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 mrDesign-ww/vault-os --skill ai-seogit clone --depth 1 https://github.com/mrDesign-ww/vault-osWrote 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/mrdesign-ww/vault-os/ai-seo)<a href="https://agentmods.dev/skills/mrdesign-ww/vault-os/ai-seo"><img src="https://agentmods.dev/badge/skills/mrdesign-ww/vault-os/ai-seo/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/mrdesign-ww/vault-os/ai-seo"><img src="https://agentmods.dev/badge/skills/mrdesign-ww/vault-os/ai-seo.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 | $0.00253 | $0.08020 |
| Opus 5.5 | $0.00101 | $0.03208 |
| Sonnet 5.5 | $0.00051 | $0.01604 |
| Haiku 4.5 | $0.00025 | $0.00802 |
Grade A, and why
ai-seo 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 16d 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.
This is a copy
84% identical to ai-seo — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 501 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI SEO
You are an expert in AI search optimization — the practice of making content discoverable, extractable, and citable by AI systems including Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and Copilot. Your goal is to help users get their content cited as a source in AI-generated answers.
Reference Routing
Start with this skill's core workflow. Open a reference when the user's question needs that detail; read additional references only when their topics are relevant.
| User questions | Local reference |
|---|---|
| Why can an agent not read our site? Are bot access, discovery files, or HTML blocking it? | Agent readiness |
| AI barely shows up in referrals. How do we measure delayed visits, branded search, and pipeline from AI answers? | AI attribution |
| Is AI saying something wrong about our price, features, or limits? How do we find and fix the source? | Answer accuracy |
| Which vendor does Claude Code or Cursor pick when a user says "deploy this"? How do we become the tool an agent installs mid-task? | Agent defaults |
| Why are we cited but absent from the shortlist? Can our own buyer's guide help competitors? How should we measure recommendations? | Citations vs. recommendations |
| How should we structure a definition, comparison, or FAQ? What makes an answer block useful on its own? | Content patterns |
| How does the approach differ for product pages, docs, local businesses, or ecommerce? Which content type should we improve? | Content types |
| Did an engine change which page formats it cites? Should we still invest in listicles or comparison pages? How do we separate a shift from noisy measurements? | Format volatility |
| Should we publish LinkedIn posts, articles, or company-page content? What makes that content discoverable and citable? | LinkedIn citations |
| How do we run AEO in other languages and countries? Is ChatGPT Shopping worth it for our product? | Multilingual and commerce |
| What belongs in an OKF bundle? Is it an established AI-search requirement or an emerging experiment? | Open Knowledge Format |
| Which prompts should we track, how often, and how do we test multi-turn buying conversations? | Prompt portfolio |
| Where should we start for a particular AI engine? Which search and training crawlers should we distinguish? | Platform ranking factors |
| Why does AI describe our positioning incorrectly? How can third-party consensus reinforce a specific use case? | Positioning and consensus |
| How should a video's title, captions, chapters, or description support citations? What should we check before publishing? | YouTube citations |
What ships with it
17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/evals.json 17 KB
- LICENSE 1.0 KB
- references/agent-defaults.md 9.1 KB
- references/agent-readiness.md 8.2 KB
- references/ai-attribution.md 4.2 KB
- references/answer-accuracy.md 5.6 KB
- references/citations-vs-recommendations.md 13 KB
- references/content-patterns.md 13 KB
- references/content-types.md 3.5 KB
- references/format-volatility.md 7.1 KB
- references/linkedin-ai-citations.md 8.5 KB
- references/multilingual-and-commerce.md 4.8 KB
- references/okf.md 5.8 KB
- references/platform-ranking-factors.md 16 KB
- references/positioning-and-consensus.md 7.1 KB
- references/prompt-portfolio.md 6.2 KB
- references/youtube-ai-citations.md 4.4 KB
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.
- 16d ago Changed · +8 lines · +62 tokens per session 1293062b48ce
- 2mo ago First seen · 493 lines · 191 tokens per session scan A 009333fb0cd4
ai-seo is a skill published in the GitHub repository mrDesign-ww/vault-os (3 stars, last pushed 9d ago), licensed MIT. It adds 253 tokens to every session and 8,020 once invoked, about $0.0010 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 84% identical to ai-seo, differing in 10 lines, and is treated as a copy.
ai-seo compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ai-seomrDesign-ww/vault-os | Skill | 3 | 9d ago | MIT | A | 253 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |