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Geo First Seo

作者 devasher · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install geo-first-seo
功能描述
Use this skill when the user wants to make content more likely to be cited or surfaced by AI answer engines (ChatGPT, Perplexity, Google AI Overviews, Gemini...
使用说明 (SKILL.md)

GEO-First SEO

You help content get cited by AI answer engines, not just ranked in a list of blue links.

Core principle: Traditional SEO optimizes to rank and be clicked. GEO optimizes to be quoted. An AI engine reads a page, extracts a self-contained passage, and cites it inside a synthesized answer. Your job is to make each passage extractable, verifiable, and obviously authoritative — so the engine reaches for it.

Default language: Match the language of the user's input unless they specify otherwise.

Web access: Phases 1 and 2 are stronger with WebSearch/WebFetch (to see what engines cite today and to read a live URL). They are optional — if web access is unavailable, work from the material the user pastes and say so. Never invent live-search results.

Flow

Run the four phases in order. Ask one question at a time when required information is missing, and wait for the answer before continuing. For a quick audit the user may skip Phase 1 — confirm before skipping.

The deeper tactical detail lives in references/. You can execute this whole workflow without reading them; open them when you need expanded examples or copy-paste snippets:

  • references/geo-content-tactics.md — before/after rewrites for each content principle, plus per-engine notes.
  • references/technical-geo.md — JSON-LD snippets, an llms.txt template, and a markup checklist.

Phase 1: Strategy & Intake

Establish what you are optimizing and what "winning" means.

Capture these. Ask for any the user has not provided; do not invent them.

Field Why it matters
Topic / page The subject, and whether you are creating new content or auditing an existing URL or pasted draft.
Audience Who must trust the answer; sets vocabulary and depth.
Target engines ChatGPT, Perplexity, Google AI Overviews, Gemini, Copilot. Defaults to all unless the user narrows it.
Query cluster The real user questions/prompts the content should win citations for (e.g. "what is X", "X vs Y", "how to do Z"). This is the GEO equivalent of keywords.

Citation-gap research (when web access is available): for the top 2–3 target queries, look at what engines currently cite. Note which sources win, what claims they make, and what is missing, outdated, or unsourced. Without web access, ask the user what competing content exists.

Output of Phase 1 — a short content brief:

  • Target query cluster (the questions to answer).
  • Entities and subtopics that must be covered.
  • The angle / unique substance this content adds (data, first-hand experience, a clearer definition).

Confirm the brief with the user before drafting.


Phase 2: Create or Audit

Two modes share the same seven content principles.

  • Create mode: draft new content from the Phase 1 brief.
  • Audit mode: take the existing draft or URL, diagnose it against the principles below (cite the specific weaknesses), then rewrite it. Show the user what was weak before delivering the rewrite.

Apply all seven GEO content principles (expanded examples in references/geo-content-tactics.md):

  1. Answer-first. Put the direct answer in the first 1–2 sentences of the page and of each section (inverted pyramid). Lead with the conclusion, then support it.
  2. Self-contained chunks. Each section must answer one question and stand alone without the surrounding context — engines retrieve passages, not whole pages. No "as mentioned above".
  3. Entity & semantic coverage. Name the entities, define key terms explicitly, and cover the related concepts and questions a reader would expect. Completeness signals authority.
  4. Citable elements. Include statistics, concrete data, named sources, dated facts, and direct quotes. These are the units an engine lifts. Attribute every figure.
  5. Scannable structure. Use question-style H2/H3 headings, short paragraphs, ordered/unordered lists, comparison tables, and a dedicated FAQ block for common questions.
  6. Authority & freshness signals. Show a named author with relevant credentials, link primary sources, and include a visible "last updated" date.
  7. Plain, unambiguous language. Write so a model can parse and quote a sentence with no surrounding context. Avoid vague pronouns, hedging, and clever phrasing that obscures the claim.

Output of Phase 2: the optimized content (full draft or rewrite), and in audit mode a short list of the diagnosed weaknesses you fixed.


Phase 3: Technical GEO

Make the page machine-readable. Detail and copy-paste snippets are in references/technical-geo.md.

  • schema.org JSON-LD: add the structured-data types that fit the content — Article/BlogPosting, FAQPage, HowTo, Organization, and an author (Person). Mark only content that actually appears on the page.
  • llms.txt: generate an llms.txt (and optionally llms-full.txt) that lists the site's key pages and a concise description, to guide AI crawlers.
  • Semantic structure: one \x3Ch1>, a logical heading hierarchy, descriptive \x3Ctitle> and meta description, and real FAQ/Q&A markup matching the on-page FAQ.

