[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7BMS9NBC0HV47FJCY2YFKZP":3,"skill-same:01M7BMS9NBC0HV47FJCY2YFKZP":52},{"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":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":26,"commitSha":27,"skillDirectory":28,"forksCount":14,"repositoryHtmlUrl":29,"repositoryHomepageUrl":6,"ownerHtmlUrl":30,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":31,"install":32,"resources":45},"01M7BMS9NBC0HV47FJCY2YFKZP","dashboard",null,"Dark-themed cloud-platform aesthetic with modular grids, glass-like panels, and strong data hierarchy for productivity dashboards.","origin-labs-ai\u002Fcode","origin-labs-ai","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F347654492?v=4","01M7B0MAD1JMVZ6ME9891AYYYG","Origin","01M7B0MADP3AZS42R4NEF1JTS8",0,"MIT","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fingot\u002Fapps\u002Fcli\u002Fpackages\u002Fbundled-skills\u002Fskills\u002Fdesign\u002Fdesign-systems\u002Fstyle-skills\u002Fdashboard\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: dashboard\ndescription: Dark-themed cloud-platform aesthetic with modular grids, glass-like panels, and strong data hierarchy for productivity dashboards.\nlicense: MIT\nmetadata:\n  author: typeui.sh\n---\n\n\u003C!-- TYPEUI_SH_MANAGED_START -->\n# Dashboard Design System Skill (Universal)\n\n## Mission\nYou are an expert design-system guideline author for Dashboard.\nCreate practical, implementation-ready guidance that can be directly used by engineers and designers.\n\n## Brand\nDashboard design emphasizes grids, modular components, and strong visual hierarchy to present complex data in a clear and accessible way. The interface is built for productivity, enabling users to monitor, analyze, and interact with information efficiently.\n\n## Style Foundations\n- Visual style: modern, clean, cloud-platform aesthetic (Heroku\u002FVercel\u002FGitHub inspired), dark theme, subtle gradients, soft shadows, glass-like panels, rounded components\n- Typography scale: 12\u002F14\u002F16\u002F20\u002F24\u002F32 | Fonts: primary=IBM Plex Sans, display=IBM Plex Sans, mono=IBM Plex Sans | weights=100, 200, 300, 400, 500, 600, 700, 800, 900\n- Color palette: primary, neutral, success, warning, danger | Tokens: primary=#0C5CAB, secondary=#0a4a8a, success=#10b981, warning=#f59e0b, danger=#ef4444, surface=#09090b, text=#fafafa\n- Spacing scale: 8pt baseline grid\n\n\n## Accessibility\nWCAG 2.2 AA, keyboard-first interactions, visible focus states, semantic HTML before ARIA, screen-reader tested labels, reduced-motion support, 44px+ touch targets, high-contrast support\n\n## Writing Tone\nconcise, confident, helpful, clear, friendly, professional, action-oriented, low-jargon\n\n## Rules: Do\n- prefer semantic tokens over raw values\n- preserve visual hierarchy\n- keep interaction states explicit\n- design for empty\u002Floading\u002Ferror states\n- ensure responsive behavior by default\n- document accessibility rationale\n\n## Rules: Don't\n- avoid low contrast text\n- avoid inconsistent spacing rhythm\n- avoid decorative motion without purpose\n- avoid ambiguous labels\n- avoid mixing multiple visual metaphors\n- avoid inaccessible hit areas\n\n## Expected Behavior\n- Follow the foundations first, then component consistency.\n- When uncertain, prioritize accessibility and clarity over novelty.\n- Provide concrete defaults and explain trade-offs when alternatives are possible.\n- Keep guidance opinionated, concise, and implementation-focused.\n\n## Guideline Authoring Workflow\n1. Restate the design intent in one sentence before proposing rules.\n2. Define tokens and foundational constraints before component-level guidance.\n3. Specify component anatomy, states, variants, and interaction behavior.\n4. Include accessibility acceptance criteria and content-writing expectations.\n5. Add anti-patterns and migration notes for existing inconsistent UI.