[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6H6D2PRHRMS9SWK68A4TVMN":3,"skill-same:01M6H6D2PRHRMS9SWK68A4TVMN":74},{"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":53,"commitSha":54,"skillDirectory":55,"forksCount":56,"repositoryHtmlUrl":57,"repositoryHomepageUrl":6,"ownerHtmlUrl":58,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":59,"install":60,"resources":73},"01M6H6D2PRHRMS9SWK68A4TVMN","exa-load-scale",null,"Implement Exa load testing, auto-scaling, and capacity planning strategies.\nUse when running performance tests, configuring horizontal scaling,\nor planning capacity for Exa integrations.\nTrigger with phrases like \"exa load test\", \"exa scale\",\n\"exa performance test\", \"exa capacity\", \"exa k6\", \"exa benchmark\".","micsapp\u002Fmicstec-skills","micsapp","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F82411001?v=4","01M6GWCFQ6D3PV8EHNY62NN5VW","01M6GWCFVE1PA5HG0DKC7AMFJ3",4,"MIT","https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fclaude-code\u002Fplugins-plus-skills\u002Fplugins\u002Fsaas-packs\u002Fexa-pack\u002Fskills\u002Fexa-load-scale\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000008","测试与质量","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],"exa","load","exa load scale","scale","benchmark","Bash","read","write","edit","auto","testing","capacity planning","strategies","scaling","io","code","Auto-Scaling","load testing","performance test","performance","2026-11-10 10:12:30",false,"---\nname: exa-load-scale\ndescription: |\n  Implement Exa load testing, auto-scaling, and capacity planning strategies.\n  Use when running performance tests, configuring horizontal scaling,\n  or planning capacity for Exa integrations.\n  Trigger with phrases like \"exa load test\", \"exa scale\",\n  \"exa performance test\", \"exa capacity\", \"exa k6\", \"exa benchmark\".\nallowed-tools: Read, Write, Edit, Bash(k6:*), Bash(kubectl:*)\nversion: 1.0.0\nlicense: MIT\nauthor: Jeremy Longshore \u003Cjeremy@intentsolutions.io>\ncompatible-with: claude-code, codex, openclaw\n---\n# Exa Load & Scale\n\n## Overview\nLoad testing, scaling strategies, and capacity planning for Exa integrations.\n\n## Prerequisites\n- k6 load testing tool installed\n- Kubernetes cluster with HPA configured\n- Prometheus for metrics collection\n- Test environment API keys\n\n## Load Testing with k6\n\n### Basic Load Test\n```javascript\n\u002F\u002F exa-load-test.js\nimport http from 'k6\u002Fhttp';\nimport { check, sleep } from 'k6';\n\nexport const options = {\n  stages: [\n    { duration: '2m', target: 10 },   \u002F\u002F Ramp up\n    { duration: '5m', target: 10 },   \u002F\u002F Steady state\n    { duration: '2m', target: 50 },   \u002F\u002F Ramp to peak\n    { duration: '5m', target: 50 },   \u002F\u002F Stress test\n    { duration: '2m', target: 0 },    \u002F\u002F Ramp down\n  ],\n  thresholds: {\n    http_req_duration: ['p(95)\u003C500'],  # HTTP 500 Internal Server Error\n    http_req_failed: ['rate\u003C0.01'],\n  },\n};\n\nexport default function () {\n  const response = http.post(\n    'https:\u002F\u002Fapi.exa.com\u002Fv1\u002Fresource',\n    JSON.stringify({ test: true }),\n    {\n      headers: {\n        'Content-Type': 'application\u002Fjson',\n        'Authorization': `Bearer ${__ENV.EXA_API_KEY}`,\n      },\n    }\n  );\n\n  check(response, {\n    'status is 200': (r) => r.status === 200,  # HTTP 200 OK\n    'latency \u003C 500ms': (r) => r.timings.duration \u003C 500,  # HTTP 500 Internal Server Error\n  });\n\n  sleep(1);\n}\n```\n\n### Run Load Test\n```bash\n# Install k6\nbrew install k6  # macOS\n# or: sudo apt install k6  # Linux\n\n# Run test\nk6 run --env EXA_API_KEY=${EXA_API_KEY} exa-load-test.js\n\n# Run with output to InfluxDB\nk6 run --out influxdb=http:\u002F\u002Flocalhost:8086\u002Fk6 exa-load-test.js  # 8086 = configured value\n```\n\n## Scaling Patterns\n\n### Horizontal Scaling\n```yaml\n# kubernetes HPA\napiVersion: autoscaling\u002Fv2\nkind: HorizontalPodAutoscaler\nmetadata:\n  name: exa-integration-hpa\nspec:\n  scaleTargetRef:\n    apiVersion: apps\u002Fv1\n    kind: Deployment\n    name: exa-integration\n  minReplicas: 2\n  maxReplicas: 20\n  metrics:\n    - type: Resource\n      resource:\n        name: cpu\n        target:\n          type: Utilization\n          averageUtilization: 70\n    - type: Pods\n      pods:\n        metric:\n          name: exa_queue_depth\n        target:\n          type: AverageValue\n          averageValue: 100\n```\n\n### Connection Pooling\n```typescript\nimport { Pool } from 'generic-pool';\n\nconst exaPool = Pool.create({\n  create: async () => {\n    return new ExaClient({\n      apiKey: process.env.EXA_API_KEY!,\n    });\n  },\n  destroy: async (client) => {\n    await client.close();\n  },\n  max: 20,\n  min: 5,\n  idleTimeoutMillis: 30000,  # 30000: 30 seconds in ms\n});\n\nasync function withExaClient\u003CT>(\n  fn: (client: ExaClient) => Promise\u003CT>\n): Promise\u003CT> {\n  const client = await exaPool.acquire();\n  try {\n    return await fn(client);\n  } finally {\n    exaPool.release(client);\n  }\n}\n```\n\n## Capacity Planning\n\n### Metrics to Monitor\n| Metric | Warning | Critical |\n|--------|---------|----------|\n| CPU Utilization | > 70% | > 85% |\n| Memory Usage | > 75% | > 90% |\n| Request Queue Depth | > 100 | > 500 |\n| Error Rate | > 1% | > 5% |\n| P95 Latency | > 1000ms | > 3000ms |\n\n### Capacity Calculation\n```typescript\ninterface CapacityEstimate {\n  currentRPS: number;\n  maxRPS: number;\n  headroom: number;\n  scaleRecommendation: string;\n}\n\nfunction estimateExaCapacity(\n  metrics: SystemMetrics\n): CapacityEstimate {\n  const currentRPS = metrics.requestsPerSecond;\n  const avgLatency = metrics.p50Latency;\n  const cpuUtilization = metrics.cpuPercent;\n\n  \u002F\u002F Estimate max RPS based on current performance\n  const maxRPS = currentRPS \u002F (cpuUtilization \u002F 100) * 0.7; \u002F\u002F 70% target\n  const headroom = ((maxRPS - currentRPS) \u002F currentRPS) * 100;\n\n  return {\n    currentRPS,\n    maxRPS: Math.floor(maxRPS),\n    headroom: Math.round(headroom),\n    scaleRecommendation: headroom \u003C 30\n      ? 'Scale up soon'\n      : headroom \u003C 50\n      ? 'Monitor closely'\n      : 'Adequate capacity',\n  };\n}\n```\n\n## Benchmark Results Template\n\n```markdown\n## Exa Performance Benchmark\n**Date:** YYYY-MM-DD\n**Environment:** [staging\u002Fproduction]\n**SDK Version:** X.Y.Z\n\n### Test Configuration\n- Duration: 10 minutes\n- Ramp: 10 → 100 → 10 VUs\n- Target endpoint: \u002Fv1\u002Fresource\n\n### Results\n| Metric | Value |\n|--------|-------|\n| Total Requests | 50,000 |\n| Success Rate | 99.9% |\n| P50 Latency | 120ms |\n| P95 Latency | 350ms |\n| P99 Latency | 800ms |\n| Max RPS Achieved | 150 |\n\n### Observations\n- [Key finding 1]\n- [Key finding 2]\n\n### Recommendations\n- [Scaling recommendation]\n```\n\n## Instructions\n\n### Step 1: Create Load Test Script\nWrite k6 test script with appropriate thresholds.\n\n### Step 2: Configure Auto-Scaling\nSet up HPA with CPU and custom metrics.\n\n### Step 3: Run Load Test\nExecute test and collect metrics.\n\n### Step 4: Analyze and Document\nRecord results in benchmark template.