[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6H94KXB9JTRZPSDGR9B3MPZ":3,"skill-same:01M6H94KXB9JTRZPSDGR9B3MPZ":83},{"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":17,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":6,"ownerHtmlUrl":53,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":54,"install":55,"resources":68},"01M6H94KXB9JTRZPSDGR9B3MPZ","supabase-performance-tuning",null,"Optimize Supabase API performance with caching, batching, and connection pooling.\nUse when experiencing slow API responses, implementing caching strategies,\nor optimizing request throughput for Supabase integrations.\nTrigger with phrases like \"supabase performance\", \"optimize supabase\",\n\"supabase latency\", \"supabase caching\", \"supabase slow\", \"supabase batch\".","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\u002Fsupabase-pack\u002Fskills\u002Fsupabase-performance-tuning\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"supabase","tuning","supabase performance tuning","performance tuning","performance","strategies","for","implementing","with","trigger","io","latency","caching strategies","caching","optimize","use","integrations","api","batch","code","2026-11-10 10:12:30",false,"---\nname: supabase-performance-tuning\ndescription: |\n  Optimize Supabase API performance with caching, batching, and connection pooling.\n  Use when experiencing slow API responses, implementing caching strategies,\n  or optimizing request throughput for Supabase integrations.\n  Trigger with phrases like \"supabase performance\", \"optimize supabase\",\n  \"supabase latency\", \"supabase caching\", \"supabase slow\", \"supabase batch\".\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# Supabase Performance Tuning\n\n## Prerequisites\n- Supabase SDK installed\n- Understanding of async patterns\n- Redis or in-memory cache available (optional)\n- Performance monitoring in place\n\n## Instructions\n\nPerformance tuning a Supabase integration should follow a measurement-first discipline. Applying optimizations without a baseline makes it impossible to quantify impact, and premature optimization often targets the wrong bottleneck. Start with profiling, then apply targeted improvements in order of expected impact.\n\n### Step 1: Establish Baseline\nMeasure current latency for critical Supabase operations using application-level instrumentation or the Supabase query editor's explain analyze output. Record P50, P95, and P99 latencies for each operation under representative load. Identify the three to five slowest operations as your primary targets.\n\n### Step 2: Implement Caching\nAdd response caching for frequently accessed data that changes infrequently. Use TTL-based invalidation for data that has a predictable freshness requirement and event-driven invalidation for data that must be immediately consistent after writes. An LRU cache in memory is appropriate for single-instance applications; Redis is needed for multi-instance deployments.\n\n### Step 3: Enable Batching\nUse DataLoader or a similar batching library to coalesce multiple individual record lookups into a single Supabase query with an `IN` clause. This is especially effective in GraphQL resolvers where N+1 query problems are common. Verify the batch size does not exceed Supabase's row limit per request.\n\n### Step 4: Optimize Connections\nConfigure connection pooling with keep-alive settings appropriate for your deployment environment. Serverless functions require aggressive connection reuse via PgBouncer in transaction mode; long-running servers can use session-mode pooling with a larger pool size.\n\n## Output\n- Measured baseline latency documented for the top critical operations\n- Caching layer implemented with appropriate invalidation strategy\n- Request batching eliminating N+1 query patterns\n- Connection pooling configured for the deployment environment\n\n## Error Handling\n\nSee `${CLAUDE_SKILL_DIR}\u002Freferences\u002Ferrors.md` for comprehensive error handling.\n\n## Examples\n\nSee `${CLAUDE_SKILL_DIR}\u002Freferences\u002Fexamples.md` for detailed examples.\n\n## Resources\n- [Supabase Performance Guide](https:\u002F\u002Fsupabase.com\u002Fdocs\u002Fperformance)\n- [DataLoader Documentation](https:\u002F\u002Fgithub.com\u002Fgraphql\u002Fdataloader)\n- [LRU Cache Documentation](https:\u002F\u002Fgithub.com\u002Fisaacs\u002Fnode-lru-cache)\n\n## Overview\n\nOptimize Supabase API performance with caching, batching, and connection pooling.","# Supabase Performance Tuning\n\n## Prerequisites\n- Supabase SDK installed\n- Understanding of async patterns\n- Redis or in-memory cache available (optional)\n- Performance monitoring in place\n\n## Instructions\n\nPerformance tuning a Supabase integration should follow a measurement-first discipline. Applying optimizations without a baseline makes it impossible to quantify impact, and premature optimization often targets the wrong bottleneck. Start with profiling, then apply targeted improvements in order of expected impact.