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Use when users want to check service status, view metrics, monitor performance, or verify deployments are healthy.","gaos6e\u002FMyOpenclaw","gaos6e","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F246307622?v=4","01M6GQWTQ9F7C09EV7E2XHF4WY","Gao Se","01M6GQWTVEYHK6B8YJT9M9BJA3",0,"MIT","https:\u002F\u002Fgithub.com\u002Fgaos6e\u002FMyOpenclaw\u002Fblob\u002Fmain\u002F.codex-openclaw\u002F.tmp\u002Fplugins\u002Fplugins\u002Frender\u002Fskills\u002Frender-monitor\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"render","monitor","render monitor","check","usage","render mcp","healthy","time","deployments","use","view","MCP","real-time","Tools","monitoring","logs","metrics","status","performance","cli","2026-11-10 10:12:30",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":15,"metadata":49,"description":7,"compatibility":52},{"author":50,"version":51,"category":38},"Render","1.0.0","Requires Render MCP tools or CLI","main","2f5832fbc22d173cdfdfb1eb0fbb00c0945c30fe",".codex-openclaw\u002F.tmp\u002Fplugins\u002Fplugins\u002Frender\u002Fskills\u002Frender-monitor","https:\u002F\u002Fgithub.com\u002Fgaos6e\u002FMyOpenclaw","https:\u002F\u002Fgithub.com\u002Fgaos6e","http:\u002F\u002Fwww.gzhu.edu.cn","2026-04-28 23:02:03",{"source":8,"skillName":5,"commands":61,"prompt":71,"zipAvailable":72},[62,65,68],{"tool":63,"command":64},"npx","npx skills add gaos6e\u002FMyOpenclaw --skill render-monitor",{"tool":66,"command":67},"bunx","bunx skills add gaos6e\u002FMyOpenclaw --skill render-monitor",{"tool":69,"command":70},"pnpm","pnpm dlx skills add gaos6e\u002FMyOpenclaw --skill render-monitor","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fgaos6e\u002FMyOpenclaw\u002Fblob\u002Fmain\u002F.codex-openclaw\u002F.tmp\u002Fplugins\u002Fplugins\u002Frender\u002Fskills\u002Frender-monitor\u002FSKILL.md",true,[74,80],{"path":75,"resourceType":76,"resourceTypeDesc":77,"sizeBytes":78,"sourceHtmlUrl":79},"assets\u002Flogo.svg","ASSET","资产文件",1894,"https:\u002F\u002Fgithub.com\u002Fgaos6e\u002FMyOpenclaw\u002Fblob\u002Fmain\u002F.codex-openclaw\u002F.tmp\u002Fplugins\u002Fplugins\u002Frender\u002Fskills\u002Frender-monitor\u002Fassets\u002Flogo.svg",{"path":81,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":84,"sourceHtmlUrl":85},"references\u002Fmetrics-guide.md","REFERENCE","参考文档",8133,"https:\u002F\u002Fgithub.com\u002Fgaos6e\u002FMyOpenclaw\u002Fblob\u002Fmain\u002F.codex-openclaw\u002F.tmp\u002Fplugins\u002Fplugins\u002Frender\u002Fskills\u002Frender-monitor\u002Freferences\u002Fmetrics-guide.md",[87,122,146,169,193,210],{"skillNo":88,"name":89,"nameZh":6,"description":90,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":91,"categories":92,"keywords":104,"publishedAt":44},"01M6GRT346W34GHKHZAV2D772D","render-workflows","Sets up, develops, tests, and deploys Render Workflows. Covers first-time scaffolding (via CLI or manual), SDK installation (Python or TypeScript), task patterns (retries, subtasks, fan-out), local development, Dashboard deployment, and troubleshooting. Use when a user wants to set up Render Workflows for the first time, scaffold a workflow service, add or modify workflow tasks, test workflows locally, or deploy workflows to Render.","https:\u002F\u002Fgithub.com\u002Fgaos6e\u002FMyOpenclaw\u002Fblob\u002Fmain\u002F.codex-openclaw\u002F.tmp\u002Fplugins\u002Fplugins\u002Frender\u002Fskills\u002Frender-workflows\u002FSKILL.md",[93,96,99],{"categoryNo":94,"categoryName":95,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":97,"categoryName":98,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000013","分析与可视化",{"categoryNo":100,"categoryName":101,"taxonomyType":102,"taxonomyTypeDesc":103},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[105,24,106,107,108,109,110,111,112,113,33,114,115,116,31,117,118,119,120,121],"workflows","render workflows","python","workflow","test","deployment","tasks","development","SET","up","task","scaffolding","local","tests","retries","local development","manual",{"skillNo":123,"name":124,"nameZh":6,"description":125,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":126,"categories":127,"keywords":129,"publishedAt":44},"01M6GRSRWTMQA26DZ7QKF8P8JH","render-migrate-from-heroku","Migrate from Heroku to Render