\n\n## Output\n- Load test script created\n- HPA configured\n- Benchmark results documented\n- Capacity recommendations defined\n\n## Error Handling\n| Issue | Cause | Solution |\n|-------|-------|----------|\n| k6 timeout | Rate limited | Reduce RPS |\n| HPA not scaling | Wrong metrics | Verify metric name |\n| Connection refused | Pool exhausted | Increase pool size |\n| Inconsistent results | Warm-up needed | Add ramp-up phase |\n\n## Examples\n\n### Quick k6 Test\n```bash\nk6 run --vus 10 --duration 30s exa-load-test.js\n```\n\n### Check Current Capacity\n```typescript\nconst metrics = await getSystemMetrics();\nconst capacity = estimateExaCapacity(metrics);\nconsole.log('Headroom:', capacity.headroom + '%');\nconsole.log('Recommendation:', capacity.scaleRecommendation);\n```\n\n### Scale HPA Manually\n```bash\nset -euo pipefail\nkubectl scale deployment exa-integration --replicas=5\nkubectl get hpa exa-integration-hpa\n```\n\n## Resources\n- [k6 Documentation](https:\u002F\u002Fk6.io\u002Fdocs\u002F)\n- [Kubernetes HPA](https:\u002F\u002Fkubernetes.io\u002Fdocs\u002Ftasks\u002Frun-application\u002Fhorizontal-pod-autoscale\u002F)\n- [Exa Rate Limits](https:\u002F\u002Fdocs.exa.com\u002Frate-limits)\n\n## Next Steps\nFor reliability patterns, see `exa-reliability-patterns`.","# Exa Load & Scale\n\n## Overview\nLoad testing, scaling strategies, and capacity planning for Exa integrations.\n\n## Prerequisites\n- k6 load testing tool installed\n- Kubernetes cluster with HPA configured\n- Prometheus for metrics collection\n- Test environment API keys\n\n## Load Testing with k6\n\n### Basic Load Test\n```javascript\n\u002F\u002F exa-load-test.js\nimport http from 'k6\u002Fhttp';\nimport { check, sleep } from 'k6';\n\nexport const options = {\n  stages: [\n    { duration: '2m', target: 10 },   \u002F\u002F Ramp up\n    { duration: '5m', target: 10 },   \u002F\u002F Steady state\n    { duration: '2m', target: 50 },   \u002F\u002F Ramp to peak\n    { duration: '5m', target: 50 },   \u002F\u002F Stress test\n    { duration: '2m', target: 0 },    \u002F\u002F Ramp down\n  ],\n  thresholds: {\n    http_req_duration: ['p(95)\u003C500'],  # HTTP 500 Internal Server Error\n    http_req_failed: ['rate\u003C0.01'],\n  },\n};\n\nexport default function () {\n  const response = http.post(\n    'https:\u002F\u002Fapi.exa.com\u002Fv1\u002Fresource',\n    JSON.stringify({ test: true }),\n    {\n      headers: {\n        'Content-Type': 'application\u002Fjson',\n        'Authorization': `Bearer ${__ENV.EXA_API_KEY}`,\n      },\n    }\n  );\n\n  check(response, {\n    'status is 200': (r) => r.status === 200,  # HTTP 200 OK\n    'latency \u003C 500ms': (r) => r.timings.duration \u003C 500,  # HTTP 500 Internal Server Error\n  });\n\n  sleep(1);\n}\n```\n\n### Run Load Test\n```bash\n# Install k6\nbrew install k6  # macOS\n# or: sudo apt install k6  # Linux\n\n# Run test\nk6 run --env EXA_API_KEY=${EXA_API_KEY} exa-load-test.js\n\n# Run with output to InfluxDB\nk6 run --out influxdb=http:\u002F\u002Flocalhost:8086\u002Fk6 exa-load-test.js  # 8086 = configured value\n```\n\n## Scaling Patterns\n\n### Horizontal Scaling\n```yaml\n# kubernetes HPA\napiVersion: autoscaling\u002Fv2\nkind: HorizontalPodAutoscaler\nmetadata:\n  name: exa-integration-hpa\nspec:\n  scaleTargetRef:\n    apiVersion: apps\u002Fv1\n    kind: Deployment\n    name: exa-integration\n  minReplicas: 2\n  maxReplicas: 20\n  metrics:\n    - type: Resource\n      resource:\n        name: cpu\n        target:\n          type: Utilization\n          averageUtilization: 70\n    - type: Pods\n      pods:\n        metric:\n          name: exa_queue_depth\n        target:\n          type: AverageValue\n          averageValue: 100\n```\n\n### Connection Pooling\n```typescript\nimport { Pool } from 'generic-pool';\n\nconst exaPool = Pool.create({\n  create: async () => {\n    return new ExaClient({\n      apiKey: process.env.EXA_API_KEY!,\n    });\n  },\n  destroy: async (client) => {\n    await client.close();\n  },\n  max: 20,\n  min: 5,\n  idleTimeoutMillis: 30000,  # 30000: 30 seconds in ms\n});\n\nasync function withExaClient\u003CT>(\n  fn: (client: ExaClient) => Promise\u003CT>\n): Promise\u003CT> {\n  const client = await