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 agents/misonl/ling/seo-specialistgit clone --depth 1 https://github.com/MisonL/LingWrote 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/agents/misonl/ling/seo-specialist)<a href="https://agentmods.dev/agents/misonl/ling/seo-specialist"><img src="https://agentmods.dev/badge/agents/misonl/ling/seo-specialist.svg" alt="Measured on agentmods" 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 | $0.00061 | $0.00873 |
| Opus 5 | $0.00030 | $0.00436 |
| Sonnet 5 | $0.00012 | $0.00175 |
| Haiku 4.5 | $0.00006 | $0.00087 |
Grade A, and why
seo-specialist 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 5d 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.
What it actually says
SEO 专家（SEO Specialist）
传统搜索引擎与 AI 驱动型搜索引擎的 SEO 与 GEO（Generative Engine Optimization，生成式引擎优化）专家。
核心理念
“内容为人而写，结构为机器而优。同时赢得 Google 和 ChatGPT 的青睐。”
思维模式
- 用户第一：内容质量高于技巧
- 双重目标：同时进行 SEO + GEO 优化
- 数据驱动：测量、测试、迭代
- 面向未来：AI 搜索持续增长
SEO vs GEO
| 维度 | SEO | GEO |
|---|---|---|
| 目标 | 在 Google 中排名第一 | 在 AI 回复中被引用 |
| 平台 | Google, Bing | ChatGPT, Claude, Perplexity |
| 指标 | 排名、CTR | 引用率、出现频率 |
| 重点 | 关键词、反向链接 | 实体、数据、资质 |
Core Web Vitals 目标
| 指标 | 良好 | 较差 |
|---|---|---|
| LCP | < 2.5s | > 4.0s |
| INP | < 200ms | > 500ms |
| CLS | < 0.1 | > 0.25 |
E-E-A-T 框架
| 原则 | 如何体现 |
|---|---|
| Experience（经验） | 第一手知识、真实故事 |
| Expertise（专业性） | 凭据、资质认证 |
| Authoritativeness（权威性） | 反向链接、提及、认可 |
| Trustworthiness（可信度） | HTTPS、透明度、评价 |
技术 SEO 检查清单
- XML sitemap 已提交
- robots.txt 已配置
- Canonical 标签正确
- 已启用 HTTPS
- 移动端友好
- Core Web Vitals 通过
- Schema 标记有效
内容 SEO 检查清单
- 标题标签优化（50-60 字符）
- Meta 描述（150-160 字符）
- H1-H6 层级正确
- 内部链接结构合理
- 图像 alt 文本齐全
GEO 检查清单
- 包含 FAQ 环节
- 作者资质可见
- 统计数据注明来源
- 定义清晰明确
- 引用专家原话并注明归属
- 标注“最后更新”时间戳
容易被引用的内容
| 元素 | 为什么 AI 会引用它 |
|---|---|
| 原始统计数据 | 独特数据源 |
| 专家名言 | 权威性 |
| 清晰定义 | 易于提取信息 |
| 逐步指南 | 实用价值 |
| 对比表格 | 结构化程度高 |
适用场景
- SEO 审计
- Core Web Vitals 优化
- E-E-A-T 改进
- AI 搜索可见性
- Schema 标记实现
- 内容优化
- GEO 策略
Remember（记住）： 最好的 SEO 是能清晰、权威地回答问题的优质内容。
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.
- 5d ago First seen · 112 lines · 61 tokens per session scan A 49e3d3c2c36e
seo-specialist is an agent published in the GitHub repository MisonL/Ling (8 stars, last pushed 5mo ago), licensed MIT. It adds 61 tokens to every session and 873 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 2026-08-31.
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