [\"\u003Cservice-id>\"], statusCode: [\"500\", \"502\", \"503\"], limit: 50)\n```\n\n---\n\n## Performance Metrics\n\n### CPU & Memory\n\n```\nget_metrics(\n  resourceId: \"\u003Cservice-id>\",\n  metricTypes: [\"cpu_usage\", \"memory_usage\", \"cpu_limit\", \"memory_limit\"]\n)\n```\n\n| Metric | Healthy | Warning | Critical |\n|--------|---------|---------|----------|\n| CPU | \u003C70% | 70-85% | >85% |\n| Memory | \u003C80% | 80-90% | >90% |\n\n### HTTP Latency\n\n```\nget_metrics(\n  resourceId: \"\u003Cservice-id>\",\n  metricTypes: [\"http_latency\"],\n  httpLatencyQuantile: 0.95\n)\n```\n\n| p95 Latency | Status |\n|-------------|--------|\n| \u003C200ms | Excellent |\n| 200-500ms | Good |\n| 500ms-1s | Concerning |\n| >1s | Problem |\n\n### Request Count\n\n```\nget_metrics(\n  resourceId: \"\u003Cservice-id>\",\n  metricTypes: [\"http_request_count\"]\n)\n```\n\n### Filter by Endpoint\n\n```\nget_metrics(\n  resourceId: \"\u003Cservice-id>\",\n  metricTypes: [\"http_latency\"],\n  httpPath: \"\u002Fapi\u002Fusers\"\n)\n```\n\nDetailed metrics guide: [references\u002Fmetrics-guide.md](references\u002Fmetrics-guide.md)\n\n---\n\n## Database Monitoring\n\n### PostgreSQL Status\n\n```\nlist_postgres_instances()\nget_postgres(postgresId: \"\u003Cpostgres-id>\")\n```\n\n### Connection Count\n\n```\nget_metrics(resourceId: \"\u003Cpostgres-id>\", metricTypes: [\"active_connections\"])\n```\n\n### Query Database\n\n```\nquery_render_postgres(\n  postgresId: \"\u003Cpostgres-id>\",\n  sql: \"SELECT state, count(*) FROM pg_stat_activity GROUP BY state\"\n)\n```\n\n### Find Slow Queries\n\n```\nquery_render_postgres(\n  postgresId: \"\u003Cpostgres-id>\",\n  sql: \"SELECT query, mean_exec_time FROM pg_stat_statements ORDER BY mean_exec_time DESC LIMIT 10\"\n)\n```\n\n### Key-Value Store\n\n```\nlist_key_value()\nget_key_value(keyValueId: \"\u003Ckv-id>\")\n```\n\n---\n\n## Log Monitoring\n\n### Recent Logs\n\n```\nlist_logs(resource: [\"\u003Cservice-id>\"], limit: 100)\n```\n\n### Error Logs\n\n```\nlist_logs(resource: [\"\u003Cservice-id>\"], level: [\"error\"], limit: 50)\n```\n\n### Search Logs\n\n```\nlist_logs(resource: [\"\u003Cservice-id>\"], text: [\"timeout\", \"error\"], limit: 50)\n```\n\n### Filter by Time\n\n```\nlist_logs(\n  resource: [\"\u003Cservice-id>\"],\n  startTime: \"2024-01-15T10:00:00Z\",\n  endTime: \"2024-01-15T11:00:00Z\"\n)\n```\n\n### Stream Logs (CLI)\n\n```bash\nrender logs -r \u003Cservice-id> --tail -o text\n```\n\n---\n\n## Quick Reference\n\n### MCP Tools\n\n```\n# Services\nlist_services()\nget_service(serviceId: \"\u003Cid>\")\nlist_deploys(serviceId: \"\u003Cid>\", limit: 5)\n\n# Logs\nlist_logs(resource: [\"\u003Cid>\"], level: [\"error\"], limit: 100)\nlist_logs(resource: [\"\u003Cid>\"], text: [\"search\"], limit: 50)\n\n# Metrics\nget_metrics(resourceId: \"\u003Cid>\", metricTypes: [\"cpu_usage\", \"memory_usage\"])\nget_metrics(resourceId: \"\u003Cid>\", metricTypes: [\"http_latency\"], httpLatencyQuantile: 0.95)\nget_metrics(resourceId: \"\u003Cid>\", metricTypes: [\"http_request_count\"])\n\n# Database\nlist_postgres_instances()\nget_postgres(postgresId: \"\u003Cid>\")\nquery_render_postgres(postgresId: \"\u003Cid>\", sql: \"SELECT ...\")\nget_metrics(resourceId: \"\u003Cpostgres-id>\", metricTypes: [\"active_connections\"])\n\n# Key-Value\nlist_key_value()\nget_key_value(keyValueId: \"\u003Cid>\")\n```\n\n### CLI Commands (Fallback)\n\nUse these if MCP tools are unavailable:\n\n```bash\n# Service status\nrender services -o json\nrender services instances \u003Cservice-id>\n\n# Deployments\nrender deploys list \u003Cservice-id> -o json\n\n# Logs\nrender logs -r \u003Cservice-id> --tail -o text          # Stream logs\nrender logs -r \u003Cservice-id> --level error -o json   # Error logs\nrender logs -r \u003Cservice-id> --type deploy -o json   # Build logs\n\n# Database\nrender psql \u003Cdatabase-id>                           # Connect to PostgreSQL\n\n# SSH for live debugging\nrender ssh \u003Cservice-id>\n```\n\n### Healthy Service Indicators\n\n| Indicator | Healthy | Warning | Critical |\n|-----------|---------|---------|----------|\n| Deploy Status | `live` | `update_in_progress` | `build_failed` |\n| Error Rate | \u003C0.1% | 0.1-1% | >1% |\n| p95 Latency | \u003C500ms | 500ms-2s | >2s |\n| CPU Usage | \u003C70% | 70-90% | >90% |\n| Memory Usage | \u003C80% | 80-95% | >95% |\n\n---\n\n## References\n\n- **Metrics guide:** [references\u002Fmetrics-guide.md](references\u002Fmetrics-guide.md)\n\n## Related Skills\n\n- **deploy:** Deploy new applications to Render\n- **debug:** Diagnose and fix deployment failures\n",{"name":5,"license":14,"metadata":48,"description":7,"compatibility":51},{"author":49,"version":50,"category":36},"Render","1.0.0","Requires Render MCP tools or CLI","main","dd673a28ba66191245f0e384c525b1dcff1c427a","plugins\u002Frender\u002Fskills\u002Frender-monitor","https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents","https:\u002F\u002Fgithub.com\u002FThamielis","2026-06-08 04:03:12",{"source":8,"skillName":5,"commands":59,"prompt":69,"zipAvailable":70},[60,63,66],{"tool":61,"command":62},"npx","npx skills add Thamielis\u002F.agents --skill render-monitor",{"tool":64,"command":65},"bunx","bunx skills add Thamielis\u002F.agents --skill render-monitor",{"tool":67,"command":68},"pnpm","pnpm dlx skills add Thamielis\u002F.agents --skill render-monitor","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fplugins\u002Frender\u002Fskills\u002Frender-monitor\u002FSKILL.md",true,[72,78,84],{"path":73,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":76,"sourceHtmlUrl":77},"agents\u002Fopenai.yaml","REFERENCE","参考文档",250,"https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fplugins\u002Frender\u002Fskills\u002Frender-monitor\u002Fagents\u002Fopenai.yaml",{"path":79,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":82,"sourceHtmlUrl":83},"assets\u002Flogo.svg","ASSET","资产文件",1894,"https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fplugins\u002Frender\u002Fskills\u002Frender-monitor\u002Fassets\u002Flogo.svg",{"path":85,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":86,"sourceHtmlUrl":87},"references\u002Fmetrics-guide.md",8133,"https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fplugins\u002Frender\u002Fskills\u002Frender-monitor\u002Freferences\u002Fmetrics-guide.md",[89,120,145,175,202,227],{"skillNo":90,"name":91,"nameZh":6,"description":92,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":93,"licenseFileUrl":94,"sourceHtmlUrl":95,"categories":96,"keywords":103,"publishedAt":43},"01M71QFD7835D0JG8MS43NRRVE","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","Apache-2.0","https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fskills\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fskills\u002Fwebapp-testing\u002FSKILL.md",[97,100],{"categoryNo":98,"categoryName":99,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":101,"categoryName":102,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000009","前端开发",[104,105,106,107,108,109,37,110,111,112,113,114,115,116,117,118,119],"webapp","testing","webapp testing","local","frontend","debugging","browser","ui","screenshots","for","applications","toolkit","with","playwright","web","behavior",{"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":93,"licenseFileUrl":124,"sourceHtmlUrl":125,"categories":126,"keywords":128,"publishedAt":43},"01M71QF1RVYQPZ2HPHXYWBC27K","web-artifacts-builder","Suite of tools for creating elaborate, multi-component Codex.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.","https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fskills\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fskills\u002Fweb-artifacts-builder\u002FSKILL.md",[127],{"categoryNo":101,"categoryName":102,"taxonomyType":20,"taxonomyTypeDesc":21},[129,130,131,118,132,133,134,113,135,136,108,137,27,138,139,140,141,142,143,144],"builder","artifacts builder","artifacts","web artifacts builder","single-file","css","Tailwind","ui components","single","file","components","react","multi","state","routing","state