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引用恢复优化器

当用户希望改进现有网页以在AI模型中获得更多引用时使用此技能。它会分析AI可见性数据,识别有潜力但表现不佳的页面,与竞争页面进行对比,生成章节级或全页改写,并将修订推送至CMS作为草稿。

引用恢复优化器 是什么?

引用恢复优化器是一种专门针对已有内容进行AI引用优化的技能。它基于一个核心逻辑:改进已有信号的页面比从零开始构建更快速。该技能通过AI可见性数据获取品牌自有页面及其引用情况,然后识别同一主题下获得引用的外部竞争页面,计算引用差距,并对自有页面进行优先级排序。它能够进行详细的页面诊断,比较回答直接性、常见问题覆盖、内容具体性、缺失章节、竞争框架和结构信号等维度。技能支持根据地输出章节级补丁或完整页面改写,并自动推送到Sanity、Contentful、HubSpot、WordPress、Ghost或Webflow等CMS系统作为草稿。它特别关注产品比较页面和列表式文章,这些类型往往被AI模型高度引用。最终目标是让用户的页面在AI回答中成为首选来源。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/amplitude/builder-skills/tree/HEAD/content-marketing-skills/skills/citation-recovery-optimizer

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

引用恢复优化器 是做什么的?

你正在帮助内容团队从现有页面中榨取更多 AI 引用。逻辑如下: 改进已有信号的页面比从零开始构建更快。AI 可见性工具会显示哪些自有页面已被引用——以及哪些竞争对手的页面在同一主题上胜出。两者的差距正是改写要瞄准的方向。


第0步 — CMS 发现(在每次会话开始时运行一次)

在做任何其他事情之前,先摸清修改后的内容会发布到哪里。这可以避免工作流最后出现复制粘贴的死胡同。

检查已连接的 CMS 工具

扫描当前上下文中可用的工具。已知的 CMS MCP 模式:

CMS要查找的工具名称模式
Sanitysanity、create_documents_from_markdown、patch_document_from_markdown
Contentfulcontentful、create_entry、update_entry
HubSpot CMShubspot、update_blog_post、create_blog_post
WordPresswordpress、wp_update_post、wp_create_post
Ghostghost、update_post、create_post
Webflowwebflow、update_cms_item、create_cms_item

如果 CMS MCP 已连接: 用一句话确认: “我看到 [CMS] 已连接——我将在完成后把修改后的内容作为更新草稿推送过去。可以吗?” 然后进入第1步。

如果什么都没连接: 简洁地问一次:

“在我们开始之前——您发布到哪个 CMS?我可以直接将修改后的内容作为草稿推送过去,而不是给您一段文本去粘贴。”

提供选项:Sanity · Contentful · HubSpot · WordPress · Webflow · Ghost · 其他 · “只给我改写内容”

然后根据他们的回答给出量身定制的设置建议(参见 prompt-gap-to-publish 技能中的相同指导)。不要因为设置而阻塞——立即开始分析,并说明等他们连接好时你已经准备好推送。


第1步 — 识别品牌并提取自有页面

使用 list_ai_visibility_org_brands 识别品牌(或使用用户指定的品牌)。

然后调用 get_ai_visibility_pages 并设置两个关键约束:

  • orgBrandId = 所选品牌
  • mentionsBrandId = 同一品牌 ID(这会过滤出提到该品牌的页面)
  • sortBy: "citationCount"

从结果中,过滤出品牌自有域名下的页面——例如 amplitude.com,而不是 pendo.io 或 g2.com。每个页面上的 domain 字段可以轻松实现这一点。这些就是你要改进的自有资产。

为每个自有页面收集:

  • url 和 title
  • citationCount 和 responseCount
  • type(landing-page、blog、product-comparison、listicle)
  • brandNames——与该页面一同提及的其他品牌(标示主题范围)

第2步 — 查找在相同主题上胜出的竞争对手页面

对于自有页面所涵盖的相同主题,提取引用数量最高的外部页面。再次使用 get_ai_visibility_pages,不加域名过滤,仅按 citationCount 排序,查找来自其他域名、提及相同品牌并涵盖重叠主题的页面。

