[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M754VF0TFGAAPGKDRZAMV353":3,"skill-same:01M754VF0TFGAAPGKDRZAMV353":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},"01M754VF0TFGAAPGKDRZAMV353","openevidence-sdk-patterns",null,"OpenEvidence SDK patterns and best practices for clinical AI integration.\nUse when implementing advanced SDK features, optimizing API usage,\nor following clinical decision support best practices.\nTrigger with phrases like \"openevidence patterns\", \"openevidence best practices\",\n\"openevidence sdk\", \"clinical ai patterns\".","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-sdk-patterns\u002FSKILL.md",[],[],"2026-11-12 13:55:43",false,"---\nname: openevidence-sdk-patterns\ndescription: |\n  OpenEvidence SDK patterns and best practices for clinical AI integration.\n  Use when implementing advanced SDK features, optimizing API usage,\n  or following clinical decision support best practices.\n  Trigger with phrases like \"openevidence patterns\", \"openevidence best practices\",\n  \"openevidence sdk\", \"clinical ai patterns\".\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 SDK Patterns\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\nBest practices and design patterns for building production clinical decision support with OpenEvidence. Covers client singleton, typed queries, query builder, response transformer, and caching strategies.\n\n## Prerequisites\n- Completed `openevidence-install-auth` setup\n- Understanding of async\u002Fawait patterns\n- Familiarity with clinical workflows\n\n## Instructions\n\n### Step 1: Client Singleton with DI\nCreate `OpenEvidenceClientFactory` with `configure()`, `getClient()`, and `setClient()` (for testing). Ensures single client instance across the application.\n\n### Step 2: Define Typed Clinical Queries\nCreate TypeScript types for `ClinicalSpecialty` (10 specialties), `QueryUrgency` (stat\u002Furgent\u002Froutine\u002Fresearch), `ClinicalContext` (specialty, urgency, patient demographics, conditions, medications), and `QueryOptions`.\n\n### Step 3: Implement Query Builder\nBuild fluent `ClinicalQueryBuilder` with `.question()`, `.specialty()`, `.urgency()`, `.withPatient()`, `.withConditions()`, `.withMedications()`, `.maxCitations()`, `.includeGuidelines()`, and `.build()` with validation.\n\n### Step 4: Create Response Transformer\nTransform raw API responses into `FormattedClinicalAnswer` with summary, detailed answer, key points, evidence with strength ratings (high for NEJM\u002FJAMA\u002FLancet, moderate for recent, low otherwise), and confidence level.\n\n### Step 5: Implement Caching Layer\nBuild `ClinicalQueryCache` with SHA-256 key generation, configurable TTL (1 hour default for clinical data), and invalidation support.\n\n## Output\n- Client singleton factory with dependency injection\n- Typed clinical query interfaces\n- Fluent query builder with validation\n- Response transformer with evidence strength ratings\n- In-memory caching with TTL management\n\n## Error Handling\n| Pattern | Use Case | Benefit |\n|---------|----------|---------|\n| Singleton | Single client instance | Memory efficiency, connection reuse |\n| Builder | Complex queries | Type safety, validation, readability |\n| Transformer | Response normalization | Consistent UI layer, evidence grading |\n| Cache | Repeated queries | Reduced API calls, lower latency |\n\n## Examples\n\n### Query Builder Usage\n```typescript\nconst query = new ClinicalQueryBuilder()\n  .question('Recommended statin dosing for secondary prevention?')\n  .specialty('cardiology')\n  .urgency('routine')\n  .withPatient(65, 'male')\n  .withConditions(['prior MI', 'hyperlipidemia'])\n  .includeGuidelines()\n  .build();\n```\n\nSee [detailed implementation](${CLAUDE_SKILL_DIR}\u002Freferences\u002Fimplementation.md) for advanced patterns.\n\n## Resources\n- [OpenEvidence API Reference](https:\u002F\u002Fdocs.openevidence.com\u002F)\n- [TypeScript Design Patterns](https:\u002F\u002Frefactoring.guru\u002Fdesign-patterns\u002Ftypescript)","# OpenEvidence SDK Patterns\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\nBest practices and design patterns for building production clinical decision support with OpenEvidence. Covers client singleton, typed queries, query builder, response transformer, and caching strategies.