[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6JKBAT01MJHRSA02K4AMCSW":3,"skill-same:01M6JKBAT01MJHRSA02K4AMCSW":70},{"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":23,"publishedAt":40,"linkOnly":41,"markdownContent":42,"markdownBody":43,"frontMatter":44,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":53,"ownerHtmlUrl":54,"ownerBlogUrl":55,"ownerDescription":6,"updatedAt":56,"install":57,"resources":69},"01M6JKBAT01MJHRSA02K4AMCSW","prototype",null,"Rapid prototyping workflow. Skips normal standards to quickly validate a game concept or mechanic. Produces throwaway code and a structured prototype report.","LongLeo287\u002FOmniClaw","LongLeo287","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F141803367?v=4","01M6JK75C62VCNZKR5BRZ386YV","LongLeo","01M6JK75GQ78TSP1ZPXNKK3MCH",9,"MIT","https:\u002F\u002Fgithub.com\u002FLongLeo287\u002FOmniClaw\u002Fblob\u002Fmain\u002Fbrain\u002Fknowledge\u002Frepositories\u002Fclaude_code_game_studios\u002F.claude\u002Fskills\u002Fprototype\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[5,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39],"read","concept","true","mechanic","prototyping","structured","standards","edit","write","grep","game","Bash","report","code","validate","workflow","2026-11-10 10:12:30",false,"---\nname: prototype\ndescription: \"Rapid prototyping workflow. Skips normal standards to quickly validate a game concept or mechanic. Produces throwaway code and a structured prototype report.\"\nargument-hint: \"[concept-description]\"\nuser-invocable: true\nallowed-tools: Read, Glob, Grep, Write, Edit, Bash\n---\n\nWhen this skill is invoked:\n\n1. **Read the concept description** from the argument. Identify the core\n   question this prototype must answer. If the concept is vague, state the\n   question explicitly before proceeding.\n\n2. **Read CLAUDE.md** for project context and the current tech stack. Understand\n   what engine, language, and frameworks are in use so the prototype is built\n   with compatible tooling.\n\n3. **Create a prototype plan**: Define in 3-5 bullet points what the minimum\n   viable prototype looks like. What is the core question? What is the absolute\n   minimum code needed to answer it? What can be skipped?\n\n4. **Create the prototype directory**: `prototypes\u002F[concept-name]\u002F` where\n   `[concept-name]` is a short, kebab-case identifier derived from the concept.\n\n5. **Implement the prototype** in the isolated directory. Every file must begin\n   with:\n   ```\n   \u002F\u002F PROTOTYPE - NOT FOR PRODUCTION\n   \u002F\u002F Question: [Core question being tested]\n   \u002F\u002F Date: [Current date]\n   ```\n   Standards are intentionally relaxed:\n   - Hardcode values freely\n   - Use placeholder assets\n   - Skip error handling\n   - Use the simplest approach that works\n   - Copy code rather than importing from production\n\n6. **Test the concept**: Run the prototype. Observe behavior. Collect any\n   measurable data (frame times, interaction counts, feel assessments).\n\n7. **Generate the Prototype Report** and save it to\n   `prototypes\u002F[concept-name]\u002FREPORT.md`:\n\n```markdown\n## Prototype Report: [Concept Name]\n\n### Hypothesis\n[What we expected to be true -- the question we set out to answer]\n\n### Approach\n[What we built, how long it took, what shortcuts we took]\n\n### Result\n[What actually happened -- specific observations, not opinions]\n\n### Metrics\n[Any measurable data collected during testing]\n- Frame time: [if relevant]\n- Feel assessment: [subjective but specific -- \"response felt sluggish at\n  200ms delay\" not \"felt bad\"]\n- Player action counts: [if relevant]\n- Iteration count: [how many attempts to get it working]\n\n### Recommendation: [PROCEED \u002F PIVOT \u002F KILL]\n\n[One paragraph explaining the recommendation with evidence]\n\n### If Proceeding\n[What needs to change for a production-quality implementation]\n- Architecture requirements\n- Performance targets\n- Scope adjustments from the original design\n- Estimated production effort\n\n### If Pivoting\n[What alternative direction the results suggest]\n\n### If Killing\n[Why this concept does not work and what we should do instead]\n\n### Lessons Learned\n[Discoveries that affect other systems or future work]\n```\n\n8. **Output a summary** to the user with: the core question, the result, and\n   the recommendation. Link to the full report at\n   `prototypes\u002F[concept-name]\u002FREPORT.md`.\n\n### Important Constraints\n\n- Prototype code must NEVER import from production source files\n- Production code must NEVER import from prototype directories\n- If the recommendation is PROCEED, the production implementation must be\n  written from scratch -- prototype code is not refactored into production\n- Total prototype effort should be timeboxed to 1-3 days equivalent of work\n- If the prototype scope starts growing, stop and reassess whether the\n  question can be simplified\n","When this skill is invoked:\n\n1. **Read the concept description** from the argument. Identify the core\n   question this prototype must answer. If the concept is vague, state the\n   question explicitly before proceeding.