[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6JJGF33DEVZ418QNET0J82F":3,"skill-same:01M6JJGF33DEVZ418QNET0J82F":64},{"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":30,"linkOnly":31,"markdownContent":32,"markdownBody":33,"frontMatter":34,"refName":36,"commitSha":37,"skillDirectory":38,"forksCount":39,"repositoryHtmlUrl":40,"repositoryHomepageUrl":6,"ownerHtmlUrl":41,"ownerBlogUrl":6,"ownerDescription":42,"updatedAt":43,"install":44,"resources":57},"01M6JJGF33DEVZ418QNET0J82F","performance-profiling",null,"Performance profiling principles. Measurement, analysis, and optimization techniques.","transaurus\u002Fstaging-davila7-claude-code-templates","transaurus","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F210882017?v=4","01M6JH1R6ZCRXGJCTDP5ZKZBE6","Page Turner Agent","01M6JH1RBBR2P6Y0XWDGM4B0G7",0,"MIT","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdevelopment\u002Fperformance-profiling\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29],"performance","performance profiling","profiling","Optimization","analysis","Bash","grep","read","principles","measurement","techniques","2026-11-10 10:12:30",false,"---\nname: performance-profiling\ndescription: Performance profiling principles. Measurement, analysis, and optimization techniques.\nallowed-tools: Read, Glob, Grep, Bash\n---\n\n# Performance Profiling\n\n> Measure, analyze, optimize - in that order.\n\n## ? Runtime Scripts\n\n**Execute these for automated profiling:**\n\n| Script | Purpose | Usage |\n|--------|---------|-------|\n| `scripts\u002Flighthouse_audit.py` | Lighthouse performance audit | `python scripts\u002Flighthouse_audit.py https:\u002F\u002Fexample.com` |\n\n---\n\n## 1. Core Web Vitals\n\n### Targets\n\n| Metric | Good | Poor | Measures |\n|--------|------|------|----------|\n| **LCP** | \u003C 2.5s | > 4.0s | Loading |\n| **INP** | \u003C 200ms | > 500ms | Interactivity |\n| **CLS** | \u003C 0.1 | > 0.25 | Stability |\n\n### When to Measure\n\n| Stage | Tool |\n|-------|------|\n| Development | Local Lighthouse |\n| CI\u002FCD | Lighthouse CI |\n| Production | RUM (Real User Monitoring) |\n\n---\n\n## 2. Profiling Workflow\n\n### The 4-Step Process\n\n```\n1. BASELINE → Measure current state\n2. IDENTIFY → Find the bottleneck\n3. FIX → Make targeted change\n4. VALIDATE → Confirm improvement\n```\n\n### Profiling Tool Selection\n\n| Problem | Tool |\n|---------|------|\n| Page load | Lighthouse |\n| Bundle size | Bundle analyzer |\n| Runtime | DevTools Performance |\n| Memory | DevTools Memory |\n| Network | DevTools Network |\n\n---\n\n## 3. Bundle Analysis\n\n### What to Look For\n\n| Issue | Indicator |\n|-------|-----------|\n| Large dependencies | Top of bundle |\n| Duplicate code | Multiple chunks |\n| Unused code | Low coverage |\n| Missing splits | Single large chunk |\n\n### Optimization Actions\n\n| Finding | Action |\n|---------|--------|\n| Big library | Import specific modules |\n| Duplicate deps | Dedupe, update versions |\n| Route in main | Code split |\n| Unused exports | Tree shake |\n\n---\n\n## 4. Runtime Profiling\n\n### Performance Tab Analysis\n\n| Pattern | Meaning |\n|---------|---------|\n| Long tasks (>50ms) | UI blocking |\n| Many small tasks | Possible batching opportunity |\n| Layout\u002Fpaint | Rendering bottleneck |\n| Script | JavaScript execution |\n\n### Memory Tab Analysis\n\n| Pattern | Meaning |\n|---------|---------|\n| Growing heap | Possible leak |\n| Large retained | Check references |\n| Detached DOM | Not cleaned up |\n\n---\n\n## 5. Common Bottlenecks\n\n### By Symptom\n\n| Symptom | Likely Cause |\n|---------|--------------|\n| Slow initial load | Large JS, render blocking |\n| Slow interactions | Heavy event handlers |\n| Jank during scroll | Layout thrashing |\n| Growing memory | Leaks, retained refs |\n\n---\n\n## 6. Quick Win Priorities\n\n| Priority | Action | Impact |\n|----------|--------|--------|\n| 1 | Enable compression | High |\n| 2 | Lazy load images | High |\n| 3 | Code split routes | High |\n| 4 | Cache static assets | Medium |\n| 5 | Optimize images | Medium |\n\n---\n\n## 7. Anti-Patterns\n\n| ❌ Don't | ✅ Do |\n|----------|-------|\n| Guess at problems | Profile first |\n| Micro-optimize | Fix biggest issue |\n| Optimize early | Optimize when needed |\n| Ignore real users | Use RUM data |\n\n---\n\n> **Remember:** The fastest code is code that doesn't run. Remove before optimizing.\n","# Performance Profiling\n\n> Measure, analyze, optimize - in that order.