\n\n### Step 1: Establish Baseline\nMeasure current latency for critical Supabase operations using application-level instrumentation or the Supabase query editor's explain analyze output. Record P50, P95, and P99 latencies for each operation under representative load. Identify the three to five slowest operations as your primary targets.\n\n### Step 2: Implement Caching\nAdd response caching for frequently accessed data that changes infrequently. Use TTL-based invalidation for data that has a predictable freshness requirement and event-driven invalidation for data that must be immediately consistent after writes. An LRU cache in memory is appropriate for single-instance applications; Redis is needed for multi-instance deployments.\n\n### Step 3: Enable Batching\nUse DataLoader or a similar batching library to coalesce multiple individual record lookups into a single Supabase query with an `IN` clause. This is especially effective in GraphQL resolvers where N+1 query problems are common. Verify the batch size does not exceed Supabase's row limit per request.\n\n### Step 4: Optimize Connections\nConfigure connection pooling with keep-alive settings appropriate for your deployment environment. Serverless functions require aggressive connection reuse via PgBouncer in transaction mode; long-running servers can use session-mode pooling with a larger pool size.\n\n## Output\n- Measured baseline latency documented for the top critical operations\n- Caching layer implemented with appropriate invalidation strategy\n- Request batching eliminating N+1 query patterns\n- Connection pooling configured for the deployment environment\n\n## Error Handling\n\nSee `${CLAUDE_SKILL_DIR}\u002Freferences\u002Ferrors.md` for comprehensive error handling.\n\n## Examples\n\nSee `${CLAUDE_SKILL_DIR}\u002Freferences\u002Fexamples.md` for detailed examples.\n\n## Resources\n- [Supabase Performance Guide](https:\u002F\u002Fsupabase.com\u002Fdocs\u002Fperformance)\n- [DataLoader Documentation](https:\u002F\u002Fgithub.com\u002Fgraphql\u002Fdataloader)\n- [LRU Cache Documentation](https:\u002F\u002Fgithub.com\u002Fisaacs\u002Fnode-lru-cache)\n\n## Overview\n\nOptimize Supabase API performance with caching, batching, and connection pooling.",{"name":5,"author":43,"license":14,"version":44,"description":45,"allowed-tools":46,"compatible-with":47},"Jeremy Longshore \u003Cjeremy@intentsolutions.io>","1.0.0","Optimize Supabase API performance with caching, batching, and connection pooling.\nUse when experiencing slow API responses, implementing caching strategies,\nor optimizing request throughput for Supabase integrations.\nTrigger with phrases like \"supabase performance\", \"optimize supabase\",\n\"supabase latency\", \"supabase caching\", \"supabase slow\", \"supabase batch\".\n","Read, Write, Edit","claude-code, codex, openclaw","master","3f5d983eb4ef375b749adcd6b07ec03bd82ae8a8","claude-code\u002Fplugins-plus-skills\u002Fplugins\u002Fsaas-packs\u002Fsupabase-pack\u002Fskills\u002Fsupabase-performance-tuning",0,"https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills","https:\u002F\u002Fgithub.com\u002Fmicsapp","2026-03-20 11:24:18",{"source":8,"skillName":5,"commands":56,"prompt":66,"zipAvailable":67},[57,60,63],{"tool":58,"command":59},"npx","npx skills add micsapp\u002Fmicstec-skills --skill supabase-performance-tuning",{"tool":61,"command":62},"bunx","bunx skills add micsapp\u002Fmicstec-skills --skill supabase-performance-tuning",{"tool":64,"command":65},"pnpm","pnpm dlx skills add micsapp\u002Fmicstec-skills --skill supabase-performance-tuning","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\u002Fsupabase-pack\u002Fskills\u002Fsupabase-performance-tuning\u002FSKILL.md",true,[69,75,79],{"path":70,"resourceType":71,"resourceTypeDesc":72,"sizeBytes":73,"sourceHtmlUrl":74},"references\u002Fcaching-strategy.md","REFERENCE","参考文档",939,"https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fclaude-code\u002Fplugins-plus-skills\u002Fplugins\u002Fsaas-packs\u002Fsupabase-pack\u002Fskills\u002Fsupabase-performance-tuning\u002Freferences\u002Fcaching-strategy.md",{"path":76,"resourceType":71,"resourceTypeDesc":72,"sizeBytes":77,"sourceHtmlUrl":78},"references\u002Ferrors.md",328,"https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fclaude-code\u002Fplugins-plus-skills\u002Fplugins\u002Fsaas-packs\u002Fsupabase-pack\u002Fskills\u002Fsupabase-performance-tuning\u002Freferences\u002Ferrors.md",{"path":80,"resourceType":71,"resourceTypeDesc":72,"sizeBytes":81,"sourceHtmlUrl":82},"references\u002Fexamples.md",213,"https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fclaude-code\u002Fplugins-plus-skills\u002Fplugins\u002Fsaas-packs\u002Fsupabase-pack\u002Fskills\u002Fsupabase-performance-tuning\u002Freferences\u002Fexamples.md",[84,118,146,166,186,211],{"skillNo":85,"name":86,"nameZh":6,"description":87,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":88,"categories":89,"keywords":100,"publishedAt":38},"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. Use