management",{"skillNo":146,"name":147,"nameZh":6,"description":148,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":149,"categories":150,"keywords":157,"publishedAt":43},"01M71QEMXGG7MTTMSRVE3YFCXC","visual-explainer","Generate beautiful, self-contained HTML pages that visually explain systems, code changes, plans, and data. Use when the user asks for a diagram, architecture overview, diff review, plan review, project recap, comparison table, or any visual explanation of technical concepts. Also use proactively when you are about to render a complex ASCII table (4+ rows or 3+ columns) — present it as a styled HTML page instead.","https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fskills\u002Fvisual-explainer\u002FSKILL.md",[151,152],{"categoryNo":101,"categoryName":102,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":153,"categoryName":154,"taxonomyType":155,"taxonomyTypeDesc":156},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[158,159,160,161,162,163,164,165,166,167,168,169,170,171,30,113,172,173,174,27],"visual","visual explainer","explainer","project","files","image","you","architecture","plan","generate","present","concepts","table","as","ascii table","ascii","surf",{"skillNo":176,"name":177,"nameZh":6,"description":178,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":179,"categories":180,"keywords":185,"publishedAt":43},"01M71QDJVMVM82514TRK7VHXC5","transloadit-media-processing","Process media files (video, audio, images, documents) using Transloadit. Use when asked to encode video to HLS\u002FMP4, generate thumbnails, resize or watermark images, extract audio, concatenate clips, add subtitles, OCR documents, or run any media processing pipeline. Covers 86+ processing robots for file transformation at scale.","https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fskills\u002Ftransloadit-media-processing\u002FSKILL.md",[181,184],{"categoryNo":182,"categoryName":183,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[186,187,188,189,190,191,192,193,194,195,162,39,196,197,38,198,199,200,201,35],"Media","processing","transloadit media processing","media processing","transloadit","images","Video","ocr","Audio","pipeline","free","documents","mcp server","thumbnails","server","mcp-server",{"skillNo":203,"name":204,"nameZh":6,"description":205,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":93,"licenseFileUrl":206,"sourceHtmlUrl":207,"categories":208,"keywords":212,"publishedAt":43},"01M71QDEJ4M9TP6VZRNK3J9NKX","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\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fskills\u002Ftheme-factory\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fskills\u002Ftheme-factory\u002FSKILL.md",[209],{"categoryNo":210,"categoryName":211,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000015","视觉设计",[213,214,215,216,217,113,218,219,220,221,164,131,222,115,223,224,116,225,167,226],"theme","theme factory","factory","SET","slides","landing","pages","new","themes","apply","can","fonts","artifact","fly",{"skillNo":228,"name":229,"nameZh":6,"description":230,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":231,"categories":232,"keywords":236,"publishedAt":43},"01M71QD9QXM9M9RWQX40E981D4","terraform-azurerm-set-diff-analyzer","Analyze Terraform plan JSON output for AzureRM Provider to distinguish between false-positive diffs (order-only changes in Set-type attributes) and actual resource changes. Use when reviewing terraform plan output for Azure resources like Application Gateway, Load Balancer, Firewall, Front Door, NSG, and other resources with Set-type attributes that cause spurious diffs due to internal ordering changes.","https:\u002F\u002Fgithub.com\u002FThamielis\u002F.agents\u002Fblob\u002Fmain\u002Fskills\u002Fterraform-azurerm-set-diff-analyzer\u002FSKILL.md",[233],{"categoryNo":234,"categoryName":235,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000011","运维与部署",[216,237,238,239,240,241,242,243,244,113,245,246,247,248,249,250,251,252,27,253],"diff","terraform azurerm set diff analyzer","analyzer","terraform","gateway","firewall","resources","attributes","provider","resource changes","balancer","front","azure","diffs","load balancer","only","load"]