[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M754TYFJB96RXVQ91CMFR0FH":3,"skill-same:01M754TYFJB96RXVQ91CMFR0FH":55},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":29,"commitSha":30,"skillDirectory":5,"forksCount":14,"repositoryHtmlUrl":31,"repositoryHomepageUrl":6,"ownerHtmlUrl":32,"ownerBlogUrl":33,"ownerDescription":6,"updatedAt":34,"install":35,"resources":48},"01M754TYFJB96RXVQ91CMFR0FH","openevidence-performance-tuning",null,"Optimize OpenEvidence clinical query performance and response times.\nUse when improving latency, optimizing query efficiency,\nor tuning caching for clinical AI applications.\nTrigger with phrases like \"openevidence performance\", \"openevidence slow\",\n\"optimize openevidence\", \"openevidence latency\", \"speed up clinical queries\".","SamuelChien\u002Fmega-skills-collection","SamuelChien","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F4652114?v=4","01M74KK34WVHA0P5ZYSJRDDFMG","Samuel Chien","01M74KK35FQN1N9VZ9EPTH3P2S",0,"MIT","https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection\u002Fblob\u002Fmain\u002Fopenevidence-performance-tuning\u002FSKILL.md",[],[],"2026-11-12 13:55:43",false,"---\nname: openevidence-performance-tuning\ndescription: |\n  Optimize OpenEvidence clinical query performance and response times.\n  Use when improving latency, optimizing query efficiency,\n  or tuning caching for clinical AI applications.\n  Trigger with phrases like \"openevidence performance\", \"openevidence slow\",\n  \"optimize openevidence\", \"openevidence latency\", \"speed up clinical queries\".\nallowed-tools: Read, Write, Edit\nversion: 1.0.0\nlicense: MIT\nauthor: Jeremy Longshore \u003Cjeremy@intentsolutions.io>\ncompatible-with: claude-code, codex, openclaw\n---\n# OpenEvidence Performance Tuning\n\n## Table of Contents\n- [Overview](#overview)\n- [Prerequisites](#prerequisites)\n- [Instructions](#instructions)\n- [Output](#output)\n- [Error Handling](#error-handling)\n- [Examples](#examples)\n- [Resources](#resources)\n\n## Overview\nOptimize OpenEvidence clinical query performance for point-of-care response times. Covers query optimization, intelligent caching with TTL management, connection pooling, request batching, and performance monitoring.\n\n## Prerequisites\n- OpenEvidence integration running\n- Monitoring configured (see `openevidence-observability`)\n- Redis for caching\n- Access to performance metrics\n\n## Performance Targets\n\n| Metric | Target | Critical |\n|--------|--------|----------|\n| Clinical Query P50 | \u003C 3s | > 10s |\n| Clinical Query P95 | \u003C 8s | > 15s |\n| Cache Hit Rate | > 70% | \u003C 50% |\n| DeepConsult Start | \u003C 5s | > 15s |\n\n## Instructions\n\n### Step 1: Optimize Query Construction\nRemove filler words from questions, limit context to top 5 conditions and 10 medications, set `maxCitations: 5` for faster responses.\n\n### Step 2: Implement Intelligent Caching\nBuild `ClinicalQueryCache` with SHA-256 key generation. Use dynamic TTL: 5min for stat\u002Furgent, 24hr for pharmacokinetics\u002Fmechanisms, 1hr for guidelines, default for others.\n\n### Step 3: Enable Connection Pooling\nConfigure HTTPS agent with `keepAlive: true`, 10 max sockets, 5 max free sockets. Pre-warm connections on startup.\n\n### Step 4: Set Up Request Batching\nUse DataLoader to batch concurrent queries (max 5 per batch, 50ms scheduling window) within rate limits.\n\n### Step 5: Add Performance Monitoring\nInstrument queries with Prometheus histograms for latency by specialty\u002Furgency\u002Fcached, plus cache hit\u002Fmiss counters.\n\n## Output\n- Optimized query construction\n- Intelligent caching with dynamic TTL management\n- Connection pooling with keep-alive\n- Request batching via DataLoader\n- Performance metrics and monitoring\n\n## Error Handling\n| Performance Issue | Detection | Resolution |\n|-------------------|-----------|------------|\n| High P95 latency | Metrics alert | Check cache hit rate, optimize queries |\n| Low cache hit rate | \u003C 50% hits | Review TTL strategy, check key normalization |\n| Connection timeouts | Timeout errors | Check keep-alive config, increase pool size |\n| Memory pressure | Redis alerts | Implement LRU eviction, reduce TTLs |\n\n## Examples\n\n### Cache TTL Strategy\n```\nStat\u002Furgent queries:      5 minutes\nPharmacokinetics\u002Fmechanisms: 24 hours\nTreatment guidelines:     1 hour\nDefault clinical queries: configurable (default 1hr)\n```\n\nSee [detailed implementation](${CLAUDE_SKILL_DIR}\u002Freferences\u002Fimplementation.md) for advanced patterns.