[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71FT515AXEBB9XY4V77ZTY2":3,"skill-same:01M71FT515AXEBB9XY4V77ZTY2":120},{"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":57,"commitSha":58,"skillDirectory":59,"forksCount":60,"repositoryHtmlUrl":61,"repositoryHomepageUrl":6,"ownerHtmlUrl":62,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":63,"install":64,"resources":77},"01M71FT515AXEBB9XY4V77ZTY2","deploying-monitoring-stacks",null,"Use when deploying monitoring stacks including Prometheus, Grafana, and Datadog. Trigger with phrases like \"deploy monitoring stack\", \"setup prometheus\", \"configure grafana\", or \"install datadog agent\". Generates production-ready configurations with metric collection, visualization dashboards, and alerting rules.","JSGforever\u002Fskillguard","JSGforever","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F85541948?v=4","01M71FQD3E132VMR5F4TAYX3YS","01M71FQD4DYW0XJ4XQ4YQH75Y9",2,"MIT","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000011","运维与部署","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],"Deploying Monitoring Stacks","monitoring","read","datadog","stack","with","grafana","alerting","collection","Bash","configure","when","Rules","use","production-ready","trigger","docker","visualization","prometheus","ready","2026-11-10 10:12:30",false,"---\ndescription: Use when deploying monitoring stacks including Prometheus, Grafana, and Datadog. Trigger with phrases like \"deploy monitoring stack\", \"setup prometheus\", \"configure grafana\", or \"install datadog agent\". Generates production-ready configurations with metric collection, visualization dashboards, and alerting rules.\nallowed-tools:\n- Read\n- Write\n- Edit\n- Grep\n- Glob\n- Bash(docker:*)\n- Bash(kubectl:*)\nname: deploying-monitoring-stacks\nlicense: MIT\nversion: 1.0.0\n---\n\n## Prerequisites\n\nBefore using this skill, ensure:\n- Target infrastructure is identified (Kubernetes, Docker, bare metal)\n- Metric endpoints are accessible from monitoring platform\n- Storage backend is configured for time-series data\n- Alert notification channels are defined (email, Slack, PagerDuty)\n- Resource requirements are calculated based on scale\n\n## Instructions\n\n1. **Select Platform**: Choose Prometheus\u002FGrafana, Datadog, or hybrid approach\n2. **Deploy Collectors**: Install exporters and agents on monitored systems\n3. **Configure Scraping**: Define metric collection endpoints and intervals\n4. **Set Up Storage**: Configure retention policies and data compaction\n5. **Create Dashboards**: Build visualization panels for key metrics\n6. **Define Alerts**: Create alerting rules with appropriate thresholds\n7. **Test Monitoring**: Verify metrics flow and alert triggering\n\n## Output\n\n**Prometheus + Grafana (Kubernetes):**\n```yaml\n# {baseDir}\u002Fmonitoring\u002Fprometheus.yaml\napiVersion: v1\nkind: ConfigMap\nmetadata:\n  name: prometheus-config\ndata:\n  prometheus.yml: |\n    global:\n      scrape_interval: 15s\n      evaluation_interval: 15s\n    scrape_configs:\n      - job_name: 'kubernetes-pods'\n        kubernetes_sd_configs:\n          - role: pod\n        relabel_configs:\n          - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]\n            action: keep\n            regex: true\n---\napiVersion: apps\u002Fv1\nkind: Deployment\nmetadata:\n  name: prometheus\nspec:\n  replicas: 1\n  template:\n    spec:\n      containers:\n      - name: prometheus\n        image: prom\u002Fprometheus:latest\n        args:\n          - '--config.file=\u002Fetc\u002Fprometheus\u002Fprometheus.yml'\n          - '--storage.tsdb.retention.time=30d'\n        ports:\n        - containerPort: 9090\n```\n\n**Grafana Dashboard Configuration:**\n```json\n{\n  \"dashboard\": {\n    \"title\": \"Application Metrics\",\n    \"panels\": [\n      {\n        \"title\": \"CPU Usage\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"rate(container_cpu_usage_seconds_total[5m])\"\n          }\n        ]\n      }\n    ]\n  }\n}\n```\n\n## Error Handling\n\n**Metrics Not Appearing**\n- Error: \"No data points\"\n- Solution: Verify scrape targets are accessible and returning metrics\n\n**High Cardinality**\n- Error: \"Too many time series\"\n- Solution: Reduce label combinations or increase Prometheus