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 jrr996shujin-png/openclaw-seo-aeo-skills --skill structured-datagit clone --depth 1 https://github.com/jrr996shujin-png/openclaw-seo-aeo-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/jrr996shujin-png/openclaw-seo-aeo-skills/structured-data)<a href="https://agentmods.dev/skills/jrr996shujin-png/openclaw-seo-aeo-skills/structured-data"><img src="https://agentmods.dev/badge/skills/jrr996shujin-png/openclaw-seo-aeo-skills/structured-data/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/jrr996shujin-png/openclaw-seo-aeo-skills/structured-data"><img src="https://agentmods.dev/badge/skills/jrr996shujin-png/openclaw-seo-aeo-skills/structured-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00072 | $0.01517 |
| Opus 5.5 | $0.00029 | $0.00607 |
| Sonnet 5.5 | $0.00014 | $0.00303 |
| Haiku 4.5 | $0.00007 | $0.00152 |
Grade A, and why
seo-structured-data 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 2mo 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
结构化数据诊断模块
本模块负责检查网站的结构化数据实现,满分 15 分。结构化数据是让搜索引擎和 AI 引擎理解页面内容语义的关键——没有它,你的内容只是一堆文字;有了它,引擎能准确知道"这是一篇文章""这是一个 FAQ""这是一家公司"。
检查项
1. Schema Markup(6 分)
检查方法:
- 用
web_fetch获取页面 HTML - 搜索 JSON-LD 块(
<script type="application/ld+json">) - 搜索 Microdata 属性(
itemscope、itemtype、itemprop) - 解析找到的 Schema,检查:
- 使用了哪些 Schema 类型(Organization、WebSite、Article、FAQ、BreadcrumbList、Product、LocalBusiness 等)
- 必填字段是否完整
- 是否有嵌套 Schema(如 Article 内嵌 Author)
- JSON-LD 语法是否正确
- 根据页面类型评估是否使用了合适的 Schema:
- 首页:Organization + WebSite
- 文章页:Article + Author + BreadcrumbList
- FAQ 页:FAQPage
- 产品页:Product
- 本地商家:LocalBusiness
评分:
- 6 分:有 JSON-LD + 使用了与页面类型匹配的 Schema + 必填字段完整
- 4 分:有 Schema 但类型不够完整或缺少部分推荐字段
- 2 分:有 Schema 但类型不匹配或语法有错误
- 0 分:无任何 Schema Markup
输出格式:
状态:✅/⚠️/❌
Schema 格式:JSON-LD / Microdata / 无
检测到的 Schema 类型:
- Organization ✅(字段完整度 X%)
- Article ⚠️(缺少 datePublished)
- ...
推荐但缺失的 Schema:
- FAQPage(页面有 FAQ 内容但未标记)
- BreadcrumbList(有面包屑导航但未加结构化标记)
修复建议:(具体 JSON-LD 代码示例)
2. Open Graph 标签(4 分)
Open Graph 决定了你的页面在社交平台(Facebook、LinkedIn、微信等)分享时的展示效果,同时也是 AI 引擎理解页面元信息的参考。
检查方法:
- 检查以下必填 OG 标签:
og:titleog:descriptionog:imageog:urlog:type
- 检查
og:image的 URL 是否可访问 - 检查
og:title和og:description的长度是否合适 - 检查
og:locale是否与页面语言一致
评分:
- 4 分:5 个核心标签齐全 + 图片可访问 + 长度合适
- 3 分:核心标签齐全但有小问题(如图片不可访问)
- 1 分:有部分 OG 标签但不完整
- 0 分:无任何 OG 标签
输出格式:
状态:✅/⚠️/❌
OG 标签检查:
| 标签 | 状态 | 值 |
|------|------|-----|
| og:title | ✅/❌ | "..." |
| og:description | ✅/❌ | "..." |
| og:image | ✅/❌ | URL(可访问/不可访问)|
| og:url | ✅/❌ | "..." |
| og:type | ✅/❌ | "..." |
修复建议:(具体建议)
3. Twitter Card 标签(2 分)
检查方法:
- 检查
twitter:card(summary / summary_large_image) - 检查
twitter:title - 检查
twitter:description - 检查
twitter:image - 如果缺少 twitter 专用标签,检查是否有 OG 标签可作为 fallback
评分:
- 2 分:twitter:card 存在 + 核心标签齐全(或 OG fallback 充分)
- 1 分:有部分标签但不完整
- 0 分:无任何 Twitter Card 标签且 OG 标签也无法作为 fallback
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.
- 2mo ago First seen · 152 lines · 72 tokens per session scan A 097d9245ed05
seo-structured-data is a skill published in the GitHub repository jrr996shujin-png/openclaw-seo-aeo-skills (13 stars, last pushed 8mo ago), licensed MIT. It adds 72 tokens to every session and 1,517 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
seo-structured-data compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| seo-structured-datajrr996shujin-png/openclaw-seo-aeo-skills | Skill | 13 | 8mo ago | MIT | A | 72 | Claude Code, Codex |
| ansvisor-aeo-coach-standaloneansvisor/ansvisor | Skill | 232 | yesterday | MIT | A | 148 | Claude Code, Codex |
| ansvisor-aeo-coachansvisor/ansvisor | Skill | 232 | yesterday | MIT | A | 241 | Claude Code, Codex |
| aeroCanonry/canonry | Skill | 198 | yesterday | MIT | A | 93 | Claude Code |
| canonryCanonry/canonry | Skill | 198 | yesterday | MIT | A | 64 | Claude Code |
| promptsansvisor/ansvisor | Skill | 232 | yesterday | MIT | A | 25 | Claude Code, Codex |
| fanoutansvisor/ansvisor | Skill | 232 | yesterday | MIT | A | 23 | Claude Code, Codex |