[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6NRPFBAYNDYFG7QKS3TZXEP":3,"skill-same:01M6NRPFBAYNDYFG7QKS3TZXEP":135},{"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":44,"commitSha":45,"skillDirectory":46,"forksCount":47,"repositoryHtmlUrl":48,"repositoryHomepageUrl":6,"ownerHtmlUrl":49,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":50,"install":51,"resources":64},"01M6NRPFBAYNDYFG7QKS3TZXEP","docs-seeker",null,"Search technical documentation using executable scripts to detect query type, fetch from llms.txt sources (context7.com), and analyze results. Use when user needs: (1) Topic-specific documentation (features\u002Fcomponents\u002Fconcepts), (2) Library\u002Fframework documentation, (3) GitHub repository analysis, (4) Documentation discovery with automated agent distribution strategy","vntopicai\u002Fai-planner","vntopicai","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F201040886?v=4","01M6NRHDP3KC0J2F22TSFZH796","01M6NRHDT0JGWD7J4Z10Y0NHHS",1,"MIT","https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"docs seeker","docs","technical","with","detect","sources","type","distribution","query","use","fetch","strategy","analyze","discovery","analysis","search","documentation","components","llms","github","2026-11-10 10:12:30",false,"---\nname: docs-seeker\ndescription: \"Search technical documentation using executable scripts to detect query type, fetch from llms.txt sources (context7.com), and analyze results. Use when user needs: (1) Topic-specific documentation (features\u002Fcomponents\u002Fconcepts), (2) Library\u002Fframework documentation, (3) GitHub repository analysis, (4) Documentation discovery with automated agent distribution strategy\"\nversion: 3.1.0\n---\n\n# Documentation Discovery via Scripts\n\n## Overview\n\n**Script-first** documentation discovery using llms.txt standard.\n\nExecute scripts to handle entire workflow - no manual URL construction needed.\n\n## Primary Workflow\n\n**ALWAYS execute scripts in this order:**\n\n```bash\n# 1. DETECT query type (topic-specific vs general)\nnode scripts\u002Fdetect-topic.js \"\u003Cuser query>\"\n\n# 2. FETCH documentation using script output\nnode scripts\u002Ffetch-docs.js \"\u003Cuser query>\"\n\n# 3. ANALYZE results (if multiple URLs returned)\ncat llms.txt | node scripts\u002Fanalyze-llms-txt.js -\n```\n\nScripts handle URL construction, fallback chains, and error handling automatically.\n\n## Scripts\n\n**`detect-topic.js`** - Classify query type\n- Identifies topic-specific vs general queries\n- Extracts library name + topic keyword\n- Returns JSON: `{topic, library, isTopicSpecific}`\n- Zero-token execution\n\n**`fetch-docs.js`** - Retrieve documentation\n- Constructs context7.com URLs automatically\n- Handles fallback: topic → general → error\n- Outputs llms.txt content or error message\n- Zero-token execution\n\n**`analyze-llms-txt.js`** - Process llms.txt\n- Categorizes URLs (critical\u002Fimportant\u002Fsupplementary)\n- Recommends agent distribution (1 agent, 3 agents, 7 agents, phased)\n- Returns JSON with strategy\n- Zero-token execution\n\n## Workflow References\n\n**[Topic-Specific Search](.\u002Fworkflows\u002Ftopic-search.md)** - Fastest path (10-15s)\n\n**[General Library Search](.\u002Fworkflows\u002Flibrary-search.md)** - Comprehensive coverage (30-60s)\n\n**[Repository Analysis](.\u002Fworkflows\u002Frepo-analysis.md)** - Fallback strategy\n\n## References\n\n**[context7-patterns.md](.\u002Freferences\u002Fcontext7-patterns.md)** - URL patterns, known repositories\n\n**[errors.md](.\u002Freferences\u002Ferrors.md)** - Error handling, fallback strategies\n\n**[advanced.md](.\u002Freferences\u002Fadvanced.md)** - Edge cases, versioning, multi-language\n\n## Execution Principles\n\n1. **Scripts first** - Execute scripts instead of manual URL construction\n2. **Zero-token overhead** - Scripts run without context loading\n3. **Automatic fallback** - Scripts handle topic → general → error chains\n4. **Progressive disclosure** - Load workflows\u002Freferences only when needed\n5. **Agent distribution** - Scripts recommend parallel agent strategy\n\n## Quick Start\n\n**Topic query:** \"How do I use date picker in shadcn?