同时调用 get_ai_visibility_sources 并按 citationCount 排序,以查看整体上哪些域名获得了最多的引用。如果某个域名的排名远高于品牌自有网站,则它值得仔细研究。

你要构建的是一个对比:对于每个自有页面,谁是在同一主题上胜出的外部页面,胜出多少?例如:

自有页面自有引用数主要竞争页面对手引用数
amplitude.com/compare/best-session-replay-tools49contentsquare.com/blog/session-replay180

这个差距就是机会——而竞争页面的结构就是你了解该主题上被广泛引用页面样子的参考。


第3步 — 评分并确定页面优先级

并非所有表现不佳的页面都值得同等的投入。根据以下指标为每个自有页面打分:

引用差距(最高优先级信号):competitor_citations - own_citations。一个自有引用数为 49 但竞争页面有 180 的页面,差距为 131——这是一个高价值的改写。

页面类型杠杆:产品比较页面和列表式文章往往被 AI 模型大量引用,因为它们直接回答“最佳 X”提示。关于概念主题的博客文章也很强。登录页面和首页几乎不会因特定查询而被引用——不要优先处理这些。

主题相关性:将页面主题与 AI 可见性中的主题进行交叉引用。如果页面涵盖的主题中品牌具有高相关性但低可见性,那么引用差距就更具可开发性。

向用户展示一个按排名排列的 3–5 个要修复的页面 短列表,显示引用差距并为每个页面提供一行诊断:

#页面自有引用数差距诊断
1/compare/best-session-replay-tools49−131竞争对手涵盖了怒气点击、滚动深度、移动端回放;此页面没有
2/compare/best-ab-testing-platforms-for-mobile-apps30−95缺少统计方法解释和常见问题;对手两者都有

询问:“您想先修复哪个页面?” 等待他们的选择。


第4步 — 诊断所选页面

使用 web_fetch 或 Chrome(如果可用)获取所选自有页面的实际内容。然后以相同方式获取主要竞争页面的内容。仔细阅读两者。

在以下维度上进行比较:

回答直接性——自有页面是否在前两句话中回答了核心 AI 提示?获得引用的竞争页面通常如此。如果自有页面将答案埋藏起来,这是第一个需要修复的地方。

常见问题覆盖——自有页面是否有结构化的常见问题块?统计问题数量。在引用中占主导地位的竞争页面通常有 5–10 个直接问答。如果自有页面没有,或者常见问题隐藏在散文中,这是一个高价值的修复点。

具体性——自有页面是否对产品做出了具体的声明(“跟踪怒气点击、滚动热图和会话录制同时进行”)还是模糊的声明(“帮助您了解用户行为”)?AI 模型引用具体内容,而非泛泛之谈。

缺失章节——竞争对手有哪些 H2 章节是自有页面没有的?逐一列出。这些是需要填补的空白。

竞争框架——自有页面是否公平地承认了竞争格局?诚实地比较工具比假装替代品不存在的页面更能获得 AI 回答中的良好排名。

结构信号——schema 标记、标题层级、目录、比较表格。这些可以提高 AI 模型的可解析性。

在开始写作之前,将诊断结果总结为一个简短的发现列表。用户应该能够看到你发现了什么并在你开始改写前同意。


第5步 — 生成改写

基于诊断结果,生成修订版本。优先选择外科手术式的章节级补丁而不是全页改写,除非该页面存在根本性的结构问题——有针对性的改写审核更快、更容易批准,并且更不容易破坏已经有效的部分。

章节级补丁的格式

对于每个更改的章节,显示清晰的对比:

### 章节:[H2 标题]

改写前:
[原文,引用或转述]

改写后:
[修订文本——完整的真实句子,不是骨架]

原因:[一句与诊断结果相关的理由]

要修复的内容,按优先级排序

  1. 开篇段落——重写它,在前两句话中直接回答核心 AI 提示。不要让读者滚动才能找到答案。

  2. 缺失章节——添加竞争对手有而自有页面没有的 H2 章节。完整写入,包含特定于 Amplitude 的功能和具体细节。

  3. 常见问题块——如果缺失,添加一个。如果较弱,扩展它。使用 AI 可见性中的真实提示(从相关主题的 get_ai_visibility_prompts 获取)作为问题来源。每个答案应为 2–4 句话,直接,并至少包含一个产品特定事实。