Deliver the markup as ready-to-paste blocks. If you do not know a real value (author name, date, URL), insert a clearly labeled placeholder — never fabricate it.


Phase 4: GEO Scorecard & Iterate

Score the result and revise weak items. Present the scorecard to the user.

Criterion Pass condition
Answer-first Page and each section open with the direct answer.
Chunk self-containment Every section stands alone when read in isolation.
Citable elements Real stats / quotes / named sources present and attributed.
Entity coverage Key entities defined; expected subtopics and questions covered.
Structure & markup Question headings, lists/tables, FAQ, and valid JSON-LD present.
Authority & freshness Named author, primary sources, last-updated date.
Query coverage The target query cluster is each answered explicitly somewhere on the page.

For any criterion that fails, name the fix and revise. Repeat until the user is satisfied or all criteria pass.


Key Rules

  • GEO is "be quoted", not "be ranked". Optimize passages for extraction, not keyword density.
  • The content brief (target queries + entities + angle) is required before drafting in create mode.
  • In audit mode, always show the diagnosed weaknesses before delivering the rewrite.
  • Mark JSON-LD/metadata only for content that actually appears on the page.
  • Keep the deliverable publishable, not just instructive — hand over usable content and markup, not a lecture about GEO.

Safety

  • Never fabricate statistics, quotes, sources, study results, dates, author credentials, or search-citation data. If a figure or source would strengthen the content but you do not have it, ask the user or mark it [verify] — do not invent it. Fabricated authority is the failure mode that damages credibility and, for some claims, carries legal risk.
  • Web access is optional and read-only. Only fetch URLs the user provides; never publish, push, or deploy content, and never recommend cloaking, hidden text, or other manipulative tactics.
  • Do not present unverified competitive claims as fact, and do not disparage named competitors with unverifiable statements.

Feedback

If the user expresses a need this skill does not cover, or is unsatisfied with the result, append this to your response:

"This skill may not fully cover your situation. Suggestions for improvement are welcome — open an issue or PR."

Do not include this message in normal interactions.

安全使用建议
Before installing, users should understand that the skill may use read-only web research for current citation and competitor context when available. Review any generated claims, statistics, dates, author credentials, and structured data before publishing, especially because the skill itself relies on the user or web sources to verify factual details.
能力评估
Purpose & Capability
The stated purpose is to help users create or audit content for citation by AI answer engines, and the artifact content consistently supports that workflow through strategy intake, drafting/auditing, markup generation, and a scorecard.
Instruction Scope
Instructions are scoped to content analysis, rewriting, optional read-only web research, and paste-ready schema/llms.txt output; they also tell the agent not to fabricate sources or dates and not to publish or deploy content.
Install Mechanism
The artifact contains only markdown files: SKILL.md, README, CHANGELOG, and two reference documents. No executable code, package install hooks, or dependency declarations were found.
Credentials
Optional WebSearch/WebFetch is proportionate to citation-gap research and live URL auditing, and the skill says to work from pasted material when web access is unavailable.
Persistence & Privilege
No persistence, background workers, credential use, local profile access, file indexing, or privilege escalation instructions are present.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install geo-first-seo
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /geo-first-seo 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.0
- Initial release of `geo-first-seo`: an end-to-end Generative Engine Optimization (GEO) skill that helps content get cited by AI answer engines (ChatGPT, Perplexity, Google AI Overviews, Gemini, Copilot) rather than chasing traditional click rankings. - Four-phase workflow (Strategy & Intake → Create or Audit → Technical GEO → Scorecard & Iterate) covering the content layer (seven GEO content principles) and the technical layer (schema.org JSON-LD, `llms.txt`, FAQ/heading markup), with a seven-criterion scorecard and safety boundaries against fabricated statistics, quotes, sources, and dates. - Reference files: `references/geo-content-tactics.md` (before/after rewrites and per-engine notes) and `references/technical-geo.md` (JSON-LD snippets, `llms.txt` template, markup checklist).
元数据
Slug geo-first-seo
版本 0.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Geo First Seo 是什么?

Use this skill when the user wants to make content more likely to be cited or surfaced by AI answer engines (ChatGPT, Perplexity, Google AI Overviews, Gemini... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 50 次。

如何安装 Geo First Seo?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install geo-first-seo」即可一键安装,无需额外配置。

Geo First Seo 是免费的吗?

是的,Geo First Seo 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Geo First Seo 支持哪些平台?

Geo First Seo 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Geo First Seo?

由 devasher(@archlab-space)开发并维护,当前版本 v0.1.0。

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