\"\n```bash\nnode scripts\u002Fdetect-topic.js \"\u003Cquery>\"  # → {topic, library, isTopicSpecific}\nnode scripts\u002Ffetch-docs.js \"\u003Cquery>\"    # → 2-3 URLs\n# Read URLs with WebFetch\n```\n\n**General query:** \"Documentation for Next.js\"\n```bash\nnode scripts\u002Fdetect-topic.js \"\u003Cquery>\"         # → {isTopicSpecific: false}\nnode scripts\u002Ffetch-docs.js \"\u003Cquery>\"           # → 8+ URLs\ncat llms.txt | node scripts\u002Fanalyze-llms-txt.js -  # → {totalUrls, distribution}\n# Deploy agents per recommendation\n```\n\n## Environment\n\nScripts load `.env`: `process.env` > `.claude\u002Fskills\u002Fdocs-seeker\u002F.env` > `.claude\u002Fskills\u002F.env` > `.claude\u002F.env`\n\nSee `.env.example` for configuration options.\n","# Documentation Discovery via Scripts\n\n## Overview\n\n**Script-first** documentation discovery using llms.txt standard.\n\nExecute scripts to handle entire workflow - no manual URL construction needed.\n\n## Primary Workflow\n\n**ALWAYS execute scripts in this order:**\n\n```bash\n# 1. DETECT query type (topic-specific vs general)\nnode scripts\u002Fdetect-topic.js \"\u003Cuser query>\"\n\n# 2. FETCH documentation using script output\nnode scripts\u002Ffetch-docs.js \"\u003Cuser query>\"\n\n# 3. ANALYZE results (if multiple URLs returned)\ncat llms.txt | node scripts\u002Fanalyze-llms-txt.js -\n```\n\nScripts handle URL construction, fallback chains, and error handling automatically.\n\n## Scripts\n\n**`detect-topic.js`** - Classify query type\n- Identifies topic-specific vs general queries\n- Extracts library name + topic keyword\n- Returns JSON: `{topic, library, isTopicSpecific}`\n- Zero-token execution\n\n**`fetch-docs.js`** - Retrieve documentation\n- Constructs context7.com URLs automatically\n- Handles fallback: topic → general → error\n- Outputs llms.txt content or error message\n- Zero-token execution\n\n**`analyze-llms-txt.js`** - Process llms.txt\n- Categorizes URLs (critical\u002Fimportant\u002Fsupplementary)\n- Recommends agent distribution (1 agent, 3 agents, 7 agents, phased)\n- Returns JSON with strategy\n- Zero-token execution\n\n## Workflow References\n\n**[Topic-Specific Search](.\u002Fworkflows\u002Ftopic-search.md)** - Fastest path (10-15s)\n\n**[General Library Search](.\u002Fworkflows\u002Flibrary-search.md)** - Comprehensive coverage (30-60s)\n\n**[Repository Analysis](.\u002Fworkflows\u002Frepo-analysis.md)** - Fallback strategy\n\n## References\n\n**[context7-patterns.md](.\u002Freferences\u002Fcontext7-patterns.md)** - URL patterns, known repositories\n\n**[errors.md](.\u002Freferences\u002Ferrors.md)** - Error handling, fallback strategies\n\n**[advanced.md](.\u002Freferences\u002Fadvanced.md)** - Edge cases, versioning, multi-language\n\n## Execution Principles\n\n1. **Scripts first** - Execute scripts instead of manual URL construction\n2. **Zero-token overhead** - Scripts run without context loading\n3. **Automatic fallback** - Scripts handle topic → general → error chains\n4. **Progressive disclosure** - Load workflows\u002Freferences only when needed\n5. **Agent distribution** - Scripts recommend parallel agent strategy\n\n## Quick Start\n\n**Topic query:** \"How do I use date picker in shadcn?\"\n```bash\nnode scripts\u002Fdetect-topic.js \"\u003Cquery>\"  # → {topic, library, isTopicSpecific}\nnode scripts\u002Ffetch-docs.js \"\u003Cquery>\"    # → 2-3 URLs\n# Read URLs with WebFetch\n```\n\n**General query:** \"Documentation for Next.js\"\n```bash\nnode scripts\u002Fdetect-topic.js \"\u003Cquery>\"         # → {isTopicSpecific: false}\nnode scripts\u002Ffetch-docs.js \"\u003Cquery>\"           # → 8+ URLs\ncat llms.txt | node scripts\u002Fanalyze-llms-txt.js -  # → {totalUrls, distribution}\n# Deploy agents per recommendation\n```\n\n## Environment\n\nScripts load `.env`: `process.env` > `.claude\u002Fskills\u002Fdocs-seeker\u002F.env` > `.claude\u002Fskills\u002F.env` > `.claude\u002F.env`\n\nSee `.env.example` for configuration options.\n",{"name":5,"version":43,"description":7},"3.1.0","main","c6237323cdebe9c0193c97f1a338cb169728d78d","fixtures\u002Flocal-skills\u002Fdocs-seeker",0,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner","https:\u002F\u002Fgithub.com\u002Fvntopicai","2026-05-13 18:29:40",{"source":8,"skillName":5,"commands":52,"prompt":62,"zipAvailable":63},[53,56,59],{"tool":54,"command":55},"npx","npx skills add vntopicai\u002Fai-planner --skill docs-seeker",{"tool":57,"command":58},"bunx","bunx skills add vntopicai\u002Fai-planner --skill docs-seeker",{"tool":60,"command":61},"pnpm","pnpm dlx skills add vntopicai\u002Fai-planner --skill