resources\n\n**Alert Not Firing**\n- Error: \"Alert condition met but no notification\"\n- Solution: Check Alertmanager configuration and notification channels\n\n**Dashboard Load Failure**\n- Error: \"Failed to load dashboard\"\n- Solution: Verify Grafana datasource configuration and permissions\n\n## Resources\n\n- Prometheus documentation: https:\u002F\u002Fprometheus.io\u002Fdocs\u002F\n- Grafana documentation: https:\u002F\u002Fgrafana.com\u002Fdocs\u002F\n- Example dashboards in {baseDir}\u002Fmonitoring-examples\u002F\n","## Prerequisites\n\nBefore using this skill, ensure:\n- Target infrastructure is identified (Kubernetes, Docker, bare metal)\n- Metric endpoints are accessible from monitoring platform\n- Storage backend is configured for time-series data\n- Alert notification channels are defined (email, Slack, PagerDuty)\n- Resource requirements are calculated based on scale\n\n## Instructions\n\n1. **Select Platform**: Choose Prometheus\u002FGrafana, Datadog, or hybrid approach\n2. **Deploy Collectors**: Install exporters and agents on monitored systems\n3. **Configure Scraping**: Define metric collection endpoints and intervals\n4. **Set Up Storage**: Configure retention policies and data compaction\n5. **Create Dashboards**: Build visualization panels for key metrics\n6. **Define Alerts**: Create alerting rules with appropriate thresholds\n7. **Test Monitoring**: Verify metrics flow and alert triggering\n\n## Output\n\n**Prometheus + Grafana (Kubernetes):**\n```yaml\n# {baseDir}\u002Fmonitoring\u002Fprometheus.yaml\napiVersion: v1\nkind: ConfigMap\nmetadata:\n  name: prometheus-config\ndata:\n  prometheus.yml: |\n    global:\n      scrape_interval: 15s\n      evaluation_interval: 15s\n    scrape_configs:\n      - job_name: 'kubernetes-pods'\n        kubernetes_sd_configs:\n          - role: pod\n        relabel_configs:\n          - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]\n            action: keep\n            regex: true\n---\napiVersion: apps\u002Fv1\nkind: Deployment\nmetadata:\n  name: prometheus\nspec:\n  replicas: 1\n  template:\n    spec:\n      containers:\n      - name: prometheus\n        image: prom\u002Fprometheus:latest\n        args:\n          - '--config.file=\u002Fetc\u002Fprometheus\u002Fprometheus.yml'\n          - '--storage.tsdb.retention.time=30d'\n        ports:\n        - containerPort: 9090\n```\n\n**Grafana Dashboard Configuration:**\n```json\n{\n  \"dashboard\": {\n    \"title\": \"Application Metrics\",\n    \"panels\": [\n      {\n        \"title\": \"CPU Usage\",\n        \"type\": \"graph\",\n        \"targets\": [\n          {\n            \"expr\": \"rate(container_cpu_usage_seconds_total[5m])\"\n          }\n        ]\n      }\n    ]\n  }\n}\n```\n\n## Error Handling\n\n**Metrics Not Appearing**\n- Error: \"No data points\"\n- Solution: Verify scrape targets are accessible and returning metrics\n\n**High Cardinality**\n- Error: \"Too many time series\"\n- Solution: Reduce label combinations or increase Prometheus resources\n\n**Alert Not Firing**\n- Error: \"Alert condition met but no notification\"\n- Solution: Check Alertmanager configuration and notification channels\n\n**Dashboard Load Failure**\n- Error: \"Failed to load dashboard\"\n- Solution: Verify Grafana datasource configuration and permissions\n\n## Resources\n\n- Prometheus documentation: https:\u002F\u002Fprometheus.io\u002Fdocs\u002F\n- Grafana documentation: https:\u002F\u002Fgrafana.com\u002Fdocs\u002F\n- Example dashboards in {baseDir}\u002Fmonitoring-examples\u002F\n",{"name":5,"license":14,"version":48,"description":7,"allowed-tools":49},"1.0.0",[50,51,52,53,54,55,56],"Read","Write","Edit","Grep","Glob","Bash(docker:*)","Bash(kubectl:*)","main","f2ec4b3b9133d34eeaf9b38e4b0a97e8e5705a7f","benchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks",0,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard","https:\u002F\u002Fgithub.com\u002FJSGforever","2026-08-29 18:27:56",{"source":8,"skillName":5,"commands":65,"prompt":75,"zipAvailable":76},[66,69,72],{"tool":67,"command":68},"npx","npx skills add JSGforever\u002Fskillguard --skill deploying-monitoring-stacks",{"tool":70,"command":71},"bunx","bunx skills add JSGforever\u002Fskillguard --skill deploying-monitoring-stacks",{"tool":73,"command":74},"pnpm","pnpm