[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skills:pro6":3,"skills:sce6":50,"skills:creators9":95,"skills:stats":193,"skills:all:stars:185:":195},[4,15,22,29,36,43],{"categoryNo":5,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":8,"categoryNameEn":9,"description":10,"level":11,"skillCount":12,"parentNo":13,"parentName":13,"children":14},"01JBSEEDCAT000000000000030","PROFESSION","适用职业","开发工程师","Software Engineer","从事软件编码、测试与运维的工程师",1,13274,null,[],{"categoryNo":16,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":17,"categoryNameEn":18,"description":19,"level":11,"skillCount":20,"parentNo":13,"parentName":13,"children":21},"01JBSEEDCAT000000000000032","设计师","Designer","视觉、交互与品牌设计人员",7775,[],{"categoryNo":23,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":24,"categoryNameEn":25,"description":26,"level":11,"skillCount":27,"parentNo":13,"parentName":13,"children":28},"01JBSEEDCAT000000000000033","数据分析师","Data Analyst","数据分析、报表与商业智能人员",4988,[],{"categoryNo":30,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":31,"categoryNameEn":32,"description":33,"level":11,"skillCount":34,"parentNo":13,"parentName":13,"children":35},"01JBSEEDCAT000000000000036","内容创作者","Content Creator","作者、编辑与自媒体创作者",3940,[],{"categoryNo":37,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":38,"categoryNameEn":39,"description":40,"level":11,"skillCount":41,"parentNo":13,"parentName":13,"children":42},"01JBSEEDCAT000000000000035","市场营销","Marketer","市场推广、增长与品牌运营人员",3446,[],{"categoryNo":44,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":45,"categoryNameEn":46,"description":47,"level":11,"skillCount":48,"parentNo":13,"parentName":13,"children":49},"01JBSEEDCAT000000000000037","律师与法务","Legal","合同、合规与法律事务人员",3316,[],[51,60,67,74,81,88],{"categoryNo":52,"taxonomyType":53,"taxonomyTypeDesc":54,"categoryName":55,"categoryNameEn":56,"description":57,"level":11,"skillCount":58,"parentNo":13,"parentName":13,"children":59},"01JBSEEDCAT000000000000022","SCENARIO","使用场景","智能体与自动化","Agents & Automation","Skill、MCP、智能体与工作流自动化",39458,[],{"categoryNo":61,"taxonomyType":53,"taxonomyTypeDesc":54,"categoryName":62,"categoryNameEn":63,"description":64,"level":11,"skillCount":65,"parentNo":13,"parentName":13,"children":66},"01JBSEEDCAT000000000000006","软件开发","Software Development","编码、测试、部署等软件研发任务",26531,[],{"categoryNo":68,"taxonomyType":53,"taxonomyTypeDesc":54,"categoryName":69,"categoryNameEn":70,"description":71,"level":11,"skillCount":72,"parentNo":13,"parentName":13,"children":73},"01JBSEEDCAT000000000000014","设计创意","Design & Creative","视觉设计、品牌与多媒体创作",13569,[],{"categoryNo":75,"taxonomyType":53,"taxonomyTypeDesc":54,"categoryName":76,"categoryNameEn":77,"description":78,"level":11,"skillCount":79,"parentNo":13,"parentName":13,"children":80},"01JBSEEDCAT000000000000001","办公效率","Office Productivity","日常办公文档、表格、演示与沟通类任务",6289,[],{"categoryNo":82,"taxonomyType":53,"taxonomyTypeDesc":54,"categoryName":83,"categoryNameEn":84,"description":85,"level":11,"skillCount":86,"parentNo":13,"parentName":13,"children":87},"01JBSEEDCAT000000000000017","内容创作","Content Creation","写作、文案与营销内容生产",6029,[],{"categoryNo":89,"taxonomyType":53,"taxonomyTypeDesc":54,"categoryName":90,"categoryNameEn":91,"description":92,"level":11,"skillCount":93,"parentNo":13,"parentName":13,"children":94},"01JBSEEDCAT000000000000020","研究与学习","Research & Learning","资料检索、知识整理与学习辅导",5531,[],{"records":96,"total":191,"current":11,"size":192},[97,111,120,130,140,150,160,169,179],{"accountNo":98,"login":99,"displayName":100,"avatarUrl":101,"accountType":102,"accountTypeDesc":103,"profileDescription":104,"skillCount":105,"repoCount":106,"professionCount":107,"scenarioCount":108,"totalStars":109,"updatedAt":110},"01M698VYDXZ6JW5WH3CRV650R8","microsoft","Microsoft","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6154722?v=4","ORGANIZATION","组织","Open source projects and samples from