{
  "site": {
    "name": "ZenLeak GEO 学院",
    "shortName": "ZenLeak",
    "url": "https://zenleak.cn",
    "description": "ZenLeak GEO 学院是一个系统学习生成式搜索优化、AI 搜索引用机制和内容可见性的中文教程站。",
    "locale": "zh-CN",
    "author": "ZenLeak 编辑部",
    "email": "geo@allintwo.cloud",
    "filings": {
      "icp": {
        "number": "粤ICP备2025415379号",
        "href": "https://beian.miit.gov.cn/"
      },
      "police": {
        "number": "粤公网安备44011402001462号",
        "recordCode": "44011402001462",
        "href": "https://beian.mps.gov.cn/#/query/webSearch?code=44011402001462"
      }
    }
  },
  "generatedAt": "2026-09-16",
  "purpose": "Machine-readable index for AI agents, internal tools, and search quality audits.",
  "architecture": {
    "learningCenter": "/start/",
    "tutorialGroups": [
      {
        "title": "GEO 入门",
        "href": "/basics/",
        "description": "理解 GEO、SEO、AEO、LLMO 的关系，建立问题研究与答案思维。"
      },
      {
        "title": "内容优化",
        "href": "/content/",
        "description": "把教程、产品页和 FAQ 写成更容易理解、摘取和复核的结构。"
      },
      {
        "title": "技术配置",
        "href": "/technical/",
        "description": "处理抓取、索引、结构化数据、sitemap、robots 和 llms.txt。"
      }
    ],
    "practiceCenter": "/practice/",
    "resourceCenter": "/resources/",
    "trustAndMethodology": "/methodology/",
    "editorialIdentity": "/about/",
    "publicEvidenceLedger": "/evidence/",
    "publicChangeLog": "/changelog/"
  },
  "editorial": {
    "name": "ZenLeak 编辑部",
    "organizationId": "https://zenleak.cn/#organization",
    "contact": "geo@allintwo.cloud",
    "about": "/about/",
    "methodology": "/methodology/",
    "corrections": "/about/#corrections"
  },
  "evidence": {
    "page": "/evidence/",
    "index": "/evidence-index.json",
    "relationshipScope": "page-level",
    "recordRepresentations": {
      "jsonPattern": "/evidence/{tutorial-id}.json",
      "markdownPattern": "/evidence/{tutorial-id}.md"
    },
    "tutorialRecords": 12,
    "claims": 36,
    "sourceCitations": 27
  },
  "learningStages": [
    {
      "stage": 1,
      "title": "建立概念与问题框架",
      "description": "先弄清 GEO 的边界，再把零散关键词扩展为真实问题、意图与实体关系。",
      "outcome": "完成一份可排序的问题库，并能解释 SEO 与 GEO 的协作关系。"
    },
    {
      "stage": 2,
      "title": "设计可理解的内容",
      "description": "学习答案结构、证据组织、主题集群和产品页表达，把概念变成可执行页面。",
      "outcome": "完成一篇包含答案、边界、证据、步骤和内链的页面初稿。"
    },
    {
      "stage": 3,
      "title": "补齐技术与发布底座",
      "description": "按照发现、抓取、索引、归一和理解的顺序，检查站点的机器入口。",
      "outcome": "完成一轮技术检查，并把正式域名与机器可读入口统一起来。"
    },
    {
      "stage": 4,
      "title": "用案例与实验复核",
      "description": "把改造前后的页面版本、固定问题、平台与答案结果记录下来，避免凭印象判断。",
      "outcome": "建立首轮测试基线，能区分品牌提及、页面链接、内容采用和答案准确度。"
    }
  ],
  "tutorials": [
    {
      "id": "what-is-geo",
      "title": "GEO 是什么：生成式搜索优化入门指南",
      "href": "/basics/what-is-geo/",
      "category": "GEO 入门",
      "difficulty": "新手",
      "readingTime": "8 分钟",
      "readingMinutes": 8,
      "datePublished": "2026-09-13",
      "dateModified": "2026-09-14",
      "description": "用一篇文章讲清楚 GEO 的定义、适用场景、和传统 SEO 的关系，以及为什么教程站、B2B、SaaS 和知识型内容要尽早关注它。",
      "keywords": [
        "GEO",
        "生成式搜索优化",
        "AI 搜索",
        "AI 引用",
        "SEO"
      ],
      "summary": [
        "GEO 是 Generative Engine Optimization，中文可以叫生成式搜索优化。",
        "它的目标不是替代 SEO，而是让内容更容易被 AI 搜索系统理解、组织、引用和推荐。",
        "一个 GEO 友好的页面通常有清晰定义、可信证据、结构化步骤、FAQ、实体信息和可抓取技术基础。"
      ],
      "stage": 1,
      "order": 1,
      "prerequisites": [],
      "outcomes": [
        "准确区分 GEO、SEO、AEO 与 LLMO",
        "判断一个页面是否具备基本的 AI 可理解性"
      ],
      "contentType": "guide",
      "status": "reviewed",
      "reviewedAt": "2026-09-14",
      "sources": [
        {
          "label": "GEO: Generative Engine Optimization",
          "url": "https://arxiv.org/abs/2311.09735",
          "publisher": "arXiv"
        },
        {
          "label": "AI features and your website",
          "url": "https://developers.google.com/search/docs/appearance/ai-features",
          "publisher": "Google Search Central"
        }
      ],
      "related": [
        "seo-vs-geo",
        "answer-friendly-page",
        "robots-sitemap-llms"
      ],
      "featured": true,
      "sections": [
        {
          "href": "#definition",
          "label": "GEO 是什么"
        },
        {
          "href": "#steps",
          "label": "新手怎么开始"
        },
        {
          "href": "#examples",
          "label": "页面改造示例"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "入门检查清单"
