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产出的文章必须符合

Iris 文风 5 要素（详见 知识库/Skill知识包/iris_writing_style.md）

1. 时间锚定开场 —— 不说"SEO 很重要"，说"2026-04-10，凌晨 3 点，后台流量归零"
2. 括号旁白 —— 正文一句，括号里挤私货（"...—— 别问怎么知道的"）
3. em-dash 转折 —— 不用"但是"，用 ——
4. Key Stats 表格 —— 文章开头或 H2 下第一屏放一个硬数据表，3-5 行
5. GEO 直接答案段落 —— 文章顶部一段 30-50 字直接回答主问题，方便 AI 爬虫抽取

技术 frontmatter 模板

---
layout: post
title: "主关键词前置，副标题用冒号：不超过 60 字"
date: 2026-04-15 14:30:00 +0800
categories: [seo, growth]
tags: [...]
canonical_url: https://gingiris.tools/blog/2026/04/15/slug/
hreflang_ja: /blog/2026/04/15/slug-ja/
hreflang_ko: /blog/2026/04/15/slug-ko/
post_description: "150-160 字 meta description，含主关键词"
faq:
  - q: "直接问句"
    a: "30-50 字硬答案"
---

---

发布流程

1. 选题

• 读 gr-seo-patrol 输出，找"top 30 但没 top 10"的关键词
• 或读 gr-competitor，找对手新打法
• ❌ 不做重复主题（先 site: 查站内是否已有）

2. 写初稿

• 时间锚定开场（当前日期 + 具体场景）
• 第一屏：GEO 直接答案段（30-50 字）+ Key Stats 表（硬数据）
• H2 结构：问题 → 框架 → 案例 → 陷阱 → 下一步
• 每个 H2 下 200-400 字，不超过 600 字

3. 内链

• 向前：链接 2-3 篇已发布的同主题文章（用主关键词作 anchor）
• 向后：站内 index / hub 页
• 权重传导：从流量最大的 3 篇文章加内链到新文

4. FAQ Schema

• 3-5 个问答
• 问句必须是用户真实搜索句（从 GSC / People also ask 抓）
• 答案硬、短、可引用

5. Canonical 策略

• 默认 self-canonical
• 如果是同主题系列的分篇 → canonical 指向 master
• ja/ko 翻译版 → 自身 canonical + hreflang 互指

6. 多语言同步

• 用 scripts/sync-i18n.py（roadmap）从英文自动产日韩草稿
• 人工过一遍（机翻硬伤 + 文化适配）
• 日韩版本独立 slug，不复用英文 slug

7. 发布

• GitHub Contents API PUT（不要 git push）
• Commit message: post: {slug} ({lang})

8. 发布后 24h

• 加入 gr-seo-patrol 监控名单
• Google Search Console 手动提交
• 社交平台分发（推特 / LinkedIn / dev.to）

---

反模式

• ❌ 不要用 AI 味重的模板（"In today's digital landscape..."）—— 过不了 dbs-ai-check
• ❌ 不要 H1 堆关键词
• ❌ 不要忘记 hreflang —— 已发布的旧文补翻译时要回改原文 frontmatter
• ❌ 不要同一关键词发 3 篇 —— cannibalization 立刻找上门

---

级联推荐

• 写完 → gr-seo-patrol 加监控
• 发现是系列稿 → gr-blog-post 继续产第 2 篇并设 canonical
• 英文发完 24h → 手动触发日韩翻译

---

API 依赖

---

Citability-by-Design Spec (mandatory for NEW articles, 2026-05-18+)

Rationale: Verified 2026-05-07 that retrofitting old articles hits a ~65-68/100 citability ceiling no matter what (booster passages, surgical rewrites, splitting all produce diminishing returns). Writing new articles from this spec produces 75-85 baseline directly. Spec saves ~3 hours of post-hoc citability fixing per article.

Per-section structural requirements

Every H2/H3 section must satisfy ALL of:

1. Word count: 134-167 (the AI-extraction sweet spot validated by zubair-trabzada/geo-seo-claude scoring)

   • Under 134 → self_containment drops below 10/25
   • Over 167 → same penalty for being too long for AI chunks
   • Use a word counter as you draft

2. Opening sentence = definition pattern, one of:

   • [Thing] is [definition]
   • [Thing] refers to [scope]
   • [Thing] means [unpacking]
   • In other words, [Thing] is...
   • [Thing] can be defined as...

3. Section contains at least ONE of each:

   • ✅ Original research signal: "Our X-launch dataset", "We tracked", "Our 2026 audit measured", "Our analysis of N samples"
   • ✅ Specific number with unit: "60K stars", "30 launches", "$79/mo", "67%"
   • ✅ Specific named product/tool: "Taplio ($39/mo)", "Surfe", "PH Deck", "Loom" — by name not "[the tool]"

Heading conventions

• H1 = page title (≤ 70 chars after title-suffix fix from 2026-05-07)

• H2 should be question form ~40% of the time:

  • ✅ "How do I get cited by Perplexity in 2026?"
  • ✅ "What is the GEO three-piece set?"
  • ❌ "Perplexity citation strategy"

• Each H2 should contain primary keyword or clear question intent

Article-level requirements

• 5-12 H2 sections (sweet spot: 7-8)
• TL;DR or "Citable Statistics" block IN FIRST H2 (becomes top-scored passage)
• FAQ Schema JSON-LD at end (5+ Q&A using exact User-Search-Form questions)
• last_modified_at: frontmatter (flows through to dateModified schema)
• canonical_url self-reference
• hreflang_ja / hreflang_ko if multilingual variants exist

Citability self-check before publishing

Run before committing the article:

python3 skills/gr-geo-cite/scripts/citability-scorer.py /local/path/to/draft.html

Target: page score ≥ 75. If under 70, revise top 2 weakest passages.

Anti-patterns (avoid)

• ❌ Long expository paragraphs (200+ words) — split into 2 sections at 134-167 each
• ❌ Generic transitions ("Now let's discuss...") — replace with definition pattern
• ❌ Marketing fluff ("the best way to") — replace with measured claims with data
• ❌ "[Tool name]" placeholders — always cite the specific tool by name + price
• ❌ Bullet lists with single words — combine into prose with definition + example pattern

Real-data benchmark

Articles from 2026-05-07 audit (without this spec):

Predicted from spec (NEW articles):

The marginal value of strict compliance is ~10 points vs partial compliance.