  4. 具体性升级——找到每个模糊的句子(“帮助团队了解行为”)并将其替换为具体的内容(“显示点击热图、滚动深度、怒气点击和死点击,以及漏斗流失情况,这样您就能确切知道用户在哪里放弃以及原因”)。

  5. 比较表格——如果页面比较工具且没有功能表,则添加一个。AI 模型喜欢引用结构化的比较数据。

要更新的元数据字段

始终在改写中包含更新的元数据字段:

  • metaTitle——50–60 个字符,关键词丰富
  • metaDescription——140–160 个字符,回答核心查询并包含行动号召
  • slug——确认其正确性;仅在明显次优时建议更改

第6步 — 发布前模拟(可选但推荐)

在推送到 CMS 之前,提一下 AI 可见性的“模拟更改”功能:

“AI 可见性有一个‘模拟更改’功能,可以在您发布之前预测更新后的内容会如何表现。如果您想先运行模拟,请将修改后的内容粘贴到 AI 可见性仪表板的‘模拟更改’中,并查看预计的引用改进。我可以等待,或者现在就推送草稿,您可以并行模拟。”

让用户决定。如果他们想先模拟,在此暂停并告诉他们要粘贴什么。如果他们准备推送,直接进入第7步。


第7步 — 将更新推送到 CMS

使用你在第0步中发现的信息。

如果 CMS MCP 已连接

这是对现有页面的更新,不是新文档。使用更新操作,而不是创建:

Sanity —— 使用 patch_document_from_markdown 并传入现有页面的文档 ID。只修补已更改的字段。如果你没有文档 ID,请向用户确认:“这个页面的 Sanity 文档 ID 是什么?” 请不要在未明确指示的情况下使用 publish_documents。

Contentful —— 使用 update_entry 并传入条目 ID。只修补更改的字段。设置 published: false 使其进入草稿/审核状态。

HubSpot —— 使用 update_blog_post 并传入文章 ID。设置 state: DRAFT。

WordPress —— 使用 wp_update_post 并传入文章 ID。设置 status: draft。

Ghost —— 使用 update_post 并传入文章 ID。设置 status: draft。

Webflow —— 使用 update_cms_item 并传入项目 ID。保持未发布状态。

推送后,确认:“完成——修改后的 [页面标题] 已作为草稿保存在 [CMS] 中。这是它的 ID/URL:[链接]。请在发布前在那里审核。”

如果没有 CMS 连接

将完整的修订内容输出为干净的 Markdown 块,结构化为差异:

  • 保持不变的部分:标记为 [未更改]
  • 新增或重写的部分:完整显示
  • 更新的元数据字段放在顶部

然后提供:“想现在连接 [CMS] 以便下次我能直接推送吗?只需大约 2 分钟。”

即使 CMS 推送成功,也始终提供 Markdown 输出,以便团队有本地副本。


什么使页面值得被 AI 引用

目标是成为 AI 模型在回答您类别中的问题时首选引用的来源。一些始终有效的原则:

  • 快速作答。 页面的前两句话权重极高。如果答案在第 40 行,AI 模型通常根本不会引用该页面。
  • 常见问题块是引用磁石。 结构化的问答直接映射到 AI 模型接收的提示格式。比较页面上一个包含 5 个问题的常见问题块可以使引用数量翻倍。
  • 具体性胜过权威性。 一个说“Amplitude 在低于 100 毫秒的延迟下捕获怒气点击、滚动深度和用户会话录制”的页面,会比一个说“我们帮助您了解用户”的页面获得更多引用——即使后者来自更大的品牌。
  • 比较表会被抓取。 AI 模型喜欢结构化数据。一个功能比较表被引用的频率远高于以散文形式编写的相同信息。
  • 公平的竞争对手覆盖率表明可信度。 承认竞争对手做得好的地方——同时解释为什么该品牌更适合特定用例的页面——比纯促销文案更被视为权威来源。