Microsoft",4160,229,11,7,828772,"2026-11-13 04:10:52",{"accountNo":112,"login":113,"displayName":113,"avatarUrl":114,"accountType":102,"accountTypeDesc":103,"profileDescription":115,"skillCount":116,"repoCount":117,"professionCount":108,"scenarioCount":108,"totalStars":118,"updatedAt":119},"01M698P3FSAZ6B4R928ZF19KPT","openclaw","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F252820863?v=4","Your personal, open source AI assistant.",362,32,437711,"2026-11-13 03:02:05",{"accountNo":121,"login":122,"displayName":123,"avatarUrl":124,"accountType":102,"accountTypeDesc":103,"profileDescription":13,"skillCount":125,"repoCount":126,"professionCount":108,"scenarioCount":127,"totalStars":128,"updatedAt":129},"01M6AC29YGCR4S2NTJFV0G8B81","openai","OpenAI","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F14957082?v=4",171,23,6,342695,"2026-11-13 04:03:41",{"accountNo":131,"login":132,"displayName":133,"avatarUrl":134,"accountType":102,"accountTypeDesc":103,"profileDescription":13,"skillCount":135,"repoCount":136,"professionCount":137,"scenarioCount":108,"totalStars":138,"updatedAt":139},"01M6AC83E6K4FDKK7HZ8WNMQKE","apache","The Apache Software Foundation","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F47359?v=4",420,75,8,298176,"2026-11-13 03:14:28",{"accountNo":141,"login":142,"displayName":143,"avatarUrl":144,"accountType":102,"accountTypeDesc":103,"profileDescription":145,"skillCount":146,"repoCount":147,"professionCount":107,"scenarioCount":108,"totalStars":148,"updatedAt":149},"01M698VYEFDM0VJBZDYYJ2T83S","google","Google","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F1342004?v=4","Google ❤️ Open Source",535,48,242366,"2026-11-13 04:17:09",{"accountNo":151,"login":152,"displayName":153,"avatarUrl":154,"accountType":102,"accountTypeDesc":103,"profileDescription":155,"skillCount":156,"repoCount":157,"professionCount":107,"scenarioCount":108,"totalStars":158,"updatedAt":159},"01M6AC83DS133TPXFSP1DHNCC6","github","GitHub","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F9919?v=4","How people build software.",940,28,238441,"2026-11-13 03:57:35",{"accountNo":161,"login":162,"displayName":163,"avatarUrl":164,"accountType":102,"accountTypeDesc":103,"profileDescription":13,"skillCount":165,"repoCount":166,"professionCount":107,"scenarioCount":108,"totalStars":167,"updatedAt":168},"01M697XGDPXJAVQ8391V2BCYTE","anthropics","Anthropic","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F76263028?v=4",674,17,231826,"2026-11-13 04:18:26",{"accountNo":170,"login":171,"displayName":172,"avatarUrl":173,"accountType":102,"accountTypeDesc":103,"profileDescription":13,"skillCount":174,"repoCount":175,"professionCount":176,"scenarioCount":108,"totalStars":177,"updatedAt":178},"01M6AC83EPDGBFN19MWYRREJD0","Significant-Gravitas","AutoGPT","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F130738209?v=4",86,2,10,188014,"2026-11-13 02:38:59",{"accountNo":180,"login":181,"displayName":182,"avatarUrl":183,"accountType":184,"accountTypeDesc":185,"profileDescription":186,"skillCount":187,"repoCount":188,"professionCount":127,"scenarioCount":108,"totalStars":189,"updatedAt":190},"01M6DJCCDDG53MTYYRTXAXFG17","garrytan","Garry Tan","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F19957?v=4","USER","个人作者","Writes software, dreams. ",324,3,174614,"2026-11-13 04:05:07",1926,9,{"skillCount":194,"professionCount":107,"scenarioCount":108,"creatorCount":191},196852,{"records":196,"total":194,"current":630,"size":631},[197,229,249,273,305,334,360,384,407,427,447,473,495,521,543,558,586,611],{"skillNo":198,"name":199,"nameZh":13,"description":200,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":209,"categories":210,"keywords":211,"publishedAt":228},"01M6AE0H7K2MMGY06Z8Q6E4PB2","app-store-optimization","Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store","davila7\u002Fclaude-code-templates","davila7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6216945?v=4","01M6ADEWWFPS191NFM0Y1EX1JH","Daniel