        }
      ]
    },
    {
      "id": "seo-vs-geo",
      "title": "GEO 和 SEO 的区别：从排名思维到答案思维",
      "href": "/basics/seo-vs-geo/",
      "category": "GEO 入门",
      "difficulty": "新手",
      "readingTime": "9 分钟",
      "readingMinutes": 9,
      "datePublished": "2026-09-13",
      "dateModified": "2026-09-14",
      "description": "对比 SEO 和 GEO 的目标、内容结构、评估方式和常见误区，帮助内容团队建立生成式搜索时代的工作框架。",
      "keywords": [
        "GEO 与 SEO",
        "AEO",
        "LLMO",
        "答案引擎优化",
        "AI 搜索优化"
      ],
      "summary": [
        "SEO 主要优化网页在搜索结果中的可见性，GEO 主要优化内容在 AI 答案中的可理解性和引用机会。",
        "二者不是对立关系：没有基础 SEO，GEO 很难稳定生效；没有 GEO 思维，内容可能只适合被点击，不适合被回答系统采用。",
        "做 GEO 时要从关键词表转向问题库、实体库、证据库和答案结构。"
      ],
      "stage": 1,
      "order": 2,
      "prerequisites": [
        "what-is-geo"
      ],
      "outcomes": [
        "用目标、输入和指标解释 SEO 与 GEO 的分工",
        "把现有 SEO 工作流扩展为问题与答案工作流"
      ],
      "contentType": "guide",
      "status": "reviewed",
      "reviewedAt": "2026-09-14",
      "sources": [
        {
          "label": "Google Search Essentials",
          "url": "https://developers.google.com/search/docs/essentials",
          "publisher": "Google Search Central"
        },
        {
          "label": "GEO: Generative Engine Optimization",
          "url": "https://arxiv.org/abs/2311.09735",
          "publisher": "arXiv"
        }
      ],
      "related": [
        "what-is-geo",
        "question-research",
        "ai-citation-test"
      ],
      "featured": false,
      "sections": [
        {
          "href": "#definition",
          "label": "SEO 与 GEO 的核心区别"
        },
        {
          "href": "#steps",
          "label": "升级工作流"
        },
        {
          "href": "#examples",
          "label": "一个选题的两种写法"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "升级检查清单"
        }
      ]
    },
    {
      "id": "question-research",
      "title": "GEO 问题研究怎么做：从关键词到用户问题和实体",
      "href": "/basics/question-research/",
      "category": "GEO 入门",
      "difficulty": "进阶",
      "readingTime": "14 分钟",
      "readingMinutes": 14,
      "datePublished": "2026-09-13",
      "dateModified": "2026-09-14",
      "description": "把关键词研究升级成问题库、意图层级和实体关系，找到真正值得写成教程、案例和工具页面的内容机会。",
      "keywords": [
        "GEO 关键词研究",
        "用户问题",
        "搜索意图",
        "实体关系",
        "内容选题"
      ],
      "summary": [
        "GEO 问题研究的单位不是单个关键词，而是包含对象、动作、场景和判断条件的完整用户问题。",
        "研究结果应该沉淀成问题库、意图层级、实体清单和页面类型，而不是只生成一份标题列表。",
        "好的问题研究能帮助你决定写什么、先写哪一页、哪些问题应该合并，以及哪些问题需要实验验证。"
      ],
      "stage": 1,
      "order": 3,
      "prerequisites": [
        "seo-vs-geo"
      ],
      "outcomes": [
        "把关键词扩展成带场景和条件的用户问题",
        "建立可排序的问题库与初步内容地图"
      ],
      "contentType": "guide",
      "status": "reviewed",
      "reviewedAt": "2026-09-14",
      "sources": [
        {
          "label": "Creating helpful, reliable, people-first content",
          "url": "https://developers.google.com/search/docs/fundamentals/creating-helpful-content",
          "publisher": "Google Search Central"
        },
        {
          "label": "Search quality evaluator guidelines",
          "url": "https://guidelines.raterhub.com/searchqualityevaluatorguidelines.pdf",
          "publisher": "Google"
        }
      ],
      "related": [
        "seo-vs-geo",
        "topic-cluster",
        "answer-friendly-page"
      ],
      "featured": false,
      "sections": [
        {
          "href": "#definition",
          "label": "为什么要研究问题"
        },
        {
          "href": "#steps",
          "label": "五步建立问题库"
        },
        {
          "href": "#examples",
          "label": "完整问题库示例"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "问题研究清单"
        }
      ]
    },
    {
      "id": "answer-friendly-page",
      "title": "AI 友好页面怎么写：定义、证据、步骤和 FAQ",
      "href": "/content/answer-friendly-page/",
      "category": "内容优化",
      "difficulty": "进阶",
      "readingTime": "12 分钟",
      "readingMinutes": 12,
      "datePublished": "2026-09-13",
      "dateModified": "2026-09-14",
      "description": "把一篇普通文章改造成 AI 搜索更容易理解的页面：先给定义，再给证据、步骤、对比、FAQ 和可验证来源。",
      "keywords": [
        "AI 友好内容",
        "GEO 内容结构",
        "FAQ",
        "引用优化",
        "内容模板"
      ],
      "summary": [
        "AI 友好页面的核心是让答案、证据和边界足够清楚。",
        "推荐结构是：先给直接答案，再补定义、步骤、对比、示例、FAQ、来源和检查清单。",
        "页面不要只追求长，而要让每个段落都能回答一个明确问题。"
      ],
      "stage": 2,
      "order": 4,
      "prerequisites": [