dlx skills add JSGforever\u002Fskillguard --skill deploying-monitoring-stacks","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks\u002FSKILL.md",true,[78,84,88,92,96,102,108,112,116],{"path":79,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":82,"sourceHtmlUrl":83},"assets\u002Fdatadog_agent_config_template.yml","ASSET","资产文件",2632,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks\u002Fassets\u002Fdatadog_agent_config_template.yml",{"path":85,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":86,"sourceHtmlUrl":87},"assets\u002Fgrafana_dashboard_template.json",5833,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks\u002Fassets\u002Fgrafana_dashboard_template.json",{"path":89,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":90,"sourceHtmlUrl":91},"assets\u002Fprometheus_config_template.yml",2908,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks\u002Fassets\u002Fprometheus_config_template.yml",{"path":93,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":94,"sourceHtmlUrl":95},"assets\u002FREADME.md",528,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks\u002Fassets\u002FREADME.md",{"path":97,"resourceType":98,"resourceTypeDesc":99,"sizeBytes":100,"sourceHtmlUrl":101},"references\u002FREADME.md","REFERENCE","参考文档",574,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks\u002Freferences\u002FREADME.md",{"path":103,"resourceType":104,"resourceTypeDesc":105,"sizeBytes":106,"sourceHtmlUrl":107},"scripts\u002Fdeploy_datadog_agent.sh","SCRIPT","脚本",5581,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks\u002Fscripts\u002Fdeploy_datadog_agent.sh",{"path":109,"resourceType":104,"resourceTypeDesc":105,"sizeBytes":110,"sourceHtmlUrl":111},"scripts\u002Fdeploy_grafana.sh",5569,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks\u002Fscripts\u002Fdeploy_grafana.sh",{"path":113,"resourceType":104,"resourceTypeDesc":105,"sizeBytes":114,"sourceHtmlUrl":115},"scripts\u002Fdeploy_prometheus.sh",5575,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks\u002Fscripts\u002Fdeploy_prometheus.sh",{"path":117,"resourceType":104,"resourceTypeDesc":105,"sizeBytes":118,"sourceHtmlUrl":119},"scripts\u002FREADME.md",510,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--deploying-monitoring-stacks\u002Fscripts\u002FREADME.md",[121,151,166,192,214,234],{"skillNo":122,"name":123,"nameZh":6,"description":124,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":125,"licenseFileUrl":6,"sourceHtmlUrl":126,"categories":127,"keywords":131,"publishedAt":43},"01M71HY2SNXBA9Q00WZDTZQ31Z","skillguard-codex-scanner","Hybrid deterministic+LLM agent-skill security scanner. Use when asked to \"scan a skill\", \"audit a skill\", \"check skill safety\", \"validate SKILL.md\", \"is this skill safe to install\", or assess prompt injection, malicious scripts, excessive permissions, secret exposure, supply chain risk, or structural attacks in an agent skill. Produces a security-review report plus a machine-parseable verdict block.","GPL-3.0","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fsrc\u002Fskillguard\u002Fstatic_scanner\u002Fskillguard-codex-scanner\u002FSKILL.md",[128],{"categoryNo":129,"categoryName":130,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[132,133,134,135,136,137,138,139,140,141,142,143,34,144,145,146,147,148,149,150],"scanner","skillguard codex scanner","skillguard","codex","chain","skill security","security-review","review report","structural","secret","prompt injection","security scanner","review","malicious","permissions","exposure","audit","scripts","safe",{"skillNo":152,"name":153,"nameZh":6,"description":154,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":155,"categories":156,"keywords":162,"publishedAt":43},"01M71HY0SPKTT3S27BC2HPAC5M","data-exfiltrator","Analyzes data files","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Fsmoke-one-skill\u002Fasset1__cisco-ai-defense--data-exfiltrator\u002FSKILL.md",[157],{"categoryNo":158,"categoryName":159,"taxonomyType":160,"taxonomyTypeDesc":161},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[163,164,165],"data","data exfiltrator","files",{"skillNo":167,"name":168,"nameZh":6,"description":169,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":125,"licenseFileUrl":6,"sourceHtmlUrl":170,"categories":171,"keywords":172,"publishedAt":43},"01M71HXVS9EMN44BGDW215FZ72","real-time-collaboration-engine","Build real-time collaborative editing with WebSockets, OT\u002FCRDT conflict resolution, and presence awareness. Implements cursor tracking, optimistic updates, and offline sync. Use for collaborative editors, whiteboards, video editing. Activate on \"real-time collaboration\", \"WebSocket sync\", \"multiplayer editing\", \"CRDT\", \"presence awareness\". NOT for simple chat, request-response APIs, or single-user apps.