[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M731X6T80947QPFX5VSTK65W":3,"skill-same:01M731X6T80947QPFX5VSTK65W":51},{"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":27,"commitSha":28,"skillDirectory":29,"forksCount":30,"repositoryHtmlUrl":31,"repositoryHomepageUrl":32,"ownerHtmlUrl":33,"ownerBlogUrl":34,"ownerDescription":35,"updatedAt":36,"install":37,"resources":50},"01M731X6T80947QPFX5VSTK65W","design--editorial",null,"Magazine-inspired editorial layout with refined serif typography, structured grids, and elegant reading experiences.","Horonomos-laps\u002FYana-AI","Horonomos-laps","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F355299122?v=4","01M76B3QPXE88ET2SQPDPVATZT"," Horonomos-laps","01M72ZQRJPCYPSSWT4D00VJR2A",13,"MIT","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fdesign--editorial\u002FSKILL.md",[],[],"2026-11-11 15:11:14",false,"---\nname: design--editorial\ndescription: >-\n  Magazine-inspired editorial layout with refined serif typography, structured grids, and elegant reading experiences.\norigin: \"github.com\u002Fbergside\u002Fawesome-design-skills (skill: editorial)\"\nlicense: MIT\nversion: \"1.0.0\"\ncompatibility: \"yana-ai >= 0.14.0\"\n---\n\n\u003C!-- TYPEUI_SH_MANAGED_START -->\n# Editorial Design System Skill (Universal)\n\n## Mission\nYou are an expert design-system guideline author for Editorial.\nCreate practical, implementation-ready guidance that can be directly used by engineers and designers.\n\n## Brand\n\n\n## Style Foundations\n- Visual style: modern, editorial\n- Typography scale: 14\u002F16\u002F18\u002F24\u002F32\u002F40 | Fonts: primary=Gelasio, display=Gelasio, mono=Ubuntu Mono | weights=100, 200, 300, 400, 500, 600, 700, 800, 900\n- Color palette: primary, secondary, neutral, success | Tokens: primary=#111111, secondary=#f1f1f1, success=#16A34A, warning=#D97706, danger=#DC2626, surface=#FFFFFF, text=#111827\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 ambiguous labels\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# Editorial Design System Skill (Universal)\n\n## Mission\nYou are an expert design-system guideline author for Editorial.\nCreate practical, implementation-ready guidance that can be directly used by engineers and designers.\n\n## Brand\n\n\n## Style Foundations\n- Visual style: modern, editorial\n- Typography scale: 14\u002F16\u002F18\u002F24\u002F32\u002F40 | Fonts: primary=Gelasio, display=Gelasio, mono=Ubuntu Mono | weights=100, 200, 300, 400, 500, 600, 700, 800, 900\n- Color palette: primary, secondary, neutral, success | Tokens: primary=#111111, secondary=#f1f1f1, success=#16A34A, warning=#D97706, danger=#DC2626, surface=#FFFFFF, text=#111827\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 ambiguous labels\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,"origin":24,"license":15,"version":25,"description":7,"compatibility":26},"github.com\u002Fbergside\u002Fawesome-design-skills (skill: editorial)","1.0.0","yana-ai >= 0.14.0","main","481dcd7dd2e288b9d627a2bd017db70e64e6c6fa",".claude\u002Fskills\u002Fdesign--editorial",2,"https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI","https:\u002F\u002Fyana.vutam.link\u002F","https:\u002F\u002Fgithub.com\u002FHoronomos-laps","https:\u002F\u002Fyana.vutam.link","An open-source governed runtime & execution environment for multi-agent AI systems.","2026-11-14 13:24:09",{"source":8,"skillName":5,"commands":38,"prompt":48,"zipAvailable":49},[39,42,45],{"tool":40,"command":41},"npx","npx skills add Horonomos-laps\u002FYana-AI --skill design--editorial",{"tool":43,"command":44},"bunx","bunx skills add Horonomos-laps\u002FYana-AI --skill design--editorial",{"tool":46,"command":47},"pnpm","pnpm dlx skills add Horonomos-laps\u002FYana-AI --skill design--editorial","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fdesign--editorial\u002FSKILL.md",true,[],[52,59,67,75,83,91],{"skillNo":53,"name":54,"nameZh":6,"description":55,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":56,"categories":57,"keywords":58,"publishedAt":19},"01M735GKET5YVYKAY62W2P5YXB","openai--sentry--sentry","Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fopenai--sentry--sentry\u002FSKILL.md",[],[],{"skillNo":60,"name":61,"nameZh":6,"description":62,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":63,"licenseFileUrl":6,"sourceHtmlUrl":64,"categories":65,"keywords":66,"publishedAt":19},"01M73DCAP83T17HY7SMGK7MGFE","ito-basket-compare","Compare Itô prediction-market baskets against a user's knowledge base, portfolio notes, financial context, watchlist, or research thesis. Use for read-only basket comparison and gap analysis without investment advice or live trading.","Apache-2.0","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fito-basket-compare\u002FSKILL.md",[],[],{"skillNo":68,"name":69,"nameZh":6,"description":70,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":63,"licenseFileUrl":71,"sourceHtmlUrl":72,"categories":73,"keywords":74,"publishedAt":19},"01M734CYEMZFDR3KH6SW0JP8TD","implementing-network-traffic-baselining","Build network traffic baselines from NetFlow\u002FIPFIX data using Python pandas for statistical analysis, z-score anomaly detection, and hourly\u002Fdaily traffic pattern profiling","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-network-traffic-baselining\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-network-traffic-baselining\u002FSKILL.md",[],[],{"skillNo":76,"name":77,"nameZh":6,"description":78,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":63,"licenseFileUrl":79,"sourceHtmlUrl":80,"categories":81,"keywords":82,"publishedAt":19},"01M73ASZ6NJRJM44Z2P84NGQ3Q","detecting-evasion-techniques-in-endpoint-logs","Detects defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FSKILL.md",[],[],{"skillNo":84,"name":85,"nameZh":6,"description":86,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":63,"licenseFileUrl":87,"sourceHtmlUrl":88,"categories":89,"keywords":90,"publishedAt":19},"01M734AFNXD06Z78QRK0VKGT7Q","implementing-microsegmentation-with-guardicore","Implementing microsegmentation using Akamai Guardicore Segmentation to map application dependencies, create granular network policies, visualize east-west traffic flows, and enforce least-privilege communication between workloads across data centers and cloud.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FSKILL.md",[],[],{"skillNo":92,"name":93,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":63,"licenseFileUrl":6,"sourceHtmlUrl":94,"categories":95,"keywords":96,"publishedAt":19},"01M736TK27QMCXK0DVCH25SJN5","ramdisk-tmpfs-patterns","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Framdisk-tmpfs-patterns\u002FSKILL.md",[],[]]