        "question-research"
      ],
      "outcomes": [
        "把一个问题写成可独立理解的答案段",
        "完成一份包含定义、步骤、证据和边界的页面大纲"
      ],
      "contentType": "guide",
      "status": "reviewed",
      "reviewedAt": "2026-09-14",
      "sources": [
        {
          "label": "Creating helpful, reliable, people-first content",
          "url": "https://developers.google.com/search/docs/fundamentals/creating-helpful-content",
          "publisher": "Google Search Central"
        },
        {
          "label": "AI features and your website",
          "url": "https://developers.google.com/search/docs/appearance/ai-features",
          "publisher": "Google Search Central"
        }
      ],
      "related": [
        "evidence-and-sources",
        "product-page-geo",
        "question-research"
      ],
      "featured": true,
      "sections": [
        {
          "href": "#definition",
          "label": "什么是 AI 友好页面"
        },
        {
          "href": "#steps",
          "label": "推荐写作结构"
        },
        {
          "href": "#examples",
          "label": "错误与正确示例"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "发布前检查清单"
        }
      ]
    },
    {
      "id": "evidence-and-sources",
      "title": "GEO 证据怎么组织：来源、引用与可信度",
      "href": "/content/evidence-and-sources/",
      "category": "内容优化",
      "difficulty": "进阶",
      "readingTime": "13 分钟",
      "readingMinutes": 13,
      "datePublished": "2026-09-13",
      "dateModified": "2026-09-14",
      "description": "学习如何为 GEO 教程匹配官方文档、原始研究、数据、案例和实验记录，让结论更可信、更容易被复核。",
      "keywords": [
        "GEO 证据",
        "内容可信度",
        "来源引用",
        "原创研究",
        "内容质量"
      ],
      "summary": [
        "GEO 内容的可信度不来自链接数量，而来自结论和证据之间是否匹配、来源是否可追溯、范围是否说清楚。",
        "规则类结论优先引用官方文档，效果类结论需要研究、数据或实验，经验类结论要标明样本和条件。",
        "深度教程应该建立证据地图：每个重要判断都有来源、证据类型、适用范围和最近验证时间。"
      ],
      "stage": 2,
      "order": 5,
      "prerequisites": [
        "answer-friendly-page"
      ],
      "outcomes": [
        "区分事实、效果、推论与建议所需的证据",
        "为一篇文章建立可维护的证据地图"
      ],
      "contentType": "guide",
      "status": "reviewed",
      "reviewedAt": "2026-09-14",
      "sources": [
        {
          "label": "Search quality evaluator guidelines",
          "url": "https://guidelines.raterhub.com/searchqualityevaluatorguidelines.pdf",
          "publisher": "Google"
        },
        {
          "label": "How to write a literature review",
          "url": "https://writingcenter.unc.edu/tips-and-tools/literature-reviews/",
          "publisher": "UNC Writing Center"
        }
      ],
      "related": [
        "answer-friendly-page",
        "ai-citation-test",
        "topic-cluster"
      ],
      "featured": false,
      "sections": [
        {
          "href": "#definition",
          "label": "什么是 GEO 证据"
        },
        {
          "href": "#steps",
          "label": "建立证据地图"
        },
        {
          "href": "#examples",
          "label": "引用写法示例"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "证据检查清单"
        }
      ]
    },
    {
      "id": "topic-cluster",
      "title": "GEO 主题集群怎么做：从关键词表到问题网络",
      "href": "/content/topic-cluster/",
      "category": "内容优化",
      "difficulty": "进阶",
      "readingTime": "15 分钟",
      "readingMinutes": 15,
      "datePublished": "2026-09-13",
      "dateModified": "2026-09-14",
      "description": "学习如何把关键词研究升级成问题网络、实体库和教程集群，建立更适合 AI 搜索理解的主题权威。",
      "keywords": [
        "GEO 主题集群",
        "问题网络",
        "实体优化",
        "内容策略",
        "主题权威"
      ],
      "summary": [
        "GEO 主题集群不是把一堆关键词塞进栏目，而是围绕一个核心问题建立可解释的知识网络。",
        "一个好的主题集群通常包含支柱页、定义页、实操教程、对比页、案例页、模板页和实验记录。",
        "主题集群的目标是让用户和 AI 搜索系统都能判断：这个网站在某个细分主题上持续、系统、可验证。"
      ],
      "stage": 2,
      "order": 6,
      "prerequisites": [
        "question-research",
        "answer-friendly-page"
      ],
      "outcomes": [
        "把问题库组织成支柱页与子页面网络",
        "为页面安排角色、内链和更新顺序"
      ],
      "contentType": "guide",
      "status": "reviewed",
      "reviewedAt": "2026-09-14",
      "sources": [
        {
          "label": "SEO Starter Guide",
          "url": "https://developers.google.com/search/docs/fundamentals/seo-starter-guide",
          "publisher": "Google Search Central"
        },
        {
          "label": "Links best practices",
          "url": "https://developers.google.com/search/docs/crawling-indexing/links-crawlable",
          "publisher": "Google Search Central"
        }
      ],
      "related": [