\n\n## Resources\n- [Redis Caching Best Practices](https:\u002F\u002Fredis.io\u002Fdocs\u002Fmanual\u002Fclient-side-caching\u002F)\n- [DataLoader Documentation](https:\u002F\u002Fgithub.com\u002Fgraphql\u002Fdataloader)","# OpenEvidence Performance Tuning\n\n## Table of Contents\n- [Overview](#overview)\n- [Prerequisites](#prerequisites)\n- [Instructions](#instructions)\n- [Output](#output)\n- [Error Handling](#error-handling)\n- [Examples](#examples)\n- [Resources](#resources)\n\n## Overview\nOptimize OpenEvidence clinical query performance for point-of-care response times. Covers query optimization, intelligent caching with TTL management, connection pooling, request batching, and performance monitoring.\n\n## Prerequisites\n- OpenEvidence integration running\n- Monitoring configured (see `openevidence-observability`)\n- Redis for caching\n- Access to performance metrics\n\n## Performance Targets\n\n| Metric | Target | Critical |\n|--------|--------|----------|\n| Clinical Query P50 | \u003C 3s | > 10s |\n| Clinical Query P95 | \u003C 8s | > 15s |\n| Cache Hit Rate | > 70% | \u003C 50% |\n| DeepConsult Start | \u003C 5s | > 15s |\n\n## Instructions\n\n### Step 1: Optimize Query Construction\nRemove filler words from questions, limit context to top 5 conditions and 10 medications, set `maxCitations: 5` for faster responses.\n\n### Step 2: Implement Intelligent Caching\nBuild `ClinicalQueryCache` with SHA-256 key generation. Use dynamic TTL: 5min for stat\u002Furgent, 24hr for pharmacokinetics\u002Fmechanisms, 1hr for guidelines, default for others.\n\n### Step 3: Enable Connection Pooling\nConfigure HTTPS agent with `keepAlive: true`, 10 max sockets, 5 max free sockets. Pre-warm connections on startup.\n\n### Step 4: Set Up Request Batching\nUse DataLoader to batch concurrent queries (max 5 per batch, 50ms scheduling window) within rate limits.\n\n### Step 5: Add Performance Monitoring\nInstrument queries with Prometheus histograms for latency by specialty\u002Furgency\u002Fcached, plus cache hit\u002Fmiss counters.\n\n## Output\n- Optimized query construction\n- Intelligent caching with dynamic TTL management\n- Connection pooling with keep-alive\n- Request batching via DataLoader\n- Performance metrics and monitoring\n\n## Error Handling\n| Performance Issue | Detection | Resolution |\n|-------------------|-----------|------------|\n| High P95 latency | Metrics alert | Check cache hit rate, optimize queries |\n| Low cache hit rate | \u003C 50% hits | Review TTL strategy, check key normalization |\n| Connection timeouts | Timeout errors | Check keep-alive config, increase pool size |\n| Memory pressure | Redis alerts | Implement LRU eviction, reduce TTLs |\n\n## Examples\n\n### Cache TTL Strategy\n```\nStat\u002Furgent queries:      5 minutes\nPharmacokinetics\u002Fmechanisms: 24 hours\nTreatment guidelines:     1 hour\nDefault clinical queries: configurable (default 1hr)\n```\n\nSee [detailed implementation](${CLAUDE_SKILL_DIR}\u002Freferences\u002Fimplementation.md) for advanced patterns.\n\n## Resources\n- [Redis Caching Best Practices](https:\u002F\u002Fredis.io\u002Fdocs\u002Fmanual\u002Fclient-side-caching\u002F)\n- [DataLoader Documentation](https:\u002F\u002Fgithub.com\u002Fgraphql\u002Fdataloader)",{"name":5,"author":24,"license":15,"version":25,"description":26,"allowed-tools":27,"compatible-with":28},"Jeremy Longshore \u003Cjeremy@intentsolutions.io>","1.0.0","Optimize OpenEvidence clinical query performance and response times.\nUse when improving latency, optimizing query efficiency,\nor tuning caching for clinical AI applications.\nTrigger with phrases like \"openevidence performance\", \"openevidence slow\",\n\"optimize openevidence\", \"openevidence latency\", \"speed up clinical queries\".