docs-seeker","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002FSKILL.md",true,[65,71,77,81,85,89,95,99,103,107,111,115,119,123,127,131],{"path":66,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":69,"sourceHtmlUrl":70},".env.example","OTHER","其他",456,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002F.env.example",{"path":72,"resourceType":73,"resourceTypeDesc":74,"sizeBytes":75,"sourceHtmlUrl":76},"package.json","REFERENCE","参考文档",631,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fpackage.json",{"path":78,"resourceType":73,"resourceTypeDesc":74,"sizeBytes":79,"sourceHtmlUrl":80},"references\u002Fadvanced.md",1776,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Freferences\u002Fadvanced.md",{"path":82,"resourceType":73,"resourceTypeDesc":74,"sizeBytes":83,"sourceHtmlUrl":84},"references\u002Fcontext7-patterns.md",1538,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Freferences\u002Fcontext7-patterns.md",{"path":86,"resourceType":73,"resourceTypeDesc":74,"sizeBytes":87,"sourceHtmlUrl":88},"references\u002Ferrors.md",1258,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Freferences\u002Ferrors.md",{"path":90,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":93,"sourceHtmlUrl":94},"scripts\u002Fanalyze-llms-txt.js","SCRIPT","脚本",5183,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fscripts\u002Fanalyze-llms-txt.js",{"path":96,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":97,"sourceHtmlUrl":98},"scripts\u002Fdetect-topic.js",4456,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fscripts\u002Fdetect-topic.js",{"path":100,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":101,"sourceHtmlUrl":102},"scripts\u002Ffetch-docs.js",4981,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fscripts\u002Ffetch-docs.js",{"path":104,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":105,"sourceHtmlUrl":106},"scripts\u002Ftests\u002Frun-tests.js",1554,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fscripts\u002Ftests\u002Frun-tests.js",{"path":108,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":109,"sourceHtmlUrl":110},"scripts\u002Ftests\u002Ftest-analyze-llms.js",3831,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fscripts\u002Ftests\u002Ftest-analyze-llms.js",{"path":112,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":113,"sourceHtmlUrl":114},"scripts\u002Ftests\u002Ftest-detect-topic.js",4009,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fscripts\u002Ftests\u002Ftest-detect-topic.js",{"path":116,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":117,"sourceHtmlUrl":118},"scripts\u002Ftests\u002Ftest-fetch-docs.js",2294,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fscripts\u002Ftests\u002Ftest-fetch-docs.js",{"path":120,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":121,"sourceHtmlUrl":122},"scripts\u002Futils\u002Fenv-loader.js",2420,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fscripts\u002Futils\u002Fenv-loader.js",{"path":124,"resourceType":73,"resourceTypeDesc":74,"sizeBytes":125,"sourceHtmlUrl":126},"workflows\u002Flibrary-search.md",2499,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fworkflows\u002Flibrary-search.md",{"path":128,"resourceType":73,"resourceTypeDesc":74,"sizeBytes":129,"sourceHtmlUrl":130},"workflows\u002Frepo-analysis.md",2216,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fworkflows\u002Frepo-analysis.md",{"path":132,"resourceType":73,"resourceTypeDesc":74,"sizeBytes":133,"sourceHtmlUrl":134},"workflows\u002Ftopic-search.md",2177,"https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fdocs-seeker\u002Fworkflows\u002Ftopic-search.md",[136,179,190,2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UI\u002FUX design intelligence - activate FIRST when user requests beautiful, stunning, gorgeous, or aesthetic interfaces. The primary skill for design decisions before implementation. 50 styles, 21 palettes, 50 font pairings, 20 charts, 8 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, check frontend UI\u002FUX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, mobile app, .html, .tsx, .vue, .svelte. Elements: button, modal, navbar, sidebar, card, table, form, chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, flat design. Topics: color palette, accessibility, animation, layout, typography, font pairing, spacing, hover, shadow, gradient.","https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fui-ux-pro-max\u002FSKILL.md",[142,147,150,153],{"categoryNo":143,"categoryName":144,"taxonomyType":145,"taxonomyTypeDesc":146},"01JBSEEDCAT000000000000009","前端开发","SCENARIO","使用场景",{"categoryNo":148,"categoryName":149,"taxonomyType":145,"taxonomyTypeDesc":146},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":151,"categoryName":152,"taxonomyType":145,"taxonomyTypeDesc":146},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":154,"categoryName":155,"taxonomyType":156,"taxonomyTypeDesc":157},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178],"ui