        "question-research",
        "answer-friendly-page",
        "homepage-audit"
      ],
      "featured": false,
      "sections": [
        {
          "href": "#definition",
          "label": "什么是主题集群"
        },
        {
          "href": "#steps",
          "label": "搭建主题集群"
        },
        {
          "href": "#examples",
          "label": "ZenLeak 组织示例"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "主题集群清单"
        }
      ]
    },
    {
      "id": "product-page-geo",
      "title": "产品页如何做 GEO：让 AI 看懂你适合谁",
      "href": "/content/product-page-geo/",
      "category": "内容优化",
      "difficulty": "进阶",
      "readingTime": "14 分钟",
      "readingMinutes": 14,
      "datePublished": "2026-09-13",
      "dateModified": "2026-09-14",
      "description": "面向 SaaS、工具、电商和 B2B 产品页，讲清楚如何表达产品定义、适用人群、替代方案、证据和 FAQ。",
      "keywords": [
        "产品页 GEO",
        "SaaS SEO",
        "B2B 内容",
        "AI 推荐",
        "产品页面优化"
      ],
      "summary": [
        "产品页 GEO 的核心不是把产品形容得更厉害，而是让 AI 准确判断产品是什么、适合谁、解决什么问题、和什么替代方案不同。",
        "一个可引用的产品页需要同时表达产品实体、用户场景、功能边界、证据、实施成本和常见疑问。",
        "产品页最好能独立回答‘这是什么、适合谁、为什么选它、怎么开始、有什么限制’这五类问题。"
      ],
      "stage": 2,
      "order": 7,
      "prerequisites": [
        "answer-friendly-page",
        "evidence-and-sources"
      ],
      "outcomes": [
        "用类别、人群和任务清楚定义产品",
        "补齐产品页的边界、替代方案与证据"
      ],
      "contentType": "guide",
      "status": "reviewed",
      "reviewedAt": "2026-09-14",
      "sources": [
        {
          "label": "Product structured data",
          "url": "https://developers.google.com/search/docs/appearance/structured-data/product",
          "publisher": "Google Search Central"
        },
        {
          "label": "Product schema",
          "url": "https://schema.org/Product",
          "publisher": "Schema.org"
        }
      ],
      "related": [
        "answer-friendly-page",
        "evidence-and-sources",
        "structured-data"
      ],
      "featured": false,
      "sections": [
        {
          "href": "#definition",
          "label": "产品页为什么需要 GEO"
        },
        {
          "href": "#steps",
          "label": "产品页推荐结构"
        },
        {
          "href": "#examples",
          "label": "产品页示例骨架"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "产品页发布清单"
        }
      ]
    },
    {
      "id": "robots-sitemap-llms",
      "title": "robots、sitemap 和 llms.txt：GEO 技术基础配置",
      "href": "/technical/robots-sitemap-llms/",
      "category": "技术配置",
      "difficulty": "进阶",
      "readingTime": "10 分钟",
      "readingMinutes": 10,
      "datePublished": "2026-09-13",
      "dateModified": "2026-09-14",
      "description": "解释 robots.txt、sitemap.xml、canonical、结构化数据和 llms.txt 在 SEO 与 GEO 中分别解决什么问题。",
      "keywords": [
        "robots.txt",
        "sitemap",
        "llms.txt",
        "结构化数据",
        "GEO 技术 SEO"
      ],
      "summary": [
        "robots.txt、sitemap 和 llms.txt 解决的是不同问题：能不能抓、怎么发现、如何快速理解。",
        "SEO 必须先保证页面可抓取、可索引、canonical 正确、sitemap 完整。",
        "llms.txt 更适合作为 AI agent 的站点导览，不能代替内容质量和搜索索引基础。"
      ],
      "stage": 3,
      "order": 8,
      "prerequisites": [
        "what-is-geo"
      ],
      "outcomes": [
        "解释 robots、sitemap、canonical 与 llms.txt 的职责",
        "按发现、抓取、索引、理解顺序排查页面"
      ],
      "contentType": "guide",
      "status": "reviewed",
      "reviewedAt": "2026-09-14",
      "sources": [
        {
          "label": "Robots Exclusion Protocol (RFC 9309)",
          "url": "https://www.rfc-editor.org/rfc/rfc9309",
          "publisher": "IETF"
        },
        {
          "label": "Build and submit a sitemap",
          "url": "https://developers.google.com/search/docs/crawling-indexing/sitemaps/build-sitemap",
          "publisher": "Google Search Central"
        },
        {
          "label": "llms.txt proposal",
          "url": "https://llmstxt.org/",
          "publisher": "llmstxt.org"
        }
      ],
      "related": [
        "structured-data",
        "root-domain-launch",
        "what-is-geo"
      ],
      "featured": true,
      "sections": [
        {
          "href": "#definition",
          "label": "三类文件的职责"
        },
        {
          "href": "#steps",
          "label": "配置顺序"
        },
        {
          "href": "#examples",
          "label": "配置示例"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "技术检查清单"
        }
      ]
    },
    {
      "id": "structured-data",
      "title": "结构化数据怎么服务 GEO：Schema 不是装饰",