Avila","01M6ADJHGM78PHQRD3XZTFDVKK",33418,"MIT","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fbusiness-marketing\u002Fapp-store-optimization\u002FSKILL.md",[],[212,213,214,215,216,142,217,218,219,220,221,222,223,224,225,226,227],"Optimization","app store optimization","app","store","app store","performance","toolkit","play","aso","tracking","mobile app","mobile","apple","complete","google play","for","2026-11-10 10:12:30",{"skillNo":230,"name":231,"nameZh":13,"description":232,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":233,"categories":234,"keywords":235,"publishedAt":228},"01M6AE0F1277VE8BFJKV0QZ3A8","templates","Project scaffolding templates for new applications. Use when creating new projects from scratch. Contains 12 templates for various tech stacks.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fbusiness-marketing\u002Fapp-builder\u002Ftemplates\u002FSKILL.md",[],[231,236,237,238,239,240,241,242,243,244,245,227,246,247,248],"applications","projects","grep","read","use","scaffolding","project","tech","From Scratch","project scaffolding","scratch","when","new",{"skillNo":250,"name":251,"nameZh":13,"description":252,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":253,"categories":254,"keywords":258,"publishedAt":228},"01M6AE0DCNGCB1H28W18KMG956","app-builder","Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fbusiness-marketing\u002Fapp-builder\u002FSKILL.md",[255],{"categoryNo":256,"categoryName":257,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000023","Skill与智能体开发",[259,260,214,236,261,262,238,239,263,264,265,266,267,268,269,242,270,271,243,272],"app builder","builder","Bash","stack","write","edit","orchestrator","language","main","natural language","coordinates","full","type","requests",{"skillNo":274,"name":275,"nameZh":13,"description":276,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":277,"categories":278,"keywords":286,"publishedAt":228},"01M6AE0ADEEV5P08PF5XPBC206","analytics-tracking","When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions \"set up tracking,\" \"GA4,\" \"Google Analytics,\" \"conversion tracking,\" \"event tracking,\" \"UTM parameters,\" \"tag manager,\" \"GTM,\" \"analytics implementation,\" or \"tracking plan.\" For A\u002FB test measurement, see ab-test-setup.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fbusiness-marketing\u002Fanalytics-tracking\u002FSKILL.md",[279,282,285],{"categoryNo":280,"categoryName":281,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":283,"categoryName":284,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000013","分析与可视化",{"categoryNo":23,"categoryName":24,"taxonomyType":6,"taxonomyTypeDesc":7},[287,288,221,142,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,227,247],"analytics","analytics tracking","test","setup","audit","google analytics","SET","improve","plan","up","conversion","ga4","gtm","ab","event","utm","measurement","manager",{"skillNo":306,"name":307,"nameZh":13,"description":308,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":309,"categories":310,"keywords":315,"publishedAt":228},"01M6AE08BN1FM1KN28EGRJJFGW","ai-wrapper-product","Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. Not just 'ChatGPT but different' - products that solve specific problems with AI. Covers prompt engineering for products, cost management, rate limiting, and building defensible AI businesses. Use when: AI wrapper, GPT product, AI tool, wrap AI, AI SaaS.