ux","ux","ui","ui ux pro max","max","pro","Tailwind","mode","card","chart","app","tsx","fix","projects","improve","Charts","Animation","actions","design","frontend",{"skillNo":180,"name":181,"nameZh":6,"description":182,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":183,"categories":184,"keywords":186,"publishedAt":38},"01M6NRWHBP9GJK3QP0SDZ5JKMZ","template-skill","Replace with description of the skill and when Claude should use it.","https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Ftemplate-skill\u002FSKILL.md",[185],{"categoryNo":151,"categoryName":152,"taxonomyType":145,"taxonomyTypeDesc":146},[187,188,21,189,27],"template skill","template","it",{"skillNo":191,"name":192,"nameZh":6,"description":193,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":194,"categories":195,"keywords":199,"publishedAt":38},"01M6NRW447KC6JHJETVDTS0D25","research","Use when you need to research, analyze, and plan technical solutions that are scalable, secure, and maintainable.","https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fresearch\u002FSKILL.md",[196],{"categoryNo":197,"categoryName":198,"taxonomyType":145,"taxonomyTypeDesc":146},"01JBSEEDCAT000000000000021","资料检索与研究",[192,200,201,30,20,27,202,203],"secure","plan","Scalable","you",{"skillNo":205,"name":206,"nameZh":6,"description":207,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":208,"categories":209,"keywords":210,"publishedAt":38},"01M6NRVG7DA75KBK2XKCHQW8YT","Problem-Solving Techniques","Apply systematic problem-solving techniques for complexity spirals (simplification cascades), innovation blocks (collision-zone thinking), recurring patterns (meta-pattern recognition), assumption constraints (inversion exercise), scale uncertainty (scale game), and dispatch when stuck. Techniques derived from Microsoft Amplifier project patterns adapted for immediate application.","https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fproblem-solving\u002FSKILL.md",[],[211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230],"techniques","Problem Solving Techniques","problem","problem solving","uncertainty","simplification","apply","inversion","for","Inversion Exercise","project","problem-solving","thinking","Scale Game","complexity","recurring","game","exercise","Meta","when stuck",{"skillNo":232,"name":233,"nameZh":6,"description":234,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":235,"categories":236,"keywords":237,"publishedAt":38},"01M6NRV95P9DA08M92S4BHRG1M","payment-integration","Implement payment integrations with SePay (Vietnamese payment gateway with VietQR, bank transfers, cards) and Polar (global SaaS monetization platform with subscriptions, usage-based billing, automated benefits). Use when integrating payment processing, implementing checkout flows, managing subscriptions, handling webhooks, processing bank transfers, generating QR codes, automating benefit delivery, or building billing systems. Supports authentication (API keys, OAuth2), product management, customer portals, tax compliance (Polar as MoR), and comprehensive SDK integrations (Node.js, PHP, Python, Go, Laravel, Next.js).","https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fpayment-integration\u002FSKILL.md",[],[238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257],"payment","payment integration","integration","laravel","api","product","authentication","customer","node","implementing","api keys","bank","transfers","qr","flows","billing","processing","checkout","delivery","next",{"skillNo":259,"name":260,"nameZh":6,"description":261,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":262,"categories":263,"keywords":264,"publishedAt":38},"01M6NRV5BXB7JXQXWBHQJZ36AJ","nodejs-best-practices","Node.js development principles and decision-making. Framework selection, async patterns, security, and architecture. Teaches thinking, not copying.","https:\u002F\u002Fgithub.com\u002Fvntopicai\u002Fai-planner\u002Fblob\u002Fmain\u002Ffixtures\u002Flocal-skills\u002Fnodejs-best-practices\u002FSKILL.md",[],[265,266,267,268,269,270,271,272,223,273,274,275,246,276,277,278,279,280,281],"best practices","nodejs","nodejs best practices","selection","unknown","principles","decision-making","patterns","community","async","framework selection","decision","js","framework","development","architecture","security"]