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

amplitude/builder-skills

Performs deep analysis of a specific Amplitude chart to explain trends, anomalies, and likely drivers. Use when a metric looks unusual, investigating a spike or drop, or understanding the "why" behind numbers.

amplitude/builder-skills

Deeply analyze Amplitude dashboards by analyzing key charts, surfacing top areas for concern and takeaways, identify anomalies, then explain changes using customer feedback trends.

amplitude/builder-skills

Designs A/B tests with proper metrics and variants, analyzes running or completed experiments, and interprets results with statistical rigor. Use when setting up experiments, checking experiment status, analyzing results, or making ship decisions.

amplitude/builder-skills

Synthesizes customer feedback into actionable themes including feature requests, bugs, pain points, and praise. Use when planning product roadmap, understanding user sentiment, investigating specific issues, or preparing voice-of-customer reports.

amplitude/builder-skills

Analyze MCP server usage instrumented with Amplitude's MCP Analytics SDK: break usage and errors down by tool, read the rationales within each tool to see what callers are trying to do, and produce a prioritized write-up of actionable fixes. Use this skill whenever the user asks to understand how their MCP server is being used, what agents/users are trying to do with it, why tool calls are failing, what to fix or improve in their MCP server, or asks for an "MCP usage report", "tool error analysis", "intent analysis", "rationale clustering", or "MCP insights". Also trigger when the user mentions [MCP]-prefixed events, tool rationale, tool call errors, or just finished instrumenting their MCP server and wants to see what the data says. Requires the Amplitude MCP connector.

amplitude/builder-skills

Read lost deals and churned accounts from your CRM, extract reasons clustered by theme (missing features, pricing, competitors, UX), and write a prioritized weekly analysis with product improvement recommendations. Use before roadmap planning or to build the case for prioritizing retention work.

amplitude/builder-skills

Creates Amplitude charts from natural language descriptions, handling event selection, filters, groupings, and visualization choices. Use when you know what you want to measure but prefer not to build the chart manually.

amplitude/builder-skills

Guide an Amplitude user through building a custom agent by suggesting use cases grounded in their role and data, shaping the idea into a well-formed spec, and generating a ready-to-run Global Agent deeplink that creates it. Use to create, build, or set up a custom agent, automate a recurring analysis, or put a repeated report on a schedule.

amplitude/builder-skills

Builds comprehensive Amplitude dashboards from requirements or goals, organizing charts into logical sections with appropriate layouts. Use when creating a complete dashboard from scratch or assembling existing charts into a cohesive view.

amplitude/builder-skills

Monitors all active and recently completed experiments across Amplitude projects, triages them by importance, then runs deep analysis and reporting on the most impactful ones. Use when the user asks to "check on experiments", "experiment status", "experiment review", "what experiments are running", or wants a periodic experiment health report.

amplitude/builder-skills

Pull Intercom tickets and Slack support messages from the past 7 days, classify each signal, enrich with CRM data (ARR, plan, renewal), score by customer value and churn risk, and output a tiered priority report saved to Drive. Use when you need a fast, data-driven view of what support signals matter most.

amplitude/builder-skills

Use this skill whenever a user wants to win AI citations on prompts that competitors currently dominate — whether they say "competitors are getting cited instead of us", "we're losing on these prompts", "how do I outrank [competitor] in AI answers", "find prompts where we should be winning", "create content to beat [competitor]", or any variation where the goal is capturing AI share on prompts a competitor currently owns. This skill pulls competitor visibility data from AI Visibility, identifies the specific prompts where competitors win and Amplitude is absent, clusters them by intent, and produces targeted comparison pages, alternatives content, or rebuttal assets — then pushes drafts to CMS. Trigger on any mention of competitor, prompt hijack, outrank, or "why is [competitor] getting cited instead of us".

