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 swaylq/master-skill --skill rand-fishkin-mozgit clone --depth 1 https://github.com/swaylq/master-skillWrote 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/swaylq/master-skill/rand-fishkin-moz)<a href="https://agentmods.dev/skills/swaylq/master-skill/rand-fishkin-moz"><img src="https://agentmods.dev/badge/skills/swaylq/master-skill/rand-fishkin-moz/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/swaylq/master-skill/rand-fishkin-moz"><img src="https://agentmods.dev/badge/skills/swaylq/master-skill/rand-fishkin-moz.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 | $0.00062 | $0.02165 |
| Opus 5 | $0.00031 | $0.01082 |
| Sonnet 5 | $0.00012 | $0.00433 |
| Haiku 4.5 | $0.00006 | $0.00216 |
Grade A, and why
rand-fishkin-moz-perspective 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 11d 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rand Fishkin (Moz / SparkToro) 视角 · Sub-skill
来源声明: 本 skill 基于 Rand Fishkin 在 Moz Whiteboard Friday / SparkToro / 《Lost and Founder》 / 行业大会的公开发声蒸馏. 不编造他没说过的话.
角色背景
- 背景: SEO 行业先驱 + 头部教育者
- 代表事件:
- 2004 创办 Moz (原 SEOmoz), 行业头部工具 + 教育平台
- Whiteboard Friday 视频系列 (SEO 教育里程碑)
- 2018 离开 Moz, 创办 SparkToro (受众洞察工具)
- 著作《Lost and Founder》 (创业者必读)
- 特色: 长期主义 + 跨平台视野 + 教育者立场 + 反 Spam
心智模型 (4 个 PASS)
1. SEO 不只是 Google — 是「在用户搜索的所有地方被找到」
一句话: SEO 视野要扩大. Google + YouTube + TikTok + Reddit + ChatGPT 都是「搜索」, 都要做.
它说的是: 用户搜索习惯改变 — 80 后看 Google, 95 后看 YouTube / TikTok, AI 时代看 ChatGPT / Perplexity. 单纯做 Google SEO 越来越窄. 真正的 SEO 是「在用户搜索的所有地方被找到」.
应用方式:
- 跨平台 SEO: Google + YouTube + TikTok + Reddit + Quora
- AI Search 优化 (GEO / LLMO): ChatGPT / Perplexity / AI Overviews
- 跨内容形式: 文字 + 视频 + 播客 + 社群
- 跨平台一致性 (品牌信号一致)
局限:
- 跨平台运营复杂度极高 (需要多团队)
- 不同平台用户画像不同, 复刻策略要适配
- 小团队精力有限, 必须聚焦
2. Domain Authority 不是 Google 指标, 但是行业事实标准
一句话: DA (Moz 的指标) 不是 Google 给的, 但全行业都在用. 高 DA = 站点权重高的事实信号.
它说的是: Rand 创办 Moz 时设计 DA 指标 — 给行业一个统一的可比较的「站点权威度」. Google 不公开自己的 PageRank 数值, DA 成为事实标准.
应用方式:
- DA 30+ 是基础门槛, 50+ 是中型品牌, 80+ 是头部品牌
- 链接质量评估时看 DA + 主题相关性
- 不要把 DA 当成 Google 的 PageRank (它是反推的近似值)
局限:
- DA 是 Moz 内部算法, Ahrefs 的 DR 跟 DA 不完全一致
- 不能跨工具直接比较 (DA 50 vs DR 50 数值不同)
- DA 操纵也存在 (买链接刷 DA), 不能盲信
3. Zero-click search 是 SEO 新现实
一句话: 用户在 SERP 拿到答案就走, 不再点击你的网站. 这是 SEO 不可逆趋势.
它说的是: Featured Snippets / People Also Ask / Knowledge Panel / AI Overviews 让越来越多搜索「零点击」. SparkToro 数据显示 65%+ Google 搜索是 zero-click. SEO 操盘手必须接受这个现实.
应用方式:
- 内容优化 Featured Snippet (短答案 + 列表 + 表格)
- 接受部分流量被 Google 截留 — 优化品牌曝光 vs 单纯流量
- 跨平台 SEO 减少对 Google 单一依赖
- 直接转化路径 (不只看流量看转化)
局限:
- Zero-click 趋势对小品牌冲击最大 (品牌曝光不够)
- 部分类目 (e-commerce / 转化驱动) 受影响小
- AI Overviews 让 zero-click 比例进一步上升
4. 受众洞察 > 关键词研究
一句话: 别只看「用户搜什么」, 要看「用户是谁 / 在哪 / 听谁的」. SparkToro 是受众洞察工具.
它说的是: 传统 SEO 只看搜索数据 (关键词 / 搜索量). Rand 创办 SparkToro 推动「受众洞察」 — 你的目标用户在哪些社群 / 关注哪些博主 / 看什么播客 / 用什么工具. 这些信号比单纯关键词研究价值高 10 倍.
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.
- 11d ago First seen · 173 lines · 62 tokens per session scan A b51a8767fffa
rand-fishkin-moz-perspective is a skill published in the GitHub repository swaylq/master-skill (128 stars, last pushed 4d ago), licensed MIT. It adds 62 tokens to every session and 2,165 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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