exaPool.acquire();\n  try {\n    return await fn(client);\n  } finally {\n    exaPool.release(client);\n  }\n}\n```\n\n## Capacity Planning\n\n### Metrics to Monitor\n| Metric | Warning | Critical |\n|--------|---------|----------|\n| CPU Utilization | > 70% | > 85% |\n| Memory Usage | > 75% | > 90% |\n| Request Queue Depth | > 100 | > 500 |\n| Error Rate | > 1% | > 5% |\n| P95 Latency | > 1000ms | > 3000ms |\n\n### Capacity Calculation\n```typescript\ninterface CapacityEstimate {\n  currentRPS: number;\n  maxRPS: number;\n  headroom: number;\n  scaleRecommendation: string;\n}\n\nfunction estimateExaCapacity(\n  metrics: SystemMetrics\n): CapacityEstimate {\n  const currentRPS = metrics.requestsPerSecond;\n  const avgLatency = metrics.p50Latency;\n  const cpuUtilization = metrics.cpuPercent;\n\n  \u002F\u002F Estimate max RPS based on current performance\n  const maxRPS = currentRPS \u002F (cpuUtilization \u002F 100) * 0.7; \u002F\u002F 70% target\n  const headroom = ((maxRPS - currentRPS) \u002F currentRPS) * 100;\n\n  return {\n    currentRPS,\n    maxRPS: Math.floor(maxRPS),\n    headroom: Math.round(headroom),\n    scaleRecommendation: headroom \u003C 30\n      ? 'Scale up soon'\n      : headroom \u003C 50\n      ? 'Monitor closely'\n      : 'Adequate capacity',\n  };\n}\n```\n\n## Benchmark Results Template\n\n```markdown\n## Exa Performance Benchmark\n**Date:** YYYY-MM-DD\n**Environment:** [staging\u002Fproduction]\n**SDK Version:** X.Y.Z\n\n### Test Configuration\n- Duration: 10 minutes\n- Ramp: 10 → 100 → 10 VUs\n- Target endpoint: \u002Fv1\u002Fresource\n\n### Results\n| Metric | Value |\n|--------|-------|\n| Total Requests | 50,000 |\n| Success Rate | 99.9% |\n| P50 Latency | 120ms |\n| P95 Latency | 350ms |\n| P99 Latency | 800ms |\n| Max RPS Achieved | 150 |\n\n### Observations\n- [Key finding 1]\n- [Key finding 2]\n\n### Recommendations\n- [Scaling recommendation]\n```\n\n## Instructions\n\n### Step 1: Create Load Test Script\nWrite k6 test script with appropriate thresholds.\n\n### Step 2: Configure Auto-Scaling\nSet up HPA with CPU and custom metrics.\n\n### Step 3: Run Load Test\nExecute test and collect metrics.\n\n### Step 4: Analyze and Document\nRecord results in benchmark template.\n\n## Output\n- Load test script created\n- HPA configured\n- Benchmark results documented\n- Capacity recommendations defined\n\n## Error Handling\n| Issue | Cause | Solution |\n|-------|-------|----------|\n| k6 timeout | Rate limited | Reduce RPS |\n| HPA not scaling | Wrong metrics | Verify metric name |\n| Connection refused | Pool exhausted | Increase pool size |\n| Inconsistent results | Warm-up needed | Add ramp-up phase |\n\n## Examples\n\n### Quick k6 Test\n```bash\nk6 run --vus 10 --duration 30s exa-load-test.js\n```\n\n### Check Current Capacity\n```typescript\nconst metrics = await getSystemMetrics();\nconst capacity = estimateExaCapacity(metrics);\nconsole.log('Headroom:', capacity.headroom + '%');\nconsole.log('Recommendation:', capacity.scaleRecommendation);\n```\n\n### Scale HPA Manually\n```bash\nset -euo pipefail\nkubectl scale deployment exa-integration --replicas=5\nkubectl get hpa exa-integration-hpa\n```\n\n## Resources\n- [k6 Documentation](https:\u002F\u002Fk6.io\u002Fdocs\u002F)\n- [Kubernetes HPA](https:\u002F\u002Fkubernetes.io\u002Fdocs\u002Ftasks\u002Frun-application\u002Fhorizontal-pod-autoscale\u002F)\n- [Exa Rate Limits](https:\u002F\u002Fdocs.exa.com\u002Frate-limits)\n\n## Next Steps\nFor reliability patterns, see `exa-reliability-patterns`.",{"name":5,"author":48,"license":14,"version":49,"description":50,"allowed-tools":51,"compatible-with":52},"Jeremy Longshore \u003Cjeremy@intentsolutions.io>","1.0.0","Implement Exa load testing, auto-scaling, and capacity planning strategies.\nUse when running performance tests, configuring horizontal scaling,\nor planning capacity for Exa integrations.