\n\n## Prerequisites\n- Completed `openevidence-install-auth` setup\n- Understanding of async\u002Fawait patterns\n- Familiarity with clinical workflows\n\n## Instructions\n\n### Step 1: Client Singleton with DI\nCreate `OpenEvidenceClientFactory` with `configure()`, `getClient()`, and `setClient()` (for testing). Ensures single client instance across the application.\n\n### Step 2: Define Typed Clinical Queries\nCreate TypeScript types for `ClinicalSpecialty` (10 specialties), `QueryUrgency` (stat\u002Furgent\u002Froutine\u002Fresearch), `ClinicalContext` (specialty, urgency, patient demographics, conditions, medications), and `QueryOptions`.\n\n### Step 3: Implement Query Builder\nBuild fluent `ClinicalQueryBuilder` with `.question()`, `.specialty()`, `.urgency()`, `.withPatient()`, `.withConditions()`, `.withMedications()`, `.maxCitations()`, `.includeGuidelines()`, and `.build()` with validation.\n\n### Step 4: Create Response Transformer\nTransform raw API responses into `FormattedClinicalAnswer` with summary, detailed answer, key points, evidence with strength ratings (high for NEJM\u002FJAMA\u002FLancet, moderate for recent, low otherwise), and confidence level.\n\n### Step 5: Implement Caching Layer\nBuild `ClinicalQueryCache` with SHA-256 key generation, configurable TTL (1 hour default for clinical data), and invalidation support.\n\n## Output\n- Client singleton factory with dependency injection\n- Typed clinical query interfaces\n- Fluent query builder with validation\n- Response transformer with evidence strength ratings\n- In-memory caching with TTL management\n\n## Error Handling\n| Pattern | Use Case | Benefit |\n|---------|----------|---------|\n| Singleton | Single client instance | Memory efficiency, connection reuse |\n| Builder | Complex queries | Type safety, validation, readability |\n| Transformer | Response normalization | Consistent UI layer, evidence grading |\n| Cache | Repeated queries | Reduced API calls, lower latency |\n\n## Examples\n\n### Query Builder Usage\n```typescript\nconst query = new ClinicalQueryBuilder()\n  .question('Recommended statin dosing for secondary prevention?')\n  .specialty('cardiology')\n  .urgency('routine')\n  .withPatient(65, 'male')\n  .withConditions(['prior MI', 'hyperlipidemia'])\n  .includeGuidelines()\n  .build();\n```\n\nSee [detailed implementation](${CLAUDE_SKILL_DIR}\u002Freferences\u002Fimplementation.md) for advanced patterns.\n\n## Resources\n- [OpenEvidence API Reference](https:\u002F\u002Fdocs.openevidence.com\u002F)\n- [TypeScript Design Patterns](https:\u002F\u002Frefactoring.guru\u002Fdesign-patterns\u002Ftypescript)",{"name":5,"author":24,"license":15,"version":25,"description":26,"allowed-tools":27,"compatible-with":28},"Jeremy Longshore \u003Cjeremy@intentsolutions.io>","1.0.0","OpenEvidence SDK patterns and best practices for clinical AI integration.\nUse when implementing advanced SDK features, optimizing API usage,\nor following clinical decision support best practices.\nTrigger with phrases like \"openevidence patterns\", \"openevidence best practices\",\n\"openevidence sdk\", \"clinical ai patterns\".\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-sdk-patterns",{"tool":41,"command":42},"bunx","bunx skills add SamuelChien\u002Fmega-skills-collection --skill openevidence-sdk-patterns",{"tool":44,"command":45},"pnpm","pnpm dlx skills add SamuelChien\u002Fmega-skills-collection --skill openevidence-sdk-patterns","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection\u002Fblob\u002Fmain\u002Fopenevidence-sdk-patterns\u002FSKILL.md",true,[49],{"path":50,"resourceType":51,"resourceTypeDesc":52,"sizeBytes":53,"sourceHtmlUrl":54},"references\u002Fimplementation.md","REFERENCE","参考文档",2542,"https:\u002F\u002Fgithub.com\u002FSamuelChien\u002Fmega-skills-collection\u002Fblob\u002Fmain\u002Fopenevidence-sdk-patterns\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",[],[]]