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 content-structuregit 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/content-structure)<a href="https://agentmods.dev/skills/jrr996shujin-png/openclaw-seo-aeo-skills/content-structure"><img src="https://agentmods.dev/badge/skills/jrr996shujin-png/openclaw-seo-aeo-skills/content-structure/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/content-structure"><img src="https://agentmods.dev/badge/skills/jrr996shujin-png/openclaw-seo-aeo-skills/content-structure.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 | $0.00090 | $0.01752 |
| Opus 5.5 | $0.00036 | $0.00701 |
| Sonnet 5.5 | $0.00018 | $0.00350 |
| Haiku 4.5 | $0.00009 | $0.00175 |
Grade A, and why
seo-content-structure 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
内容结构诊断模块
本模块负责检查页面的内容结构是否利于搜索引擎和 AI 引擎解析,满分 15 分。内容结构的好坏直接决定了 AI 引擎能否准确提取和引用你的内容——一个结构清晰的页面,AI 能精准引用其中的段落;一个结构混乱的页面,AI 可能直接跳过它。
检查项
1. Meta 标签质量(4 分)
检查方法:
- 提取
<title>标签:- 是否存在
- 长度是否在 30-60 字符之间(中文 15-30 字)
- 是否包含目标关键词(如果能从内容推断)
- 是否唯一且描述性(非通用模板如"首页 - 公司名")
- 提取
<meta name="description">:- 是否存在
- 长度是否在 120-160 字符之间(中文 60-80 字)
- 是否为具有行动号召力的摘要
- 是否与页面实际内容相关
- 检查是否有重复的 title 或 description 标签
评分:
- 4 分:title + description 均存在、长度合适、内容相关
- 3 分:均存在但有长度或质量问题
- 1 分:缺少其中一个或两者质量都差
- 0 分:title 和 description 都缺失
输出格式:
状态:✅/⚠️/❌
Title:「...」(X 字符)
- 长度:合适/过长/过短
- 关键词:包含/未包含
Description:「...」(X 字符)
- 长度:合适/过长/过短
- 行动力:强/弱
修复建议:(含改写示例)
2. H1-H4 标题层级(4 分)
标题层级是 AI 引擎理解页面内容组织结构的核心线索。一个语义清晰的标题层级就像一本书的目录——AI 可以据此快速定位和引用特定部分。
检查方法:
- 提取所有
<h1>到<h6>标签 - 检查:
- H1 是否唯一(一个页面应只有一个 H1)
- H1 是否在页面顶部
- 标题层级是否连续(不应从 H1 直接跳到 H4)
- 标题内容是否具有描述性(非通用文字如"更多")
- 是否有空标题标签
- 标题是否过长(建议 < 70 字符)
- 生成标题大纲树,展示层级关系
评分:
- 4 分:H1 唯一 + 层级连续 + 内容描述性强
- 3 分:H1 唯一但有层级跳跃
- 1 分:多个 H1 或层级混乱
- 0 分:无任何标题标签或大量空标题
输出格式:
状态:✅/⚠️/❌
H1 数量:X 个
标题大纲:
H1: [标题内容]
H2: [标题内容]
H3: [标题内容]
H2: [标题内容]
H3: [标题内容]
H4: [标题内容]
层级连续性:✅ 连续 / ⚠️ 有跳跃(H1→H3)
修复建议:(具体建议)
3. 列表独立性(2 分)
AI 引擎特别善于提取格式化列表作为回答。但列表需要"独立可理解"——即脱离上下文也能看懂每一项。
检查方法:
- 提取所有
<ul>、<ol>列表 - 检查:
- 列表项是否自包含(每项是否有足够的上下文,不依赖前一项理解)
- 列表前是否有引导性标题或段落说明
- 列表项长度是否合适(太短可能缺乏信息,太长可能需要拆分)
- 是否有嵌套列表(适度嵌套可以,过深不好)
评分:
- 2 分:列表有引导、项目自包含、结构合理
- 1 分:有列表但可读性或独立性有问题
- 0 分:无列表或列表质量很差
4. 结构化表格(2 分)
表格是数据密集内容的最佳呈现方式,也是 AI 引擎最容易直接引用的格式之一。
检查方法:
- 提取所有
<table>标签 - 检查:
- 是否有
<thead>/<th>表头 - 是否有
<caption>或<summary>描述 - 表格是否用于布局而非数据(反模式)
- 表格是否在移动端可滚动(
overflow-x: auto等)
- 是否有
- 如果页面有比较性数据但未使用表格,标注为优化机会
评分:
- 2 分:表格有表头 + 描述 + 非布局用途
- 1 分:有表格但缺少表头或描述
- 0 分:数据适合表格但未使用,或表格用于布局
5. FAQ 格式(3 分)
FAQ 是 AEO 的黄金格式——问答形式天然匹配 AI 引擎的"问答"检索模式。
检查方法:
- 检查是否有 FAQPage Schema(与结构化数据模块联动)
- 检查页面中是否有问答格式的内容(即使未标记为 FAQ):
- 以"?"结尾的标题后跟段落
- "Q: ... A: ..." 格式
<details>/<summary>折叠面板
- 如果有问答内容,检查:
- 问题是否自然、完整(像真实用户会问的)
- 答案是否在问题后立即给出(不要问了一页才回答)
- 答案的第一句话是否能独立作为回答
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 · 154 lines · 90 tokens per session scan A 9d86099454d7
seo-content-structure is a skill published in the GitHub repository jrr996shujin-png/openclaw-seo-aeo-skills (13 stars, last pushed 8mo ago), licensed MIT. It adds 90 tokens to every session and 1,752 once invoked, about $0.0004 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-content-structure compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| seo-content-structurejrr996shujin-png/openclaw-seo-aeo-skills | Skill | 13 | 8mo ago | MIT | A | 90 | 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 |