by reading local project files and generating equivalent Render services. Triggers: any mention of migrating from Heroku, moving off Heroku, Heroku to Render migration, or switching from Heroku. Reads Procfile, dependency files, and app config from the local repo. Optionally uses Heroku MCP to enrich with live config vars, add-on details, and dyno sizes. Uses Render MCP or Blueprint YAML to create services.","https:\u002F\u002Fgithub.com\u002Fgaos6e\u002FMyOpenclaw\u002Fblob\u002Fmain\u002F.codex-openclaw\u002F.tmp\u002Fplugins\u002Fplugins\u002Frender\u002Fskills\u002Frender-migrate-from-heroku\u002FSKILL.md",[128],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[130,24,131,132,35,133,134,135,136,137,138,139,140,117,141,142,143,144,29,145],"migrate","heroku","render migrate from heroku","mcp server","config","create","verification","server","dependency","Blueprint","files","project","switching","creation","app","enrich",{"skillNo":147,"name":148,"nameZh":6,"description":149,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":150,"categories":151,"keywords":154,"publishedAt":44},"01M6GRSK7JJ10Z7KQ7KS4NPRP5","render-deploy","Deploy applications to Render by analyzing codebases, generating render.yaml Blueprints, and providing Dashboard deeplinks. Use when the user wants to deploy, host, publish, or set up their application on Render's cloud platform.","https:\u002F\u002Fgithub.com\u002Fgaos6e\u002FMyOpenclaw\u002Fblob\u002Fmain\u002F.codex-openclaw\u002F.tmp\u002Fplugins\u002Fplugins\u002Frender\u002Fskills\u002Frender-deploy\u002FSKILL.md",[152,153],{"categoryNo":94,"categoryName":95,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[155,156,24,35,157,43,158,159,160,161,162,163,113,114,139,164,165,166,167,168],"deploy","render deploy","image","dashboard","gitlab","git","repository","publish","analyzing","bitbucket","live","host","render cli","flows",{"skillNo":170,"name":171,"nameZh":6,"description":172,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":173,"categories":174,"keywords":182,"publishedAt":44},"01M6GRSDVM9AW4V8GWB6N5HHDG","render-debug","Debug failed Render deployments by analyzing logs, metrics, and database state. Identifies errors (missing env vars, port binding, OOM, etc.) and suggests fixes. Use when deployments fail, services won't start, or users mention errors, logs, or debugging.","https:\u002F\u002Fgithub.com\u002Fgaos6e\u002FMyOpenclaw\u002Fblob\u002Fmain\u002F.codex-openclaw\u002F.tmp\u002Fplugins\u002Fplugins\u002Frender\u002Fskills\u002Frender-debug\u002FSKILL.md",[175,178,179],{"categoryNo":176,"categoryName":177,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":180,"categoryName":181,"taxonomyType":102,"taxonomyTypeDesc":103},"01JBSEEDCAT000000000000030","开发工程师",[183,184,24,35,43,185,186,40,39,187,188,163,37,33,32,189,29,190,191,192],"debug","render debug","debugging","database","env vars","start","Analyzing Logs","missing","port","errors",{"skillNo":194,"name":195,"nameZh":6,"description":196,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":197,"categories":198,"keywords":200,"publishedAt":44},"01M6GRRFJQKY22ZQRSAN91V9XR","minimal-skill","Minimal example skill for plugin-eval tests. Use when the user wants a compact demonstration of a well-structured skill.","https:\u002F\u002Fgithub.com\u002Fgaos6e\u002FMyOpenclaw\u002Fblob\u002Fmain\u002F.codex-openclaw\u002F.tmp\u002Fplugins\u002Fplugins\u002Fplugin-eval\u002Ffixtures\u002Fminimal-skill\u002FSKILL.md",[199],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[201,202,203,204,205,206,33,207,208,209,118],"minimal skill","minimal","example skill","plugin","eval","user","example","compact","structured",{"skillNo":211,"name":212,"nameZh":6,"description":213,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":214,"categories":215,"keywords":216,"publishedAt":44},"01M6GR6FVVPXS2VY5VWMYFN6AG","use-dom","Use Expo DOM components to run web code in a webview on native and as-is on web. Migrate web code to native incrementally.","https:\u002F\u002Fgithub.com\u002Fgaos6e\u002FMyOpenclaw\u002Fblob\u002Fmain\u002F.codex-openclaw\u002F.tmp\u002Fplugins\u002Fplugins\u002Fexpo\u002Fskills\u002Fuse-dom\u002FSKILL.md",[],[217,33,218,219,220,221,222,130,223,224,225],"use dom","dom","web","components","run","code","expo","as","native"]