\n\n## ? Runtime Scripts\n\n**Execute these for automated profiling:**\n\n| Script | Purpose | Usage |\n|--------|---------|-------|\n| `scripts\u002Flighthouse_audit.py` | Lighthouse performance audit | `python scripts\u002Flighthouse_audit.py https:\u002F\u002Fexample.com` |\n\n---\n\n## 1. Core Web Vitals\n\n### Targets\n\n| Metric | Good | Poor | Measures |\n|--------|------|------|----------|\n| **LCP** | \u003C 2.5s | > 4.0s | Loading |\n| **INP** | \u003C 200ms | > 500ms | Interactivity |\n| **CLS** | \u003C 0.1 | > 0.25 | Stability |\n\n### When to Measure\n\n| Stage | Tool |\n|-------|------|\n| Development | Local Lighthouse |\n| CI\u002FCD | Lighthouse CI |\n| Production | RUM (Real User Monitoring) |\n\n---\n\n## 2. Profiling Workflow\n\n### The 4-Step Process\n\n```\n1. BASELINE → Measure current state\n2. IDENTIFY → Find the bottleneck\n3. FIX → Make targeted change\n4. VALIDATE → Confirm improvement\n```\n\n### Profiling Tool Selection\n\n| Problem | Tool |\n|---------|------|\n| Page load | Lighthouse |\n| Bundle size | Bundle analyzer |\n| Runtime | DevTools Performance |\n| Memory | DevTools Memory |\n| Network | DevTools Network |\n\n---\n\n## 3. Bundle Analysis\n\n### What to Look For\n\n| Issue | Indicator |\n|-------|-----------|\n| Large dependencies | Top of bundle |\n| Duplicate code | Multiple chunks |\n| Unused code | Low coverage |\n| Missing splits | Single large chunk |\n\n### Optimization Actions\n\n| Finding | Action |\n|---------|--------|\n| Big library | Import specific modules |\n| Duplicate deps | Dedupe, update versions |\n| Route in main | Code split |\n| Unused exports | Tree shake |\n\n---\n\n## 4. Runtime Profiling\n\n### Performance Tab Analysis\n\n| Pattern | Meaning |\n|---------|---------|\n| Long tasks (>50ms) | UI blocking |\n| Many small tasks | Possible batching opportunity |\n| Layout\u002Fpaint | Rendering bottleneck |\n| Script | JavaScript execution |\n\n### Memory Tab Analysis\n\n| Pattern | Meaning |\n|---------|---------|\n| Growing heap | Possible leak |\n| Large retained | Check references |\n| Detached DOM | Not cleaned up |\n\n---\n\n## 5. Common Bottlenecks\n\n### By Symptom\n\n| Symptom | Likely Cause |\n|---------|--------------|\n| Slow initial load | Large JS, render blocking |\n| Slow interactions | Heavy event handlers |\n| Jank during scroll | Layout thrashing |\n| Growing memory | Leaks, retained refs |\n\n---\n\n## 6. Quick Win Priorities\n\n| Priority | Action | Impact |\n|----------|--------|--------|\n| 1 | Enable compression | High |\n| 2 | Lazy load images | High |\n| 3 | Code split routes | High |\n| 4 | Cache static assets | Medium |\n| 5 | Optimize images | Medium |\n\n---\n\n## 7. Anti-Patterns\n\n| ❌ Don't | ✅ Do |\n|----------|-------|\n| Guess at problems | Profile first |\n| Micro-optimize | Fix biggest issue |\n| Optimize early | Optimize when needed |\n| Ignore real users | Use RUM data |\n\n---\n\n> **Remember:** The fastest code is code that doesn't run. Remove before optimizing.\n",{"name":5,"description":7,"allowed-tools":35},"Read, Glob, Grep, Bash","main","34fa6acf794b9a6310d298cbb8fb8c9420a5edcf","cli-tool\u002Fcomponents\u002Fskills\u002Fdevelopment\u002Fperformance-profiling",2,"https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates","https:\u002F\u002Fgithub.com\u002Ftransaurus","Automated works of Page Turner","2026-03-28 10:12:59",{"source":8,"skillName":5,"commands":45,"prompt":55,"zipAvailable":56},[46,49,52],{"tool":47,"command":48},"npx","npx skills add transaurus\u002Fstaging-davila7-claude-code-templates --skill performance-profiling",{"tool":50,"command":51},"bunx","bunx skills add transaurus\u002Fstaging-davila7-claude-code-templates --skill performance-profiling",{"tool":53,"command":54},"pnpm","pnpm dlx skills add transaurus\u002Fstaging-davila7-claude-code-templates --skill performance-profiling","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdevelopment\u002Fperformance-profiling\u002FSKILL.md",true,[58],{"path":59,"resourceType":60,"resourceTypeDesc":61,"sizeBytes":62,"sourceHtmlUrl":63},"scripts\u002Flighthouse_audit.py","SCRIPT","脚本",2657,"https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdevelopment\u002Fperformance-profiling\u002Fscripts\u002Flighthouse_audit.py",[65,97,118,142,162,188],{"skillNo":66,"name":67,"nameZh":6,"description":68,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":69,"categories":70,"keywords":76,"publishedAt":30},"01M6JMRJR3BE0HGWFWDZSB853S","zapier-make-patterns","No-code automation democratizes workflow building. Zapier and Make (formerly Integromat) let non-developers automate business processes without writing code. But no-code doesn't mean no-complexity - these platforms have their own patterns, pitfalls, and breaking points.  