Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Gingiris-1031/gingiris-skills --skill gingiris-seo-geogit clone --depth 1 https://github.com/Gingiris-1031/gingiris-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gingiris-seo-geo)<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gingiris-seo-geo"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gingiris-seo-geo/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gingiris-seo-geo"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gingiris-seo-geo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00698 | $0.06183 |
| Opus 5 | $0.00349 | $0.03092 |
| Sonnet 5 | $0.00140 | $0.01237 |
| Haiku 4.5 | $0.00070 | $0.00618 |
Grade A, and why
gingiris-seo-geo scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
⚠️ 使用前：确认你的产品类型
本 skill 默认场景：开发者工具 / 开源项目 / B2B SaaS 出海
如果你的产品是 2C 消费品 / 教育 / 应用 / 游戏，以下参数需要调整：
| 参数 | 默认值（B2B/开源） | 2C 建议值 |
|---|---|---|
| 关键词 volume 下限 | 300 | 50（长尾高转化词量少但值得做） |
| E-E-A-T 要求 | 创始人真实声音 | YMYL 品类（教育/医疗/金融）需可验证资质 + 方法论透明页 |
| 启动渠道 | PH / GitHub / HN | Reddit 垂类社区 / 小红书 / TikTok / 知乎 / Quora |
| 程序化页面风险 | 低 | 需"每页独有价值"，防 doorway page penalty |
| 关键词策略 | 单轨 BOFU + 长尾 | 加"时间窗口红利词"（如"2026 新规/改革/新题型"） |
| 外链获取渠道 | 技术媒体 / dev blog | 行业媒体 / 学校机构 / 垂直 KOL |
详细 2C 使用指南见 → references/2c-adaptation.md
SEO & GEO 双引擎增长手册
中文版
作者：Iris (生姜iris) | 版本：v1.0 (2026年4月)
核心理念
SEO 和 GEO 不是两件事，是一件事的两面。结构化数据同时服务传统搜索和 AI 搜索。
传统 SEO 解决「被搜到」，GEO 解决「被 AI 引用」。
2026 年的搜索流量已经分裂为两个入口：Google/Bing 的传统排名，和 ChatGPT/Perplexity/Claude 的 AI 回答。你的内容必须同时在两个战场上赢。
SEO + GEO 双引擎对比
| 维度 | SEO（传统搜索） | GEO（AI 搜索） |
|---|---|---|
| 目标 | Google/Bing 排名 | AI 回答中被引用 |
| 核心信号 | 反向链接 + 关键词匹配 | 结构化数据 + E-E-A-T 真实性 |
| 内容格式 | H2/H3 层级 + 长尾词覆盖 | 直接回答 + 对比表格 + FAQ Schema |
| 技术手段 | XML Sitemap + Core Web Vitals | IndexNow + robots.txt 开放 AI 爬虫 |
| 衡量方式 | GA4 自然流量 + Ahrefs 排名 | 手动检查 AI 引用频率 |
五个核心原则（2026-06-24 执行标准）
- 从 BOFU 往上做 — 先做高意向关键词（定价、对比），再做教育型内容。转化率最高的词优先。
- 真实声音是最好的 E-E-A-T — 不要让 AI 写得像 AI。用创始人声音、真实数字、亲历故事建立可信度。
- 结构化 = 可引用 — Key Stats 表格、FAQ Schema、对比矩阵让 AI 引擎直接抓取引用。
- IndexNow 是 GEO 的基础设施 — 内容更新后秒级推送到 Bing/AI 搜索，不等爬虫。
- 对比页是 SEO 金矿 — 每个竞品一个独立页面，截获决策期用户。
关键词选择标准（Ahrefs 筛选规则）
| 参数 | 标准 | 说明 |
|---|---|---|
| Volume | 300–1,000/月 | 新站专打此区间；大词竞争太激烈 |
| Keyword Difficulty | KD 5–35 | KD > 35 = 新站短期内无法排进首页 |
| Traffic Potential | 300+ | 看该词落地页的整体流量潜力，不只看单词 |
| Search Intent | 第一要务 | 写前先看该词 Google top-10（忽略 Sponsored）判意图（step-by-step 指南 vs 列表/gallery），内容必须对齐意图 |
| 竞品新词 | 优先挖 | 扒竞品 blog 最新文，找还没被 Google 爬到的新词 |
页面优化执行标准
| 规则 | 标准 | 原因 |
|---|---|---|
| 内链密度 | 每段 ≤ 2-3 个 | 多了 Google 判 spam → 降 ranking |
| 外链策略 | 主动 cite 竞品 blog | Google 视为客观 → 提信用分 → 提 ranking |
| 标题套路 | best / free / top / guide + 年份 | CTR 提升最显著的公式 |
| Meta description | 关键词 rephrase（如 "figma alternative" → "the alternative to Figma"） | 提点击率 |
| 面包屑导航 | BreadcrumbList schema + 可见 | 结构信号 + SERP 富结果提 CTR |
| Freshness | 标注最后更新日期 | freshness 信号提排名 |
| URL 结构 | 短 + 含词 + 带尾斜杠 | 可读 + 语义信号 |
What ships with it
21 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/logo.png 24 KB
- assets/star.png 23 KB
- CODE_OF_CONDUCT.md 908 B
- CONTRIBUTING.md 1.2 KB
- LICENSE 1.1 KB
- README.md 16 KB
- references/2c-adaptation.md 10 KB
- references/comparison-pages.md 5.5 KB
- references/content-sop.md 5.0 KB
- references/en/comparison-pages.md 5.1 KB
- references/en/content-sop.md 4.8 KB
- references/en/geo-evidence-standard.md 3.7 KB
- references/en/geo-optimization.md 5.4 KB
- references/en/keyword-strategy.md 4.7 KB
- references/en/seo-foundations.md 4.8 KB
- references/en/writing-voice.md 5.4 KB
- references/geo-evidence-standard.md 3.5 KB
- references/geo-optimization.md 5.5 KB
- references/keyword-strategy.md 4.5 KB
- references/seo-foundations.md 5.0 KB
- references/writing-voice.md 5.3 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 265 lines · 698 tokens per session scan A 658ab1bd7ade
gingiris-seo-geo is a skill published in the GitHub repository Gingiris-1031/gingiris-skills (79 stars, last pushed 5d ago), licensed MIT. It adds 698 tokens to every session and 6,183 once invoked, about $0.0035 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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