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fbusiness-marketing\u002Fai-wrapper-product\u002FSKILL.md",[311,312],{"categoryNo":256,"categoryName":257,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":313,"categoryName":314,"taxonomyType":6,"taxonomyTypeDesc":7},"01JBSEEDCAT000000000000031","产品经理",[316,317,318,319,320,321,122,132,322,323,324,325,326,240,327,328,329,330,331,227,332,333,247],"product","ai wrapper product","Wrapper","prompt engineering","cost management","chatgpt","gpt","engineering","Tools","tool","just","solve","expert","but","people","pay","spawner","rate",{"skillNo":335,"name":336,"nameZh":13,"description":337,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":338,"categories":339,"keywords":342,"publishedAt":228},"01M6AE05QMTZXTPASG2MK76692","ai-product","Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production.  This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fbusiness-marketing\u002Fai-product\u002FSKILL.md",[340,341],{"categoryNo":256,"categoryName":257,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":313,"categoryName":314,"taxonomyType":6,"taxonomyTypeDesc":7},[316,343,319,344,345,346,347,348,132,349,350,351,323,212,352,353,354,355,240,356,357,358,359,332,247],"ai product","architecture","cost optimization","rag","code","ux","file","demo","integration","Production","ship","prompt","question","trust","patterns","llm integration","you",{"skillNo":361,"name":362,"nameZh":13,"description":363,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":364,"categories":365,"keywords":367,"publishedAt":228},"01M6AE03P13J8BV3GAA281MH9X","ai-directory-submitter","Lists an AI product on free AI directories, launch sites and MCP or agent directories, one at a time, from FalcoScan's checked list of free directories, and keeps a record of each submission. Use when the user wants to list, launch or promote an AI tool, SaaS, MCP server or agent on directories, or asks where to submit their product.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fbusiness-marketing\u002Fai-directory-submitter\u002FSKILL.md",[366],{"categoryNo":256,"categoryName":257,"taxonomyType":53,"taxonomyTypeDesc":54},[368,369,370,371,372,316,373,374,343,375,325,376,240,377,378,379,380,381,382,383,247],"directory","ai directory submitter","MCP","mcp server","launch","promote","server","saas","one at a time","record","time","free","sites","submit","directories","submission",{"skillNo":385,"name":386,"nameZh":13,"description":387,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":388,"categories":389,"keywords":391,"publishedAt":228},"01M6AE01PXBD1AXS6RRPW83N9F","agile-product-owner","Agile product ownership toolkit for Senior Product Owner including INVEST-compliant user story generation, sprint planning, backlog management, and velocity tracking. Use for story writing, sprint planning, stakeholder communication, and agile ceremonies.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fbusiness-marketing\u002Fagile-product-owner\u002FSKILL.md",[390],{"categoryNo":313,"categoryName":314,"taxonomyType":6,"taxonomyTypeDesc":7},[392,316,393,394,395,218,396,397,221,398,399,240,400,401,402,403,404,405,227,406],"agile","agile product owner","writing","backlog management","planning","communication","management","user story","backlog","velocity","generation","sprint planning","sprint","agile ceremonies","senior",{"skillNo":408,"name":409,"nameZh":13,"description":410,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":411,"categories":412,"keywords":414,"publishedAt":228},"01M6ADZYSDZ5VBXNEF99239G3A","ab-test-setup","When the user wants to plan, design, or implement an A\u002FB test or experiment. Also use when the user mentions \"A\u002FB test,\" \"split test,\" \"experiment,\" \"test this change,\" \"variant copy,\" \"multivariate test,\" or \"hypothesis.\" For tracking implementation, see analytics-tracking.