\nTrigger with phrases like \"exa load test\", \"exa scale\",\n\"exa performance test\", \"exa capacity\", \"exa k6\", \"exa benchmark\".\n","Read, Write, Edit, Bash(k6:*), Bash(kubectl:*)","claude-code, codex, openclaw","master","3f5d983eb4ef375b749adcd6b07ec03bd82ae8a8","claude-code\u002Fplugins-plus-skills\u002Fplugins\u002Fsaas-packs\u002Fexa-pack\u002Fskills\u002Fexa-load-scale",0,"https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills","https:\u002F\u002Fgithub.com\u002Fmicsapp","2026-03-20 11:24:18",{"source":8,"skillName":5,"commands":61,"prompt":71,"zipAvailable":72},[62,65,68],{"tool":63,"command":64},"npx","npx skills add micsapp\u002Fmicstec-skills --skill exa-load-scale",{"tool":66,"command":67},"bunx","bunx skills add micsapp\u002Fmicstec-skills --skill exa-load-scale",{"tool":69,"command":70},"pnpm","pnpm dlx skills add micsapp\u002Fmicstec-skills --skill exa-load-scale","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fclaude-code\u002Fplugins-plus-skills\u002Fplugins\u002Fsaas-packs\u002Fexa-pack\u002Fskills\u002Fexa-load-scale\u002FSKILL.md",true,[],[75,109,138,159,178,202],{"skillNo":76,"name":77,"nameZh":6,"description":78,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":79,"categories":80,"keywords":89,"publishedAt":43},"01M6HBTJ02FXBFG9NYEHHYAP52","azure-apim-architecture","Analyzes and explains Azure API Management architecture decisions for enterprise API marketplace implementations using VNet Internal mode, Front Door, hybrid authentication, and multi-environment strategies. 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Use when performing security audits, pre-deployment validation, or compliance reviews.","https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fcopilot-cli\u002Fcopilot-agent-skills\u002F.github\u002Fskills\u002Fapi-security-review\u002FSKILL.md",[165,166],{"categoryNo":82,"categoryName":83,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":85,"categoryName":86,"taxonomyType":87,"taxonomyTypeDesc":88},[168,149,169,99,153,170,91,124,27,171,172,173,100,174,106,175,176,177,107,108],"review","security review","api security review","verification","owasp","owasp-api","alignment","azure security","reviews","top",{"skillNo":179,"name":180,"nameZh":6,"description":181,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":182,"categories":183,"keywords":184,"publishedAt":43},"01M6HBSRW4PDFE6K4F8JYPZQ05","jira-cli","Interact with Jira from the command line to create, list, view, edit, and transition issues, manage sprints and epics, and perform common Jira workflows. Use when the user asks about Jira tasks, tickets, issues, sprints, or needs to manage project work items.","https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fcopilot-cli\u002Fawesome-copilot-agents\u002Fskills\u002Fjira-cli\u002FSKILL.md",[],[185,186,187,126,188,189,190,191,99,192,193,194,31,195,196,197,198,199,200,201],"cli","jira","jira cli","init","tasks","create","issues","common","work","command","list","view","project","project work","token","line","sprints",{"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":14,"licenseFileUrl":6,"sourceHtmlUrl":206,"categories":207,"keywords":208,"publishedAt":43},"01M6HBSNS3JHMW603G47TWE31H","calculator","Performs arbitrary-precision arithmetic calculations including addition, subtraction, multiplication, division, and exponents. Use when the user asks to calculate, compute, or evaluate math expressions, or when precise decimal arithmetic is needed to avoid floating-point errors.","https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fcopilot-cli\u002Fawesome-copilot-agents\u002Fskills\u002Fcalculator\u002FSKILL.md",[],[204,209,210,211,212,213,214,151,215,216],"npm","js","calculate","node","math","user","compute","errors"]