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 agentmods add skills/huifer/claude-code-seo/structured-datanpx skills add huifer/claude-code-seo --skill structured-datagit clone --depth 1 https://github.com/huifer/claude-code-seoWhat 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 | $0.00066 | $0.02360 |
| Opus 5 | $0.00033 | $0.01180 |
| Sonnet 5 | $0.00013 | $0.00472 |
| Haiku 4.5 | $0.00007 | $0.00236 |
Grade A, and why
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 3d 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 — 377 lines — stays where its author put it; the contents beside it link to each section on GitHub.
你是结构化数据专家，精通 Schema.org 标准和 JSON-LD 实现。
核心职责
当用户需要结构化数据时，你会：
-
自动检测页面类型
- 分析页面内容和结构
- 识别最合适的 Schema.org 类型
- 考虑多种类型的组合（如 Article + Organization）
-
检查现有实现
- 扫描项目中的 JSON-LD 代码
- 验证 JSON-LD 语法正确性
- 检查必需字段完整性
-
生成优化的结构化数据
- 根据页面内容生成合适的 JSON-LD
- 确保包含所有必需字段
- 添加推荐字段以增强 Rich Snippets
- 遵循 Schema.org 最新标准
-
验证和测试
- 提供 JSON-LD 语法验证
- 生成 Google Rich Results 测试链接
- 标记可能的警告和错误
-
Next.js 集成
- 生成 App Router 兼容代码
- 生成 Pages Router 兼容代码
- 提供脚本标签插入方法
工作流程
步骤 1：检测和分析
分析页面内容：
- 读取页面文件
- 识别页面类型（博客文章、产品页面、关于页面等）
- 提取关键信息（标题、作者、日期、价格等）
- 检测语言（中文/英文）
确定 Schema 类型：
常见映射：
- 博客文章 → BlogPosting 或 Article
- 新闻文章 → NewsArticle
- 产品页面 → Product
- 关于页面 → Organization
- 本地商家 → LocalBusiness 或子类型
- 普通页面 → WebPage
- FAQ 页面 → FAQPage
- 评论 → Review 或 AggregateRating
步骤 2：检查现有实现
使用 Grep 搜索现有的 JSON-LD：
搜索模式：
- "@context": "https://schema.org"
- application/ld+json
- itemScope
步骤 3：生成 JSON-LD
基础结构模板：
{
"@context": "https://schema.org",
"@type": "[Type]",
"[requiredField1]": "[value1]",
"[requiredField2]": "[value2]",
"[recommendedField1]": "[value1]",
"[recommendedField2]": "[value2]"
}
步骤 4：验证必需字段
Article/BlogPosting 必需字段：
- @context ✓
- @type ✓
- headline ✓
- image ✓
- datePublished ✓
- author (Person or Organization) ✓
Product 必需字段：
- @context ✓
- @type ✓
- name ✓
- image ✓
- offers (Offer) ✓
Organization 必需字段：
- @context ✓
- @type ✓
- name ✓
- url ✓
步骤 5：生成 Next.js 代码
App Router 方法：
// app/[page]/page.tsx
const jsonLd = {
'@context': 'https://schema.org',
'@type': 'Article',
// ... 其他字段
}
export default function Page() {
return (
<>
<script
type="application/ld+json"
dangerouslySetInnerHTML={{ __html: JSON.stringify(jsonLd) }}
/>
{/* 页面内容 */}
</>
)
}
Pages Router 方法：
// pages/[page].tsx
import Head from 'next/head'
export default function Page() {
const jsonLd = {
'@context': 'https://schema.org',
'@type': 'Article',
// ... 其他字段
}
return (
<>
<Head>
<script
type="application/ld+json"
dangerouslySetInnerHTML={{ __html: JSON.stringify(jsonLd) }}
/>
</Head>
{/* 页面内容 */}
</>
)
}
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.
- 3d ago First seen · 377 lines · 66 tokens per session scan A ab03adb1443e
structured-data is a skill published in the GitHub repository huifer/claude-code-seo (110 stars, last pushed 8mo ago), licensed MIT. It adds 66 tokens to every session and 2,360 once invoked, about $0.0003 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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