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--real-time-collaboration-engine\u002FSKILL.md",[],[173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,32,188,189,190,191],"time","real time collaboration engine","real time collaboration","collaboration","engine","real time","Video","reliability","video editing","performance","conflict resolution","presence","access","apps","updates","activate","optimizer","react","streaming",{"skillNo":193,"name":194,"nameZh":6,"description":195,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":125,"licenseFileUrl":6,"sourceHtmlUrl":196,"categories":197,"keywords":201,"publishedAt":43},"01M71HXP6CTY4KFN0QVMMN0V7J","react-performance-optimizer","Optimize React apps for 60fps performance. Implements memoization, virtualization, code splitting, bundle optimization. Use for slow renders, large lists, bundle bloat. Activate on \"React performance\", \"slow render\", \"useMemo\", \"bundle size\", \"virtualization\". NOT for backend optimization, non-React frameworks, or premature optimization.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--react-performance-optimizer\u002FSKILL.md",[198],{"categoryNo":199,"categoryName":200,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000009","前端开发",[182,202,189,190,203,204,205,206,207,208,173,209,210,186,32,211,188,191,212,213],"react performance optimizer","react performance","performance optimizer","app","nextjs","expert","re","render","2025","code","router","strategies",{"skillNo":215,"name":216,"nameZh":6,"description":217,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":125,"licenseFileUrl":6,"sourceHtmlUrl":218,"categories":219,"keywords":221,"publishedAt":43},"01M71HXH7QXSQB4QTDZ7SP7YXQ","llm-streaming-response-handler","Build production LLM streaming UIs with Server-Sent Events, real-time token display, cancellation, error recovery. Handles OpenAI\u002FAnthropic\u002FClaude streaming APIs. Use for chatbots, AI assistants, real-time text generation. Activate on \"LLM streaming\", \"SSE\", \"token stream\", \"chat UI\", \"real-time AI\". NOT for batch processing, non-streaming APIs, or WebSocket bidirectional chat.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--llm-streaming-response-handler\u002FSKILL.md",[220],{"categoryNo":199,"categoryName":200,"taxonomyType":20,"taxonomyTypeDesc":21},[222,191,223,224,225,226,182,173,227,228,229,32,188,189,230,190,231,232,233,25],"llm streaming response handler","handler","error","processing","retry","chat ui","error recovery","critical","batch","display","text","server",{"skillNo":235,"name":236,"nameZh":6,"description":237,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":125,"licenseFileUrl":6,"sourceHtmlUrl":238,"categories":239,"keywords":245,"publishedAt":43},"01M71HXCB0E1YRKYW1Y8T0Y106","github-actions-pipeline-builder","Build production CI\u002FCD pipelines with GitHub Actions. Implements matrix builds, caching, deployments, testing, security scanning. Use for automated testing, deployments, release workflows. Activate on \"GitHub Actions\", \"CI\u002FCD\", \"workflow\", \"deployment pipeline\", \"automated testing\". NOT for Jenkins\u002FCircleCI, manual deployments, or non-GitHub repositories.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--github-actions-pipeline-builder\u002FSKILL.md",[240,243,244],{"categoryNo":241,"categoryName":242,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":129,"categoryName":130,"taxonomyType":20,"taxonomyTypeDesc":21},[246,247,248,249,250,251,252,180,207,253,254,255,188,213,256,25,257,258,259,260],"github actions pipeline builder","actions","github actions","pipeline builder","github","builder","pipeline","testing","ci","workflows","run","release","write","edit","git"]