\n","Read, Write, Edit","claude-code, codex, openclaw","main","c2b1fdccc779e99ac814e55fb69ca8d71215dd0f","https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection","https:\u002F\u002Fgithub.com\u002FSamuelChien","http:\u002F\u002Fsamuelchien.com\u002F","2026-05-26 08:27:14",{"source":8,"skillName":5,"commands":36,"prompt":46,"zipAvailable":47},[37,40,43],{"tool":38,"command":39},"npx","npx skills add SamuelChien\u002Fmega-skills-collection --skill openevidence-performance-tuning",{"tool":41,"command":42},"bunx","bunx skills add SamuelChien\u002Fmega-skills-collection --skill openevidence-performance-tuning",{"tool":44,"command":45},"pnpm","pnpm dlx skills add SamuelChien\u002Fmega-skills-collection --skill openevidence-performance-tuning","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection\u002Fblob\u002Fmain\u002Fopenevidence-performance-tuning\u002FSKILL.md",true,[49],{"path":50,"resourceType":51,"resourceTypeDesc":52,"sizeBytes":53,"sourceHtmlUrl":54},"references\u002Fimplementation.md","REFERENCE","参考文档",2486,"https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection\u002Fblob\u002Fmain\u002Fopenevidence-performance-tuning\u002Freferences\u002Fimplementation.md",[56,63,70,77,84,92],{"skillNo":57,"name":58,"nameZh":6,"description":59,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":60,"categories":61,"keywords":62,"publishedAt":19},"01M76R4WZQZAXGGXMQCA0FZ716","zustand-store-ts","Create Zustand stores with TypeScript, subscribeWithSelector middleware, and proper state\u002Faction separation. Use when building React state management, creating global stores, or implementing reactive state patterns with Zustand.","https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection\u002Fblob\u002Fmain\u002Fzustand-store-ts\u002FSKILL.md",[],[],{"skillNo":64,"name":65,"nameZh":6,"description":66,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":67,"categories":68,"keywords":69,"publishedAt":19},"01M76R4T9KENDH7FENGZQHBW4G","zustand-store-creator","Zustand Store Creator - Auto-activating skill for Frontend Development.\nTriggers on: zustand store creator, zustand store creator\nPart of the Frontend Development skill category.","https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection\u002Fblob\u002Fmain\u002Fzustand-store-creator\u002FSKILL.md",[],[],{"skillNo":71,"name":72,"nameZh":6,"description":73,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":74,"categories":75,"keywords":76,"publishedAt":19},"01M76R3YWN84B7SANJ52X799ZE","zero-trust-config-helper","Zero Trust Config Helper - Auto-activating skill for Security Advanced.\nTriggers on: zero trust config helper, zero trust config helper\nPart of the Security Advanced skill category.","https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection\u002Fblob\u002Fmain\u002Fzero-trust-config-helper\u002FSKILL.md",[],[],{"skillNo":78,"name":79,"nameZh":6,"description":80,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":81,"categories":82,"keywords":83,"publishedAt":19},"01M76R3HNSV2AEYSKHM915GJ58","zapier-integration-helper","Zapier Integration Helper - Auto-activating skill for Business Automation.\nTriggers on: zapier integration helper, zapier integration helper\nPart of the Business Automation skill category.","https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection\u002Fblob\u002Fmain\u002Fzapier-integration-helper\u002FSKILL.md",[],[],{"skillNo":85,"name":86,"nameZh":6,"description":87,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":88,"licenseFileUrl":6,"sourceHtmlUrl":89,"categories":90,"keywords":91,"publishedAt":19},"01M76R3DJSKAT4FA7DV4BF3GCE","zai-cli","Execute z.AI CLI providing vision, search, reader, and GitHub exploration via CLI and MCP.\nUse when user needs image\u002Fvideo analysis, OCR, UI-to-code conversion, error diagnosis,\nreal-time web search, web page to markdown extraction, or GitHub code exploration.\nTrigger with phrases like \"analyze this image\", \"search the web for\", \"read this page\",\n\"explore this repo\", or \"use zai\". Requires Z_AI_API_KEY.","Apache-2.0","https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection\u002Fblob\u002Fmain\u002Fzai-cli\u002FSKILL.md",[],[],{"skillNo":93,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":96,"categories":97,"keywords":98,"publishedAt":19},"01M76R2KAM699XE9AJVAWE4H2E","yt-research","Research competitor YouTube channels, niches, and trending topics for your content strategy.\nUse this skill whenever the user says \"research channels\", \"analyze competitors\", \"find trending topics\",\n\"niche analysis\", \"competitive research\", \"what are other creators doing\", \"scrape YouTube channels\",\nor wants to understand the competitive landscape for a specific tool or topic area. Use when working with yt research. Trigger with 'yt', 'research'.","https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection\u002Fblob\u002Fmain\u002Fyt-research\u002FSKILL.md",[],[]]