\n6. End with a QA checklist that can be executed in code review.\n\n## Required Output Structure\nWhen generating design-system guidance, use this structure:\n- Context and goals\n- Design tokens and foundations\n- Component-level rules (anatomy, variants, states, responsive behavior)\n- Accessibility requirements and testable acceptance criteria\n- Content and tone standards with examples\n- Anti-patterns and prohibited implementations\n- QA checklist\n\n## Component Rule Expectations\n- Define required states: default, hover, focus-visible, active, disabled, loading, error (as relevant).\n- Describe interaction behavior for keyboard, pointer, and touch.\n- State spacing, typography, and color-token usage explicitly.\n- Include responsive behavior and edge cases (long labels, empty states, overflow).\n\n## Quality Gates\n- No rule should depend on ambiguous adjectives alone; anchor each rule to a token, threshold, or example.\n- Every accessibility statement must be testable in implementation.\n- Prefer system consistency over one-off local optimizations.\n- Flag conflicts between aesthetics and accessibility, then prioritize accessibility.\n\n## Example Constraint Language\n- Use \"must\" for non-negotiable rules and \"should\" for recommendations.\n- Pair every do-rule with at least one concrete don't-example.\n- If introducing a new pattern, include migration guidance for existing components.\n\n\u003C!-- TYPEUI_SH_MANAGED_END -->\n","\u003C!-- TYPEUI_SH_MANAGED_START -->\n# Dashboard Design System Skill (Universal)\n\n## Mission\nYou are an expert design-system guideline author for Dashboard.\nCreate practical, implementation-ready guidance that can be directly used by engineers and designers.\n\n## Brand\nDashboard design emphasizes grids, modular components, and strong visual hierarchy to present complex data in a clear and accessible way. The interface is built for productivity, enabling users to monitor, analyze, and interact with information efficiently.\n\n## Style Foundations\n- Visual style: modern, clean, cloud-platform aesthetic (Heroku\u002FVercel\u002FGitHub inspired), dark theme, subtle gradients, soft shadows, glass-like panels, rounded components\n- Typography scale: 12\u002F14\u002F16\u002F20\u002F24\u002F32 | Fonts: primary=IBM Plex Sans, display=IBM Plex Sans, mono=IBM Plex Sans | weights=100, 200, 300, 400, 500, 600, 700, 800, 900\n- Color palette: primary, neutral, success, warning, danger | Tokens: primary=#0C5CAB, secondary=#0a4a8a, success=#10b981, warning=#f59e0b, danger=#ef4444, surface=#09090b, text=#fafafa\n- Spacing scale: 8pt baseline grid\n\n\n## Accessibility\nWCAG 2.2 AA, keyboard-first interactions, visible focus states, semantic HTML before ARIA, screen-reader tested labels, reduced-motion support, 44px+ touch targets, high-contrast support\n\n## Writing Tone\nconcise, confident, helpful, clear, friendly, professional, action-oriented, low-jargon\n\n## Rules: Do\n- prefer semantic tokens over raw values\n- preserve visual hierarchy\n- keep interaction states explicit\n- design for empty\u002Floading\u002Ferror states\n- ensure responsive behavior by default\n- document accessibility rationale\n\n## Rules: Don't\n- avoid low contrast text\n- avoid inconsistent spacing rhythm\n- avoid decorative motion without purpose\n- avoid ambiguous labels\n- avoid mixing multiple visual metaphors\n- avoid inaccessible hit areas\n\n## Expected Behavior\n- Follow the foundations first, then component consistency.\n- When uncertain, prioritize accessibility and clarity over novelty.\n- Provide concrete defaults and explain trade-offs when alternatives are possible.\n- Keep guidance opinionated, concise, and implementation-focused.\n\n## Guideline Authoring Workflow\n1. Restate the design intent in one sentence before proposing rules.\n2. Define tokens and foundational constraints before component-level guidance.