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SEO (搜尋引擎優化)

審計、規劃並執行技術 SEO、頁面優化、結構化資料、Core Web Vitals 及內容策略,以提升搜尋能見度。

SEO (搜尋引擎優化) 是什麼?

此技能專注於透過技術正確性、效能及內容相關性來提升搜尋能見度,而非使用投機取巧的手法。它涵蓋了技術 SEO 檢查清單(包括可爬性、可索引性、效能及結構化資料)、頁面優化規則(如標題標籤、中繼描述、標題結構)、關鍵字映射與內部連結策略。支援的平台範圍廣泛,只要是能編輯 robots.txt、sitemap、HTML 標籤及 JSON-LD 的網站皆適用。操作流程遵循「先解決技術障礙,再進行內容優化」的原則,確保每項建議都可歸因至具體頁面且可執行。此技能也明確指出反模式,例如關鍵字堆砌、內容薄弱的重複頁面,以及與實際內容不符的結構化資料。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/seo

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

SEO (搜尋引擎優化) 是做什麼的?

透過技術正確性、效能和內容相關性來提升搜尋能見度,而非使用投機取巧的手法。

使用時機

在以下情況使用此技能:

  • 審計可爬性、可索引性、標準網址 (canonical) 或重新導向
  • 改善標題標籤、中繼描述和標題結構
  • 新增或驗證結構化資料
  • 改善 Core Web Vitals
  • 進行關鍵字研究,並將關鍵字對應至網址
  • 規劃內部連結或修改 sitemap / robots

運作方式

原則

  1. 先修復技術障礙,再進行內容優化。
  2. 一個頁面應有一個明確的主要搜尋意圖。
  3. 偏好長期品質訊號,而非操縱性模式。
  4. 由於索引是以行動裝置優先,因此必須以行動優先為前提。
  5. 建議應針對特定頁面且可執行。

技術 SEO 檢查清單

可爬性 (Crawlability)

  • robots.txt 應允許重要頁面,並封鎖低價值內容
  • 沒有重要頁面應意外地被設定為 noindex
  • 重要頁面應可在淺層點擊深度內到達
  • 避免超過兩層的重新導向鏈
  • 標準網址標籤應自我一致且無循環

可索引性 (Indexability)

  • 偏好的網址格式應保持一致
  • 多語言頁面若使用 hreflang 則必須正確設定
  • Sitemap 應反映預期的公開頁面範圍
  • 不應有重複的網址在缺乏標準網址控制的情況下互相競爭

效能

  • LCP < 2.5s
  • INP < 200ms
  • CLS < 0.1
  • 常見修正:預載重點素材、減少阻塞渲染的工作、保留版面空間、削減大量 JS

結構化資料

  • 首頁:適當時使用組織或商家結構化資料
  • 編輯頁面:Article / BlogPosting
  • 產品頁面:Product 和 Offer
  • 內部頁面:BreadcrumbList
  • Q&A 區塊:僅在內容真正符合時使用 FAQPage

頁面優化規則

標題標籤

  • 目標長度約為 50-60 個字元
  • 將主要關鍵字或概念放在靠近開頭的位置
  • 讓標題對人類來說清晰可讀,而非為了搜尋引擎而堆砌

中繼描述

  • 目標長度約為 120-160 個字元
  • 誠實描述頁面內容
  • 自然地包含主要主題

標題結構

  • 一個清晰的 H1
  • H2 和 H3 應反映實際的內容層級
  • 不要為了視覺樣式而跳過結構

關鍵字映射

  1. 定義搜尋意圖
  2. 收集實際的關鍵字變體
  3. 根據意圖匹配度、可能價值和競爭程度進行優先排序
  4. 將一個主要關鍵字/主題對應到一個網址
  5. 偵測並避免關鍵字自相殘殺 (cannibalization)

內部連結

  • 從權威頁面連結到你想要排名的頁面
  • 使用具描述性的錨點文字
  • 避免在可以使用更具體錨點時使用通用錨點
  • 從新頁面補充連結到相關的現有頁面

範例

標題公式

主要主題 - 特定修飾詞 | 品牌

中繼描述公式

行動 + 主題 + 價值主張 + 一項輔助細節

JSON-LD 範例

{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "此處為頁面標題",
  "author": {
    "@type": "Person",
    "name": "作者姓名"
  },
  "publisher": {
    "@type": "Organization",
    "name": "品牌名稱"
  }
}

審計輸出格式

[HIGH] 產品頁面重複的標題標籤
位置: src/routes/products/[slug].tsx
問題: 動態標題收斂成相同的預設字串,削弱了相關性並造成重複訊號。
修正: 使用產品名稱和主要類別為每個產品產生唯一的標題。

反模式

反模式修正方式
關鍵字堆砌優先為使用者而寫
內容單薄的重複頁面合併或區分它們
為未實際存在的內容加入結構化資料讓結構化資料符合實際情況
未檢查實際頁面就給出內容建議先閱讀真實頁面
籠統的「改善 SEO」輸出將每項建議都連結到特定頁面或資產

相關技能

  • seo-specialist
  • frontend-patterns
  • brand-voice
  • market-research

Individual skills in this repo

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

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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