      "href": "/technical/structured-data/",
      "category": "技术配置",
      "difficulty": "进阶",
      "readingTime": "13 分钟",
      "readingMinutes": 13,
      "datePublished": "2026-09-13",
      "dateModified": "2026-09-14",
      "description": "解释 Article、LearningResource、BreadcrumbList、Organization 等结构化数据如何帮助搜索系统理解教程站。",
      "keywords": [
        "结构化数据",
        "Schema.org",
        "Article",
        "LearningResource",
        "BreadcrumbList"
      ],
      "summary": [
        "结构化数据不是用来把普通页面变成高排名页面，而是用标准词汇表达页面是什么、属于谁、和哪些页面相关。",
        "教程站最常用的类型包括 Organization、WebSite、BreadcrumbList、Article、LearningResource 和 DefinedTermSet。",
        "结构化数据必须和页面可见内容一致；不能在 JSON-LD 里声明正文没有出现的评分、价格、作者或 FAQ。"
      ],
      "stage": 3,
      "order": 9,
      "prerequisites": [
        "robots-sitemap-llms"
      ],
      "outcomes": [
        "为教程站选择正确的 Schema.org 类型",
        "检查 JSON-LD 是否与页面可见内容一致"
      ],
      "contentType": "guide",
      "status": "reviewed",
      "reviewedAt": "2026-09-14",
      "sources": [
        {
          "label": "Understand how structured data works",
          "url": "https://developers.google.com/search/docs/appearance/structured-data/intro-structured-data",
          "publisher": "Google Search Central"
        },
        {
          "label": "LearningResource",
          "url": "https://schema.org/LearningResource",
          "publisher": "Schema.org"
        }
      ],
      "related": [
        "robots-sitemap-llms",
        "root-domain-launch",
        "product-page-geo"
      ],
      "featured": false,
      "sections": [
        {
          "href": "#definition",
          "label": "结构化数据是什么"
        },
        {
          "href": "#steps",
          "label": "正确配置步骤"
        },
        {
          "href": "#examples",
          "label": "JSON-LD 示例"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "结构化数据清单"
        }
      ]
    },
    {
      "id": "root-domain-launch",
      "title": "主域名上线怎么优化：ZenLeak 根域名发布清单",
      "href": "/technical/root-domain-launch/",
      "category": "技术配置",
      "difficulty": "实战",
      "readingTime": "12 分钟",
      "readingMinutes": 12,
      "datePublished": "2026-09-14",
      "dateModified": "2026-09-14",
      "description": "用 zenleak.cn 作为正式主域名时，系统检查 DNS、www 归一、HTTPS、canonical、sitemap、robots、缓存、安全响应头和站长平台提交。",
      "keywords": [
        "主域名 SEO",
        "根域名 canonical",
        "www 跳转",
        "GEO 上线清单",
        "Search Console"
      ],
      "summary": [
        "ZenLeak 如果用 zenleak.cn 作为主域名，最重要的是把所有公开入口统一到 https://zenleak.cn。",
        "系统层要同时处理 DNS、HTTPS、www 301 跳转、canonical、sitemap、robots、缓存和安全响应头。",
        "GEO 不是只多放一个 llms.txt，而是让搜索引擎、AI agent 和真实读者看到同一套稳定、可读、可验证的站点结构。"
      ],
      "stage": 3,
      "order": 10,
      "prerequisites": [
        "robots-sitemap-llms",
        "structured-data"
      ],
      "outcomes": [
        "把根域名、www 与临时域名统一为一个正式地址",
        "完成 DNS、HTTPS、canonical、缓存与站长平台检查"
      ],
      "contentType": "guide",
      "status": "reviewed",
      "reviewedAt": "2026-09-14",
      "sources": [
        {
          "label": "Canonical URLs",
          "url": "https://developers.google.com/search/docs/crawling-indexing/consolidate-duplicate-urls",
          "publisher": "Google Search Central"
        },
        {
          "label": "Sitemap integration",
          "url": "https://docs.astro.build/en/guides/integrations-guide/sitemap/",
          "publisher": "Astro"
        }
      ],
      "related": [
        "robots-sitemap-llms",
        "structured-data",
        "homepage-audit"
      ],
      "featured": false,
      "sections": [
        {
          "href": "#definition",
          "label": "主域名优化核心"
        },
        {
          "href": "#steps",
          "label": "主域名上线顺序"
        },
        {
          "href": "#examples",
          "label": "ZenLeak 上线文件"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "主域名上线清单"
        }
      ]
    },
    {
      "id": "homepage-audit",
      "title": "案例：把 GEO 教程站首页改造成 AI 可理解入口",
      "href": "/cases/homepage-audit/",
      "category": "案例",
      "difficulty": "实战",
      "readingTime": "18 分钟",
      "readingMinutes": 18,
      "datePublished": "2026-09-13",
      "dateModified": "2026-09-16",
      "description": "用 ZenLeak 首页作为示例，拆解品牌定义、学习路径、主题集群、机器可读入口和后续实验应该如何连接。",
      "keywords": [
        "GEO 首页案例",
        "教程站架构",
        "首页优化",
        "AI 可理解网站",
        "内容入口"
      ],
      "summary": [