This skill covers when to use which platform, how to build reliable automations, and when to graduate to code-based solutions. Key insight: Zapier optimizes for simplicity and integrations (7000+ apps), Make optimizes for power","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fzapier-make-patterns\u002FSKILL.md",[71],{"categoryNo":72,"categoryName":73,"taxonomyType":74,"taxonomyTypeDesc":75},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96],"zapier make patterns","patterns","make","zapier","writing","workflow","automation","code","integrations","business","use","power","complexity","platform","apps","how to","No-Code","which","for","spawner",{"skillNo":98,"name":99,"nameZh":6,"description":100,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":101,"categories":102,"keywords":103,"publishedAt":30},"01M6JMR8YK6SWPCTG1MCQTMN9S","yeet","Use only when the user explicitly asks to stage, commit, push, and open a GitHub pull request in one flow using the GitHub CLI (`gh`).","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fyeet\u002FSKILL.md",[],[99,104,105,106,107,108,109,110,111,112,113,114,87,115,116,117],"cli","github","commit","pull request","openai","pull","push","flow","open","gh","user","only","stage","github cli",{"skillNo":119,"name":120,"nameZh":6,"description":121,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":122,"categories":123,"keywords":125,"publishedAt":30},"01M6JMQNFE64ZASQK90HARRXW8","workflow-automation","Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, workflows resume exactly where they left off.  This skill covers the platforms (n8n, Temporal, Inngest) and patterns (sequential, parallel, orchestrator-worker) that turn brittle scripts into production-grade automation.  Key insight: The platforms make different tradeoffs. n8n optimizes for accessibility","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fworkflow-automation\u002FSKILL.md",[124],{"categoryNo":72,"categoryName":73,"taxonomyType":74,"taxonomyTypeDesc":75},[82,83,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,95,96],"Workflow Automation","ai agents","accessibility","workflows","apache","execution","inngest","parallel","orchestrator","resume","n8n","payment","worker","scripts","temporal","with",{"skillNo":143,"name":144,"nameZh":6,"description":145,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":146,"categories":147,"keywords":148,"publishedAt":30},"01M6JMQDYJ0XETERPHGDR3EVGN","trigger-dev","Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design. Use when: trigger.dev, trigger dev, background task, ai background job, long running task.","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Ftrigger-dev\u002FSKILL.md",[],[149,150,151,152,153,129,154,130,131,155,87,156,157,158,159,160,161,141,95,96],"dev","trigger dev","trigger","design","typescript","async execution","first","async","developer experience","expert","task","background jobs","long",{"skillNo":163,"name":164,"nameZh":6,"description":165,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":166,"categories":167,"keywords":171,"publishedAt":30},"01M6JMQ5J6KK3GSX9FJCWWK6G6","planning-with-files","Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage. Use when starting complex tasks, multi-step projects, research tasks, or when the user mentions planning, organizing work, tracking progress, or wants structured output.","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fplanning-with-files\u002FSKILL.md",[168],{"categoryNo":169,"categoryName":170,"taxonomyType":74,"taxonomyTypeDesc":75},"01JBSEEDCAT000000000000021","资料检索与研究",[172,173,174,141,175,82,176,177,178,179,180,181,87,182,183,184,185,186,187,95],"planning with files","planning","files","with files","storage","tasks","markdown","knowledge","projects","work","manus","structured output","progress","transforms","multi","output",{"skillNo":189,"name":190,"nameZh":6,"description":191,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":192,"categories":193,"keywords":198,"publishedAt":30},"01M6JMPWAT60RXXNEC4V9TRBRS","n8n-workflow-patterns","Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, or scheduled tasks.","https:\u002F\u002Fgithub.com\u002Ftransaurus\u002Fstaging-davila7-claude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fn8n\u002Fn8n-workflow-patterns\u002FSKILL.md",[194,197],{"categoryNo":195,"categoryName":196,"taxonomyType":74,"taxonomyTypeDesc":75},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":72,"categoryName":73,"taxonomyType":74,"taxonomyTypeDesc":75},[82,199,136,200,78,201,202,129,203,177,173,204,205,206,207,208,209,210,211,212],"n8n workflow patterns","workflow patterns","n8n workflow","ai agent","architecture","database","api","planning workflow","structure","database operations","webhook","processing","http api","scheduled"]