\n\n2. **Read CLAUDE.md** for project context and the current tech stack. Understand\n   what engine, language, and frameworks are in use so the prototype is built\n   with compatible tooling.\n\n3. **Create a prototype plan**: Define in 3-5 bullet points what the minimum\n   viable prototype looks like. What is the core question? What is the absolute\n   minimum code needed to answer it? What can be skipped?\n\n4. **Create the prototype directory**: `prototypes\u002F[concept-name]\u002F` where\n   `[concept-name]` is a short, kebab-case identifier derived from the concept.\n\n5. **Implement the prototype** in the isolated directory. Every file must begin\n   with:\n   ```\n   \u002F\u002F PROTOTYPE - NOT FOR PRODUCTION\n   \u002F\u002F Question: [Core question being tested]\n   \u002F\u002F Date: [Current date]\n   ```\n   Standards are intentionally relaxed:\n   - Hardcode values freely\n   - Use placeholder assets\n   - Skip error handling\n   - Use the simplest approach that works\n   - Copy code rather than importing from production\n\n6. **Test the concept**: Run the prototype. Observe behavior. Collect any\n   measurable data (frame times, interaction counts, feel assessments).\n\n7. **Generate the Prototype Report** and save it to\n   `prototypes\u002F[concept-name]\u002FREPORT.md`:\n\n```markdown\n## Prototype Report: [Concept Name]\n\n### Hypothesis\n[What we expected to be true -- the question we set out to answer]\n\n### Approach\n[What we built, how long it took, what shortcuts we took]\n\n### Result\n[What actually happened -- specific observations, not opinions]\n\n### Metrics\n[Any measurable data collected during testing]\n- Frame time: [if relevant]\n- Feel assessment: [subjective but specific -- \"response felt sluggish at\n  200ms delay\" not \"felt bad\"]\n- Player action counts: [if relevant]\n- Iteration count: [how many attempts to get it working]\n\n### Recommendation: [PROCEED \u002F PIVOT \u002F KILL]\n\n[One paragraph explaining the recommendation with evidence]\n\n### If Proceeding\n[What needs to change for a production-quality implementation]\n- Architecture requirements\n- Performance targets\n- Scope adjustments from the original design\n- Estimated production effort\n\n### If Pivoting\n[What alternative direction the results suggest]\n\n### If Killing\n[Why this concept does not work and what we should do instead]\n\n### Lessons Learned\n[Discoveries that affect other systems or future work]\n```\n\n8. **Output a summary** to the user with: the core question, the result, and\n   the recommendation. Link to the full report at\n   `prototypes\u002F[concept-name]\u002FREPORT.md`.\n\n### Important Constraints\n\n- Prototype code must NEVER import from production source files\n- Production code must NEVER import from prototype directories\n- If the recommendation is PROCEED, the production implementation must be\n  written from scratch -- prototype code is not refactored into production\n- Total prototype effort should be timeboxed to 1-3 days equivalent of work\n- If the prototype scope starts growing, stop and reassess whether the\n  question can be simplified\n",{"name":5,"description":7,"allowed-tools":45,"argument-hint":46,"user-invocable":47},"Read, Glob, Grep, Write, Edit, Bash","[concept-description]",true,"main","c173cdffe08e788a99b91928a831b476b8434838","brain\u002Fknowledge\u002Frepositories\u002Fclaude_code_game_studios\u002F.claude\u002Fskills\u002Fprototype",0,"https:\u002F\u002Fgithub.com\u002FLongLeo287\u002FOmniClaw","https:\u002F\u002Fportfolio-longleo.vercel.app\u002Flabs\u002Fomniclaw.html","https:\u002F\u002Fgithub.com\u002FLongLeo287","https:\u002F\u002Fwww.facebook.com\u002FResourceRookie2023","2026-09-30 00:58:05",{"source":8,"skillName":5,"commands":58,"prompt":68,"zipAvailable":47},[59,62,65],{"tool":60,"command":61},"npx","npx skills add LongLeo287\u002FOmniClaw --skill prototype",{"tool":63,"command":64},"bunx","bunx skills add LongLeo287\u002FOmniClaw --skill prototype",{"tool":66,"command":67},"pnpm","pnpm dlx skills add LongLeo287\u002FOmniClaw --skill prototype","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FLongLeo287\u002FOmniClaw\u002Fblob\u002Fmain\u002Fbrain\u002Fknowledge\u002Frepositories\u002Fclaude_code_game_studios\u002F.claude\u002Fskills\u002Fprototype\u002FSKILL.md",[],[71,110,132,160,175,201],{"skillNo":72,"name":73,"nameZh":6,"description":74,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":75,"categories":76,"keywords":89,"publishedAt":40},"01M6JR0KQP4MHT32TN40D9CBFX","UI-UX