\n3. Specify component anatomy, states, variants, and interaction behavior.\n4. Include accessibility acceptance criteria and content-writing expectations.\n5. Add anti-patterns and migration notes for existing inconsistent UI.\n6. End with a QA checklist that can be executed in code review.\n\n## Required Output Structure\nWhen generating design-system guidance, use this structure:\n- Context and goals\n- Design tokens and foundations\n- Component-level rules (anatomy, variants, states, responsive behavior)\n- Accessibility requirements and testable acceptance criteria\n- Content and tone standards with examples\n- Anti-patterns and prohibited implementations\n- QA checklist\n\n## Component Rule Expectations\n- Define required states: default, hover, focus-visible, active, disabled, loading, error (as relevant).\n- Describe interaction behavior for keyboard, pointer, and touch.\n- State spacing, typography, and color-token usage explicitly.\n- Include responsive behavior and edge cases (long labels, empty states, overflow).\n\n## Quality Gates\n- No rule should depend on ambiguous adjectives alone; anchor each rule to a token, threshold, or example.\n- Every accessibility statement must be testable in implementation.\n- Prefer system consistency over one-off local optimizations.\n- Flag conflicts between aesthetics and accessibility, then prioritize accessibility.\n\n## Example Constraint Language\n- Use \"must\" for non-negotiable rules and \"should\" for recommendations.\n- Pair every do-rule with at least one concrete don't-example.\n- If introducing a new pattern, include migration guidance for existing components.\n\n\u003C!-- TYPEUI_SH_MANAGED_END -->\n",{"name":5,"license":15,"metadata":24,"description":7},{"author":25},"typeui.sh","main","1e72c52e0f3ffd72fbc6ba994fda0f4a6d63911a","windows\u002Fingot\u002Fapps\u002Fcli\u002Fpackages\u002Fbundled-skills\u002Fskills\u002Fdesign\u002Fdesign-systems\u002Fstyle-skills\u002Fdashboard","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai","2026-11-14 20:35:25",{"source":8,"skillName":5,"commands":33,"prompt":43,"zipAvailable":44},[34,37,40],{"tool":35,"command":36},"npx","npx skills add origin-labs-ai\u002Fcode --skill dashboard",{"tool":38,"command":39},"bunx","bunx skills add origin-labs-ai\u002Fcode --skill dashboard",{"tool":41,"command":42},"pnpm","pnpm dlx skills add origin-labs-ai\u002Fcode --skill dashboard","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fingot\u002Fapps\u002Fcli\u002Fpackages\u002Fbundled-skills\u002Fskills\u002Fdesign\u002Fdesign-systems\u002Fstyle-skills\u002Fdashboard\u002FSKILL.md",true,[46],{"path":47,"resourceType":48,"resourceTypeDesc":49,"sizeBytes":50,"sourceHtmlUrl":51},"DESIGN.md","REFERENCE","参考文档",1716,"https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fingot\u002Fapps\u002Fcli\u002Fpackages\u002Fbundled-skills\u002Fskills\u002Fdesign\u002Fdesign-systems\u002Fstyle-skills\u002Fdashboard\u002FDESIGN.md",[53,61,69,77,85,94],{"skillNo":54,"name":55,"nameZh":6,"description":56,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":57,"sourceHtmlUrl":58,"categories":59,"keywords":60,"publishedAt":19},"01M7BP6Z7NBQXMB8Y5ZRR7PGCF","web-search","Implement web search capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to search for real-time information from the web, retrieve up-to-date content beyond the knowledge cutoff, or find the latest news and data. Returns structured search results with URLs, snippets, and metadata.","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fsonar\u002Fmerger\u002Fcode-fusion-dead-20261101\u002Fskills\u002Fweb-search\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fsonar\u002Fmerger\u002Fcode-fusion-dead-20261101\u002Fskills\u002Fweb-search\u002FSKILL.md",[],[],{"skillNo":62,"name":63,"nameZh":6,"description":64,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":65,"sourceHtmlUrl":66,"categories":67,"keywords":68,"publishedAt":19},"01M7BP6T13CWYHZSHGYG0RT885","web-reader","Implement