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fbusiness-marketing\u002Fab-test-setup\u002FSKILL.md",[413],{"categoryNo":280,"categoryName":281,"taxonomyType":53,"taxonomyTypeDesc":54},[289,290,415,416,300,417,418,419,420,287,421,295,240,422,423,424,227,425,426,247],"ab test setup","test setup","ab test","design","implement","change","hypothesis","experiment","implementation","split","to plan","variant",{"skillNo":428,"name":429,"nameZh":13,"description":430,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":431,"categories":432,"keywords":435,"publishedAt":228},"01M6ADZVD39FV3G7HKHTJF7CDV","google-analytics","Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics\u002FSKILL.md",[433,434],{"categoryNo":283,"categoryName":284,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":23,"categoryName":24,"taxonomyType":6,"taxonomyTypeDesc":7},[142,287,292,436,217,437,438,212,439,440,441,442,240,297,357,443,444,445,446,247],"review","metrics","website","data","analysis","performance optimization","analyze","traffic analysis","about","traffic","data-driven",{"skillNo":448,"name":449,"nameZh":13,"description":450,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":451,"categories":452,"keywords":454,"publishedAt":228},"01M6ADZRXN3V2A428Y4TSXVCTZ","voice-ai-development","Expert in building voice AI applications - from real-time voice agents to voice-enabled apps. Covers OpenAI Realtime API, Vapi for voice agents, Deepgram for transcription, ElevenLabs for synthesis, LiveKit for real-time infrastructure, and WebRTC fundamentals. Knows how to build low-latency, production-ready voice experiences. Use when: voice ai, voice agent, speech to text, text to speech, realtime voice.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fai-research\u002Fvoice-ai-development\u002FSKILL.md",[453],{"categoryNo":256,"categoryName":257,"taxonomyType":53,"taxonomyTypeDesc":54},[455,456,457,458,459,460,122,461,462,132,352,463,464,465,466,467,328,468,378,469,470,471,332,247,472],"development","voice ai development","voice","ai development","realtime","infrastructure","realtime api","speech","voice agents","api","how","text","ready","webrtc","apps","how to","production-ready","Low-Latency",{"skillNo":474,"name":475,"nameZh":13,"description":476,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":477,"categories":478,"keywords":481,"publishedAt":228},"01M6ADZP9C11J3VAS78YBKKRA6","voice-agents","Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance.  This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fai-research\u002Fvoice-agents\u002FSKILL.md",[479,480],{"categoryNo":256,"categoryName":257,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":5,"categoryName":8,"taxonomyType":6,"taxonomyTypeDesc":7},[463,457,482,459,122,461,462,132,483,484,464,485,486,326,487,488,489,490,491,492,493,494,332],"debug","flow","pipeline","tts","speech recognition","challenge","conversation","stt","latency","interaction","natural conversation","architectures","openai realtime",{"skillNo":496,"name":497,"nameZh":13,"description":498,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":499,"categories":500,"keywords":501,"publishedAt":228},"01M6ADZKGTAW2S1YPP1YCHRN01","tokenization-sentencepiece","Language-independent tokenizer treating text as raw Unicode. Supports BPE and Unigram algorithms. Fast (50k sentences\u002Fsec), lightweight (6MB memory), deterministic vocabulary. Used by T5, ALBERT, XLNet, mBART. Train on raw text without pre-tokenization. Use when you need multilingual support, CJK languages, or reproducible tokenization.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fai-research\u002Ftokenization-sentencepiece\u002FSKILL.md",[],[502,503,504,142,505,506,507,508,509,510,466,511,512,513,514,515,516,517,518,519,520,359,247],"tokenization sentencepiece","Tokenization","sentencepiece","memory","research","support","fast","Reproducible","Transformers","multilingual","deterministic","algorithms","as","cjk","BPE","Unigram","Language-Independent","CJK Languages","Unicode",{"skillNo":522,"name":523,"nameZh":13,"description":524,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":525,"categories":526,"keywords":530,"publishedAt":228},"01M6ADZGSATBNJ9KV4QF7M1DCH","tokenization-huggingface-tokenizers","Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in \u003C20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding\u002Ftruncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fai-research\u002Ftokenization-huggingface-tokenizers\u002FSKILL.md",[527],{"categoryNo":528,"categoryName":529,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000021","资料检索与研究",[531,532,533,503,217,534,506,535,508,510,352,536,513,537,516,538,517,539,540,541,359,542,247],"HuggingFace","tokenization huggingface tokenizers","huggingface tokenizers","rust","training","alignment","high-performance","WordPiece","Fast Tokenization","Custom Tokenizer","Alignment Tracking","track",{"skillNo":544,"name":545,"nameZh":13,"description":546,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":547,"categories":548,"keywords":550,"publishedAt":228},"01M6ADZEZ328JHKB6VRW1CC3J4","subagent-driven-development","Use when executing implementation plans with independent tasks in the current session","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fai-research\u002Fsubagent-driven-development\u002FSKILL.md",[549],{"categoryNo":256,"categoryName":257,"taxonomyType":53,"taxonomyTypeDesc":54},[455,551,552,553,554,555,240,423,556,557,247],"subagent driven development","subagent","driven","tasks","session","plans","with",{"skillNo":559,"name":560,"nameZh":13,"description":561,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":562,"categories":563,"keywords":564,"publishedAt":228},"01M6ADZBVV6Z7TTGE1WS8Z02QT","safety-alignment-nemo-guardrails","NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input\u002Foutput validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fai-research\u002Fsafety-alignment-nemo-guardrails\u002FSKILL.md",[],[565,566,567,568,569,536,506,570,571,572,573,352,574,575,576,577,578,579,580,581,467,582,583,471,584,585],"NeMo","Safety Alignment","Guardrails","safety alignment nemo guardrails","Safety","validation","framework","gpu","NVIDIA","NeMo Guardrails","Jailbreak Detection","Colang","Runtime Safety","Hallucination Detection","PII Filtering","pii","rails","LLM Applications","fact-checking","features","dsl",{"skillNo":587,"name":588,"nameZh":13,"description":589,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":590,"categories":591,"keywords":594,"publishedAt":228},"01M6ADZ8459C9HYVQ61T87H2P2","safety-alignment-llamaguard","Meta's 7-8B specialized moderation model for LLM input\u002Foutput filtering. 6 safety categories - violence\u002Fhate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fai-research\u002Fsafety-alignment-llamaguard\u002FSKILL.md",[592,593],{"categoryNo":256,"categoryName":257,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":30,"categoryName":31,"taxonomyType":6,"taxonomyTypeDesc":7},[595,569,536,506,596,396,597,565,531,598,510,566,599,600,601,567,602,603,604,605,574,606,607,608,609,610],"safety alignment llamaguard","deploy","content","vLLM","LlamaGuard","Content Moderation","Meta","Safety Classification","Input Filtering","Output Filtering","AI Safety","model","specialized","self","input","categories",{"skillNo":612,"name":613,"nameZh":13,"description":614,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":615,"categories":616,"keywords":617,"publishedAt":228},"01M6ADZ5WRPA2K2XZQ8AT1FERQ","safety-alignment-constitutional-ai","Anthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with self-critique\u002Frevision, then RLAIF (RL from AI Feedback). Use for safety alignment, reducing harmful outputs without human labels. Powers Claude's safety system.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fai-research\u002Fsafety-alignment-constitutional-ai\u002FSKILL.md",[],[618,566,569,536,619,506,535,510,605,620,621,608,622,623,624,227,625,626,627,628,629],"safety alignment constitutional ai","Constitutional AI","critique","feedback","human","revision","orchestra","improvement","labels","phase","supervised","Supervised Learning",185,18]