Pro Max","Advanced UI\u002FUX analysis and generation skills with data-driven patterns. Python scripts (core.py, search.py) for systematic UI pattern extraction, design system generation, and component search from curated data sources.","https:\u002F\u002Fgithub.com\u002FLongLeo287\u002FOmniClaw\u002Fblob\u002Fmain\u002Fecosystem\u002Fui_components\u002Fui_ux_pro_max\u002FSKILL.md",[77,80,81,86],{"categoryNo":78,"categoryName":79,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":82,"categoryName":83,"taxonomyType":84,"taxonomyTypeDesc":85},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",{"categoryNo":87,"categoryName":88,"taxonomyType":84,"taxonomyTypeDesc":85},"01JBSEEDCAT000000000000033","数据分析师",[90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109],"ux","ui","ui ux pro max","max","pro","ui ux","design","component","search","analysis","team","rd","ui-ux","active","systematic","scripts","pattern extraction","sources","advanced","data-driven",{"skillNo":111,"name":112,"nameZh":6,"description":113,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":114,"categories":115,"keywords":117,"publishedAt":40},"01M6JR0EF5AEQHP2FSTB57H05P","shadcn-ui","Expert guidance for integrating and building applications with shadcn\u002Fui components, including component discovery, installation, customization, and best practices.","https:\u002F\u002Fgithub.com\u002FLongLeo287\u002FOmniClaw\u002Fblob\u002Fmain\u002Fecosystem\u002Fui_components\u002Fshadcn_ui\u002FSKILL.md",[116],{"categoryNo":82,"categoryName":83,"taxonomyType":84,"taxonomyTypeDesc":85},[118,91,119,120,97,121,122,123,124,100,125,126,127,103,128,129,130,131],"shadcn","shadcn ui","components","core","best practices","applications","discovery","customization","guidance","expert","installation","ui components","with","for",{"skillNo":133,"name":134,"nameZh":6,"description":135,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":136,"categories":137,"keywords":141,"publishedAt":40},"01M6JR08F51BEN17RHFYX65WVE","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\u002FLongLeo287\u002FOmniClaw\u002Fblob\u002Fmain\u002Fecosystem\u002Fskills\u002Fzustand_store_ts\u002FSKILL.md",[138],{"categoryNo":139,"categoryName":140,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,130,158,159],"zustand store ts","zustand","store","typescript","microsoft","react","create","state management","state","react state management","management","global","use","patterns","separation","middleware","action","implementing",{"skillNo":161,"name":143,"nameZh":6,"description":162,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":163,"categories":164,"keywords":165,"publishedAt":40},"01M6JR00TDMVAFFCZXZ04AN7Q7","Zustand state management guide. Use when working with store code (src\u002Fstore\u002F**), implementing actions, managing state, or creating slices. Triggers on Zustand store development, state management questions, or action implementation.","https:\u002F\u002Fgithub.com\u002FLongLeo287\u002FOmniClaw\u002Fblob\u002Fmain\u002Fecosystem\u002Fskills\u002Fzustand\u002FSKILL.md",[],[143,166,149,37,150,167,168,152,169,154,170,171,172,144,130,173,174,158,159],"development","actions","src","guide","implementation","zustand state","triggers","questions","zustand state management",{"skillNo":176,"name":177,"nameZh":6,"description":178,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":179,"categories":180,"keywords":185,"publishedAt":40},"01M6JQZSWV4KWJP112G6XHEP44","youtube_summarizer","Automatically fetch YouTube video transcripts, generate structured summaries, and send full transcripts to messaging platforms. Detects YouTube URLs and provides metadata, key insights, and downloadable transcripts.","https:\u002F\u002Fgithub.com\u002FLongLeo287\u002FOmniClaw\u002Fblob\u002Fmain\u002Fecosystem\u002Fskills\u002Fyoutube_summarizer\u002FSKILL.md",[181,184],{"categoryNo":182,"categoryName":183,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[186,187,188,189,190,191,192,193,194,195,196,29,197,198,199,200],"youtube","youtube summarizer","summarizer","generate","metadata","messaging","Video","fetch","telegram","transcription","summarization","full","insights","transcripts","summaries",{"skillNo":202,"name":203,"nameZh":6,"description":204,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":205,"categories":206,"keywords":207,"publishedAt":40},"01M6JQZN3QJB6B77JGKJD62DQT","youtube_clipper","YouTube 视频智能剪辑工具。下载视频和字幕，AI 分析生成精细章节（几分钟级别）， 用户选择片段后自动剪辑、翻译字幕为中英双语、烧录字幕到视频，并生成总结文案。 使用场景：当用户需要剪辑 YouTube 视频、生成短视频片段、制作双语字幕版本时。 关键词：视频剪辑、YouTube、字幕翻译、双语字幕、视频下载、clip video","https:\u002F\u002Fgithub.com\u002FLongLeo287\u002FOmniClaw\u002Fblob\u002Fmain\u002Fecosystem\u002Fskills\u002Fyoutube_clipper\u002FSKILL.md",[],[186,208,209,192,35,210,211,212,213,214,24,32,215,216,217,218,219],"clipper","youtube clipper","下载","视频","生成","关键词","翻译","clip","总结","工具","文案","sonnet"]