        "本案例以 ZenLeak GEO 学院首页为示例，演示教程站如何同时服务普通读者、搜索系统和 AI agent。",
        "核心改造不是增加一句宣传语，而是把品牌定义、学习路径、核心教程、主题集群、机器可读入口和实验室连接起来。",
        "本文是架构示例，不声称已经产生某个平台的固定排名或引用结果；上线后的表现需要按实验方法单独复测。"
      ],
      "stage": 4,
      "order": 11,
      "prerequisites": [
        "topic-cluster",
        "root-domain-launch"
      ],
      "outcomes": [
        "用五层模型审查教程站首页",
        "设计一组可验证的首页改造指标"
      ],
      "contentType": "case-study",
      "status": "reviewed",
      "reviewedAt": "2026-09-16",
      "sources": [
        {
          "label": "ZenLeak GEO 方法论",
          "url": "/methodology/",
          "publisher": "ZenLeak 编辑部"
        },
        {
          "label": "SEO Starter Guide",
          "url": "https://developers.google.com/search/docs/fundamentals/seo-starter-guide",
          "publisher": "Google Search Central"
        },
        {
          "label": "AI features and your website",
          "url": "https://developers.google.com/search/docs/appearance/ai-features",
          "publisher": "Google Search Central"
        }
      ],
      "related": [
        "topic-cluster",
        "root-domain-launch",
        "ai-citation-test"
      ],
      "featured": false,
      "sections": [
        {
          "href": "#background",
          "label": "案例背景"
        },
        {
          "href": "#diagnosis",
          "label": "问题诊断"
        },
        {
          "href": "#design",
          "label": "页面设计"
        },
        {
          "href": "#measurement",
          "label": "如何验证"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "复盘清单"
        }
      ]
    },
    {
      "id": "ai-citation-test",
      "title": "AI 引用测试怎么做：建立 GEO 实验记录",
      "href": "/experiments/ai-citation-test/",
      "category": "实验室",
      "difficulty": "实战",
      "readingTime": "16 分钟",
      "readingMinutes": 16,
      "datePublished": "2026-09-13",
      "dateModified": "2026-09-16",
      "description": "用标准化问题、测试平台、记录表和复测节奏，观察你的页面是否被 AI 搜索提到、引用或误解。",
      "keywords": [
        "AI 引用测试",
        "GEO 实验",
        "AI 搜索监测",
        "品牌提及",
        "内容复测"
      ],
      "summary": [
        "AI 引用测试是用一组固定问题，定期记录品牌是否被提及、页面是否被引用、答案是否准确以及结果是否稳定。",
        "测试结果不能简单等同于排名，也不能用一次回答证明某个页面一定被系统收录或信任。",
        "真正有价值的实验需要固定问题、平台、日期、页面版本和判定标准，然后比较改造前后的变化。"
      ],
      "stage": 4,
      "order": 12,
      "prerequisites": [
        "homepage-audit",
        "evidence-and-sources"
      ],
      "outcomes": [
        "设计一组可复测的 AI 搜索问题",
        "分开记录提及、链接、采用与准确度"
      ],
      "contentType": "experiment",
      "status": "experimental",
      "reviewedAt": "2026-09-16",
      "sources": [
        {
          "label": "ZenLeak GEO 方法论",
          "url": "/methodology/",
          "publisher": "ZenLeak 编辑部"
        },
        {
          "label": "GEO: Generative Engine Optimization",
          "url": "https://arxiv.org/abs/2311.09735",
          "publisher": "arXiv"
        },
        {
          "label": "Evaluation best practices",
          "url": "https://platform.openai.com/docs/guides/evaluation-best-practices",
          "publisher": "OpenAI"
        }
      ],
      "related": [
        "homepage-audit",
        "evidence-and-sources",
        "seo-vs-geo"
      ],
      "featured": true,
      "sections": [
        {
          "href": "#definition",
          "label": "什么是 AI 引用测试"
        },
        {
          "href": "#steps",
          "label": "建立一轮实验"
        },
        {
          "href": "#examples",
          "label": "实验记录模板"
        },
        {
          "href": "#faq",
          "label": "常见问题"
        },
        {
          "href": "#checklist",
          "label": "实验检查清单"
        }
      ]
    }
  ],
  "glossary": [
    {
      "id": "geo",
      "term": "GEO",
      "name": "Generative Engine Optimization",
      "category": "基础概念",
      "aliases": [
        "生成式搜索优化",
        "生成引擎优化"
      ],
      "description": "生成式搜索优化，目标是让内容更容易被 AI 搜索系统发现、理解、采用、引用或推荐。它不是单一排名技巧，而是内容、证据、实体与技术基础的组合。",
      "related": [
        "what-is-geo",
        "seo-vs-geo"
      ]
    },
    {
      "id": "aeo",
      "term": "AEO",
      "name": "Answer Engine Optimization",
      "category": "基础概念",
      "aliases": [
        "答案引擎优化"
      ],
      "description": "答案引擎优化，强调页面能否直接、准确地回答用户问题，并被精选摘要、语音助手或答案型搜索界面采用。",
      "related": [
        "seo-vs-geo",
        "answer-friendly-page"
      ]
    },
    {
      "id": "llmo",
      "term": "LLMO",
      "name": "Large Language Model Optimization",
      "category": "基础概念",
      "aliases": [