amplitude/builder-skills

Use this skill whenever a user wants to turn AI Visibility data into published content — whether they say "find content gaps", "what should we write about", "which topics have low visibility", "help me get cited by AI models", "create a blog post from our AI Visibility gaps", "we're losing to competitors on these prompts", or any variation where they want to go from AI visibility weakness to a draft article, landing page, or FAQ. This skill connects directly to Amplitude AI Visibility data (topics, prompts, visibility scores, citations, competitor data, full LLM responses and sources) and produces a publish-ready content brief plus full article draft. If the user mentions CMS (WordPress, Webflow, Contentful, Sanity, HubSpot, Ghost, Shopify), also trigger this skill to push the draft directly. Trigger even if they just say something vague like "what content should we create?" in an AI Visibility context.

amplitude/builder-skills

Use this skill whenever a user wants to test content variants before publishing to find which one will get cited most by AI models — whether they say "which version of this content will perform better", "test this article before we publish", "simulate how AI will respond to this content", "which angle should we use", "generate content variants and pick the winner", "run a simulation before publishing", or any variation where the goal is data-driven content selection rather than gut-feel publishing. This skill takes an identified content opportunity, generates 2–3 distinct variants with different angles or structures, scores them against actual AI model responses from AI Visibility, references the Simulate Changes feature for pre-publish validation, and produces a clear recommendation on which variant to publish — then pushes the winner to CMS. Trigger on any mention of "simulate", "test variants", "which performs better", "A/B content", or "before we publish".

amplitude/builder-skills

Use this skill whenever a user wants to understand which external sources are being cited by AI models on topics relevant to their brand, and wants to create content that will outrank those sources — whether they say "what sources are AI models citing", "why is [third-party site] being cited instead of us", "we want to be the definitive source on X", "build something that gets cited more than G2 or TechRadar", "create an authoritative asset", or any variation where the goal is producing a new reference asset (definition page, benchmark, methodology, glossary, comparison hub) designed to beat existing top-cited sources. This skill analyzes AI Visibility source data, reverse-engineers what makes top-cited pages authoritative, and produces a superior source asset — then pushes it to CMS as a draft. Trigger on any mention of "sources", "third-party citations", "authoritative content", "definitional pages", or "outrank".

amplitude/builder-skills

Instrument a Node/TypeScript MCP server with Amplitude's @amplitude/mcp-analytics SDK so tool calls, sessions, and rationale are tracked as Amplitude events. Use this skill whenever the user wants to add Amplitude analytics to their MCP server, mentions "MCP Analytics", "@amplitude/mcp-analytics", "instrument my MCP server", "track MCP tool calls", "add rationale to my MCP tools", or wants agent traffic (Claude, Cursor, ChatGPT) attributed back to Amplitude. Also use for adding UTM tagging to MCP-returned links, or for troubleshooting identity/user_id mismatches between MCP events and web/mobile Amplitude data.

amplitude/builder-skills

Instruments a pull request with Amplitude analytics that conform to the project's existing taxonomy. Reads the tracking plan via the Amplitude MCP server (events, properties, naming conventions), analyzes the PR diff to find the few user actions genuinely worth tracking, detects the codebase's SDK and tracking patterns, and adds instrumentation that matches both. Optionally (opt-in) stages new events and properties on an Amplitude tracking-plan branch for data-governance review. Use when asked to "instrument this PR", "add analytics to this change", "add tracking", "add Amplitude events", "instrument this feature", or "what should I track here".

amplitude/builder-skills

Diagnoses product health by cross-referencing Amplitude analytics (dashboards, charts, funnels, feedback, AI agent analytics), optionally Datadog (errors, latency, stack traces), and optionally Slack (qualitative feedback, bug reports, feature requests). Identifies what's broken, what's working, and what to do about it — with root causes, not just symptoms. Use when asked to "diagnose my product", "what's going on", "product health check", "what's broken", "where are users struggling", "give me a product diagnosis", or "what should I focus on".

amplitude/builder-skills

Turn one or more meeting transcripts, notes, or Slack threads into concise takeaways and clear action items with DRIs. Works with a single meeting or a batch from the whole week.

amplitude/builder-skills

Summarizes B2B account health by analyzing usage patterns, engagement trends, risk signals, and expansion opportunities. Use for customer success reviews, renewal preparation, QBRs, or account prioritization.

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