when discussing APIM component selection, network topology, cost optimization, or comparing alternatives like workspaces vs instances, VNet Internal vs External mode, or Front Door vs Application Gateway.","https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fcopilot-cli\u002Fcopilot-agent-skills\u002F.github\u002Fskills\u002Fazure-apim-architecture\u002FSKILL.md",[90,95],{"categoryNo":91,"categoryName":92,"taxonomyType":93,"taxonomyTypeDesc":94},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":96,"categoryName":97,"taxonomyType":98,"taxonomyTypeDesc":99},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[101,102,103,104,105,106,107,108,109,35,110,111,112,113,114,115,23,116,117,24],"architecture","azure","azure apim architecture","component","authentication","gateway","topology","Optimization","network","team","environment","multi-environment","workspaces","instances","selection","azure api management","mode",{"skillNo":119,"name":120,"nameZh":6,"description":121,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":122,"categories":123,"keywords":132,"publishedAt":38},"01M6HBT7J4H082JEEA670B3EQ9","apiops-deployment","Guides deployment of Azure API Management infrastructure using Infrastructure as Code (Bicep\u002FTerraform), CI\u002FCD pipelines (GitHub Actions\u002FAzure DevOps), and APIOps workflows. Use when deploying APIM, creating pipelines, or implementing dev→test→prod promotion strategies.","https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fcopilot-cli\u002Fcopilot-agent-skills\u002F.github\u002Fskills\u002Fapiops-deployment\u002FSKILL.md",[124,125,128,131],{"categoryNo":91,"categoryName":92,"taxonomyType":93,"taxonomyTypeDesc":94},{"categoryNo":126,"categoryName":127,"taxonomyType":93,"taxonomyTypeDesc":94},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":129,"categoryName":130,"taxonomyType":93,"taxonomyTypeDesc":94},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":96,"categoryName":97,"taxonomyType":98,"taxonomyTypeDesc":99},[133,134,135,136,102,137,37,138,139,140,141,142,35,110,23,143,144,116,145,25],"deployment","apiops deployment","workflows","azure devops","infrastructure","infrastructure as code","actions","ci","github actions","github-actions","as","guides","CI\u002FCD",{"skillNo":147,"name":148,"nameZh":6,"description":149,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":150,"categories":151,"keywords":153,"publishedAt":38},"01M6HBT2HEA23THNE9E00GYQBE","apim-policy-authoring","Creates production-ready Azure API Management policy XML for authentication (OAuth 2.0, JWT validation, subscription keys), rate limiting, CORS configuration, error handling, and API transformations. Use when implementing API security, access control, or request\u002Fresponse processing logic.","https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fcopilot-cli\u002Fcopilot-agent-skills\u002F.github\u002Fskills\u002Fapim-policy-authoring\u002FSKILL.md",[152],{"categoryNo":91,"categoryName":92,"taxonomyType":93,"taxonomyTypeDesc":94},[154,155,156,157,102,105,35,110,158,33,159,160,161,162,163,116,164,165,25,24],"policy","authoring","apim policy authoring","security","access","ready","api security","Access Control","error","processing","cors configuration","production-ready",{"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":14,"licenseFileUrl":6,"sourceHtmlUrl":170,"categories":171,"keywords":174,"publishedAt":38},"01M6HBSY65SB29J9WE9KYD0K6T","api-security-review","Reviews Azure API Management configurations for security vulnerabilities, OWASP API Security Top 10 compliance, VNet Internal mode validation, Private Link verification, and Azure Security Benchmark alignment. 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",[172,173],{"categoryNo":91,"categoryName":92,"taxonomyType":93,"taxonomyTypeDesc":94},{"categoryNo":96,"categoryName":97,"taxonomyType":98,"taxonomyTypeDesc":99},[175,157,176,35,160,177,102,133,178,179,180,181,110,182,116,183,184,185,117,24],"review","security review","api security review","benchmark","verification","owasp","owasp-api","alignment","azure security","reviews","top",{"skillNo":187,"name":188,"nameZh":6,"description":189,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":190,"categories":191,"keywords":192,"publishedAt":38},"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",[],[193,194,195,135,196,197,198,199,35,200,201,202,203,204,205,206,207,208,209,210],"cli","jira","jira cli","init","tasks","create","issues","common","work","command","edit","list","view","project","project work","token","line","sprints",{"skillNo":212,"name":213,"nameZh":6,"description":214,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":215,"categories":216,"keywords":217,"publishedAt":38},"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",[],[213,218,219,220,221,222,223,33,224,225],"npm","js","calculate","node","math","user","compute","errors"]