web page content extraction capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to scrape web pages, extract article content, retrieve page metadata, or build applications that process web content. Supports automatic content extraction with title, HTML, and publication time retrieval.","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fsonar\u002Fmerger\u002Fcode-fusion-dead-20261101\u002Fskills\u002Fweb-reader\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fsonar\u002Fmerger\u002Fcode-fusion-dead-20261101\u002Fskills\u002Fweb-reader\u002FSKILL.md",[],[],{"skillNo":70,"name":71,"nameZh":6,"description":72,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":73,"sourceHtmlUrl":74,"categories":75,"keywords":76,"publishedAt":19},"01M7BP6GM9Z301PPT4ZRV049AN","video-understand","Implement specialized video understanding capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to analyze video content, understand motion and temporal sequences, extract information from video frames, describe video scenes, or perform video-based AI analysis. Optimized for MP4, AVI, MOV, and other common video formats.","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fsonar\u002Fmerger\u002Fcode-fusion-dead-20261101\u002Fskills\u002Fvideo-understand\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fsonar\u002Fmerger\u002Fcode-fusion-dead-20261101\u002Fskills\u002Fvideo-understand\u002FSKILL.md",[],[],{"skillNo":78,"name":79,"nameZh":6,"description":80,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":81,"sourceHtmlUrl":82,"categories":83,"keywords":84,"publishedAt":19},"01M7BP6ANRHQ1K7PVS11RBZCC7","Video Generation","Implement AI-powered video generation capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to generate videos from text prompts or images, create video content programmatically, or build applications that produce video outputs. Supports asynchronous task management with status polling and result retrieval.","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fsonar\u002Fmerger\u002Fcode-fusion-dead-20261101\u002Fskills\u002Fvideo-generation\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fsonar\u002Fmerger\u002Fcode-fusion-dead-20261101\u002Fskills\u002Fvideo-generation\u002FSKILL.md",[],[],{"skillNo":86,"name":87,"nameZh":6,"description":88,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":89,"licenseFileUrl":90,"sourceHtmlUrl":91,"categories":92,"keywords":93,"publishedAt":19},"01M7BP56W5SX2MMJWKMJVC66F0","skill-creator","Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fsonar\u002Fmerger\u002Fcode-fusion-dead-20261101\u002Fskills\u002Fskill-creator\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fsonar\u002Fmerger\u002Fcode-fusion-dead-20261101\u002Fskills\u002Fskill-creator\u002FSKILL.md",[],[],{"skillNo":95,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":89,"licenseFileUrl":6,"sourceHtmlUrl":98,"categories":99,"keywords":100,"publishedAt":19},"01M7BP503HPG0DBCN4K0JKCA88","seo-content-writer","Use when the user asks to \"write SEO content\", \"create a blog post\", \"write an article\", \"content writing\", \"draft optimized content\", \"write me an article\", \"create a blog post about\", \"help me write SEO content\", or \"draft content for\". Creates high-quality, SEO-optimized content that ranks in search engines. Applies on-page SEO best practices, keyword optimization, and content structure for maximum visibility and engagement. For AI citation optimization, see geo-content-optimizer. For updating existing content, see content-refresher.","https:\u002F\u002Fgithub.com\u002Forigin-labs-ai\u002Fcode\u002Fblob\u002Fmain\u002Fwindows\u002Fsonar\u002Fmerger\u002Fcode-fusion-dead-20261101\u002Fskills\u002Fseo-content-writer\u002FSKILL.md",[],[]]