        "大语言模型优化"
      ],
      "description": "面向大语言模型的信息呈现优化，常用于描述品牌、实体、产品文档和知识库的可理解性建设。行业对其边界尚无统一定义。",
      "related": [
        "seo-vs-geo",
        "what-is-geo"
      ]
    },
    {
      "id": "entity",
      "term": "实体",
      "name": "Entity",
      "category": "内容结构",
      "aliases": [
        "品牌实体",
        "语义实体"
      ],
      "description": "搜索系统可以识别和归类的人、品牌、产品、地点、组织、概念或事件。清晰实体通常拥有稳定名称、属性、关系和可核验来源。",
      "related": [
        "question-research",
        "product-page-geo"
      ]
    },
    {
      "id": "citation-potential",
      "term": "引用潜力",
      "name": "Citation Potential",
      "category": "验证指标",
      "aliases": [
        "AI 引用机会"
      ],
      "description": "页面内容被 AI 答案作为来源、证据或推荐对象采用的可能性。它只能通过持续测试观察，不能由单个静态分数直接证明。",
      "related": [
        "evidence-and-sources",
        "ai-citation-test"
      ]
    },
    {
      "id": "llms-txt",
      "term": "llms.txt",
      "name": "LLM-friendly site guide",
      "category": "技术基础",
      "aliases": [
        "AI 站点导览"
      ],
      "description": "放在网站根目录的文本文件，用来向 AI agent 概括站点定位和重点页面。它是补充入口，不能替代 robots、sitemap、索引基础或正文质量。",
      "related": [
        "robots-sitemap-llms",
        "root-domain-launch"
      ]
    },
    {
      "id": "topic-cluster",
      "term": "主题集群",
      "name": "Topic Cluster",
      "category": "内容结构",
      "aliases": [
        "内容集群",
        "专题集群"
      ],
      "description": "围绕一个核心主题组织支柱页、子教程、案例、模板和实验，让读者与机器都能看清主题边界、页面角色和学习顺序。",
      "related": [
        "topic-cluster",
        "homepage-audit"
      ]
    },
    {
      "id": "question-graph",
      "term": "问题网络",
      "name": "Question Graph",
      "category": "内容结构",
      "aliases": [
        "问题图谱",
        "用户问题库"
      ],
      "description": "把用户问题按意图、阶段、实体、前置知识和上下文连接起来，用来规划页面类型、合并边界、内链与更新优先级。",
      "related": [
        "question-research",
        "topic-cluster"
      ]
    },
    {
      "id": "structured-data",
      "term": "结构化数据",
      "name": "Structured Data",
      "category": "技术基础",
      "aliases": [
        "Schema",
        "JSON-LD"
      ],
      "description": "用标准词汇描述页面、组织、文章、课程、产品或面包屑等对象，帮助机器识别内容类型和关系；声明必须与页面可见内容一致。",
      "related": [
        "structured-data",
        "product-page-geo"
      ]
    },
    {
      "id": "extractable-answer",
      "term": "可摘答案",
      "name": "Extractable Answer",
      "category": "内容结构",
      "aliases": [
        "直接答案",
        "答案段"
      ],
      "description": "离开原页面上下文也能基本成立的短段落，通常包含定义、适用条件、关键判断和必要边界，而不只是口号或无条件结论。",
      "related": [
        "answer-friendly-page",
        "evidence-and-sources"
      ]
    }
  ],
  "templates": [
    {
      "id": "definition-paragraph",
      "title": "AI 友好定义段",
      "useCase": "概念页开头",
      "description": "用于概念首次出现的位置。定义要能独立回答“这是什么”，同时说明场景、差异和判断标准，不能只展开英文缩写。",
      "page": "/templates/#definition-paragraph",
      "download": "/downloads/templates/definition-paragraph.md"
    },
    {
      "id": "tutorial-page",
      "title": "深度教程页结构",
      "useCase": "操作型教程",
      "description": "适合“怎么做”类内容。先交付答案，再补前置条件、判断标准和失败处理，让读者能按步骤完成一个结果。",
      "page": "/templates/#tutorial-page",
      "download": "/downloads/templates/tutorial-page.md"
    },
    {
      "id": "pillar-page",
      "title": "主题支柱页",
      "useCase": "专题入口",
      "description": "支柱页负责建立主题边界和阅读顺序，不负责吞下全部细节。它应该连接定义、教程、案例、模板和实验。",
      "page": "/templates/#pillar-page",
      "download": "/downloads/templates/pillar-page.md"
    },
    {
      "id": "faq-answer",
      "title": "FAQ 答案",
      "useCase": "长尾问题",
      "description": "问题尽量保留用户原话。答案第一句先给结论，之后再说明条件、分支和例外，不要把 FAQ 写成自我宣传。",
      "page": "/templates/#faq-answer",
      "download": "/downloads/templates/faq-answer.md"
    },
    {
      "id": "product-page",
      "title": "产品页 GEO",
      "useCase": "SaaS 与 B2B",
      "description": "把功能名改写成用户任务，并明确适用人群、替代方案、实施条件和证据，帮助用户与 AI 判断产品是否匹配。",
      "page": "/templates/#product-page",
      "download": "/downloads/templates/product-page.md"
    },
    {
      "id": "evidence-map",
      "title": "证据地图",
      "useCase": "写作与审稿",
      "description": "在写作前区分事实、规则、效果和建议，为重要判断匹配证据类型、适用范围和更新时间。",
      "page": "/templates/#evidence-map",
      "download": "/downloads/templates/evidence-map.md"
    },
    {
      "id": "ai-citation-experiment",
      "title": "AI 引用实验记录",
      "useCase": "基线与复测",
      "description": "保留问题原文和页面版本，分开记录提及、链接、内容采用与准确度，避免把一次回答误当成稳定排名。",
      "page": "/templates/#ai-citation-experiment",
      "download": "/downloads/templates/ai-citation-experiment.md"
    },
    {
      "id": "pre-publish-checklist",
      "title": "发布前 GEO 检查清单",
      "useCase": "编辑与发布",
      "description": "用于最终审稿。清单不能证明页面一定获得排名或引用，但能减少主题模糊、证据不足、入口缺失和版本不一致。",
      "page": "/templates/#pre-publish-checklist",
      "download": "/downloads/templates/pre-publish-checklist.md"
    }
  ],
  "pages": [
    {
      "title": "ZenLeak GEO 学院",
      "href": "/",
      "category": "首页",
      "description": "中文生成式搜索优化教程站，提供系统课程、案例、实验和实用资源。",
      "keywords": [
        "GEO 教程",
        "AI 搜索"
      ]
    },
    {
      "title": "GEO 学习中心",
      "href": "/start/",
      "category": "学习",
      "description": "按四个阶段学习 GEO，从概念、内容和技术走到案例与实验。",
      "keywords": [
        "学习路径",
        "课程"
      ]
    },
    {
      "title": "GEO 入门",
      "href": "/basics/",
      "category": "教程栏目",
      "description": "GEO、SEO、AEO、LLMO、问题研究与实体基础。",
      "keywords": [
        "新手",
        "基础"
      ]
    },
    {
      "title": "内容优化",
      "href": "/content/",
      "category": "教程栏目",
      "description": "答案结构、证据、主题集群与产品页 GEO。",
      "keywords": [
        "写作",
        "内容"
      ]
    },
    {
      "title": "技术配置",
      "href": "/technical/",
      "category": "教程栏目",
      "description": "抓取、索引、结构化数据、域名和机器入口。",
      "keywords": [
        "技术 SEO",
        "Schema"
      ]
    },
    {
      "title": "实践中心",
      "href": "/practice/",
      "category": "实践",
      "description": "案例拆解、实验方法与公开研究记录。",
      "keywords": [
        "案例",
        "实验"
      ]
    },
    {
      "title": "GEO 案例拆解",
      "href": "/cases/",
      "category": "实践",
      "description": "用页面改造前后对比解释 AI 搜索如何理解、引用或忽略内容。",
      "keywords": [
        "案例",
        "页面审计"
      ]
    },
    {
      "title": "AI 搜索实验室",
      "href": "/experiments/",
      "category": "实践",
      "description": "公开记录测试条件、原始观察、复测过程和结论边界。",
      "keywords": [
        "AI 引用",
        "实验记录"
      ]
    },
    {
      "title": "资源中心",
      "href": "/resources/",
      "category": "资源",
      "description": "模板、发布检查工具、术语库与研究方法。",
      "keywords": [
        "模板",
        "工具",
        "术语"
      ]
    },
    {
      "title": "GEO 模板库",
      "href": "/templates/",
      "category": "资源",
      "description": "八份可以复制和下载的 GEO 写作、证据与实验模板。",
      "keywords": [
        "Markdown",
        "大纲"
      ]
    },
    {
      "title": "GEO 发布前检查",
      "href": "/tools/",
      "category": "资源",
      "description": "可保存进度的 SEO 与 GEO 页面发布检查工具。",
      "keywords": [
        "评分",
        "清单"
      ]
    },
    {
      "title": "GEO 术语库",
      "href": "/glossary/",
      "category": "资源",
      "description": "常见 GEO、AI 搜索与内容结构概念。",
      "keywords": [
        "词典",
        "定义"
      ]
    },
    {
      "title": "ZenLeak 研究方法",
      "href": "/methodology/",
      "category": "信任",
      "description": "ZenLeak 如何区分事实、推论、经验和实验结论。",
      "keywords": [
        "方法论",
        "来源",
        "复核"
      ]
    },
    {
      "title": "关于 ZenLeak",
      "href": "/about/",
      "category": "信任",
      "description": "ZenLeak 的站点定位、编辑责任、内容边界、修正机制和联系信息。",
      "keywords": [
        "编辑部",
        "关于",
        "纠错"
      ]
    },
    {
      "title": "ZenLeak 公开证据账本",
      "href": "/evidence/",
      "category": "信任",
      "description": "逐篇查看主线教程的核心声明、参考来源、状态与复核日期。",
      "keywords": [
        "证据",
        "来源",
        "复核"
      ]
    },
    {
      "title": "ZenLeak 内容更新记录",
      "href": "/changelog/",
      "category": "信任",
      "description": "按日期查看主线教程的发布日期、更新时间与复核状态。",
      "keywords": [
        "更新记录",
        "时间线",
        "维护"
      ]
    }
  ],
  "seoChecklist": [
    "每个页面有唯一标题、描述、canonical 和一个清晰 H1。",
    "重要教程可以从首页、栏目页、学习路径和相关文章中被访问到。",
    "站点提供 sitemap.xml、robots.txt、RSS 和可读的文本内容。",
    "页面结构遵循 H2/H3 层级，避免把核心内容藏在脚本渲染里。",
    "关键概念有定义段、示例、常见错误和 FAQ。",
    "有作者、更新时间、适用人群、来源或验证方式。"
  ],
  "geoChecklist": [
    "每篇教程开头提供 2-4 句可直接摘取的核心摘要。",
    "用问题式小标题承接真实搜索意图，而不是只写抽象标题。",
    "加入定义、步骤、对比表、清单、FAQ 和可验证证据。",
    "围绕品牌、产品、行业、人群和问题建立一致实体描述。",
    "提供 llms.txt 和站点索引 JSON，方便 AI agent 快速理解站点结构。",
    "实验和案例页面保留测试日期、问题、平台、结果和结论。"
  ],
  "machineAccess": {
    "sitemap": "/sitemap-index.xml",
    "robots": "/robots.txt",
    "rss": "/rss.xml",
    "llms": "/llms.txt",
    "llmsFull": "/llms-full.txt",
    "searchIndex": "/search-index.json",
    "evidenceIndex": "/evidence-index.json",
    "evidenceRecordJsonPattern": "/evidence/{tutorial-id}.json",
    "evidenceRecordMarkdownPattern": "/evidence/{tutorial-id}.md"
  }
}