Borrowing it
Nothing to install: this file belongs to jacob-dietle/context-os. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jacob-dietle/context-os/main/.claude/skills/seo-aeo-expert-perspectives/SKILL.mdgit clone --depth 1 https://github.com/jacob-dietle/context-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/jacob-dietle/context-os/seo-aeo-expert-perspectives)<a href="https://agentmods.dev/skills/jacob-dietle/context-os/seo-aeo-expert-perspectives"><img src="https://agentmods.dev/badge/skills/jacob-dietle/context-os/seo-aeo-expert-perspectives/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/jacob-dietle/context-os/seo-aeo-expert-perspectives"><img src="https://agentmods.dev/badge/skills/jacob-dietle/context-os/seo-aeo-expert-perspectives.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 | $0.00108 | $0.04400 |
| Opus 5 | $0.00054 | $0.02200 |
| Sonnet 5 | $0.00022 | $0.00880 |
| Haiku 4.5 | $0.00011 | $0.00440 |
Grade A, and why
SEO & AEO Expert Perspectives 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 12d 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 — 448 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEO & AEO Expert Perspectives
Systematic methodology for applying expert mental models to search visibility decisions, ensuring implementation goes beyond checklists to expert-grade optimization.
Meta-Principle: "Checklists produce 6/10 SEO. Expert lenses produce 9/10. The difference is asking the right diagnostic questions before writing a single meta tag."
When to Use This Skill
Apply this skill when:
- Building or optimizing pages for search engine visibility
- Deciding what structured data (JSON-LD, schema.org) to add
- Evaluating whether programmatic pages have search value
- Making AEO decisions (AI Overview, featured snippet optimization)
- Reviewing title tags, meta descriptions, on-page signals
- Adding SEO infrastructure (sitemaps, robots.txt, canonical URLs)
- Generating content with AI for search purposes
- Designing internal linking architecture
Do NOT use for:
- Paid search / SEM campaigns
- Social media optimization (unless OG tags specifically)
- Email marketing
- General content writing without search intent
Core Principle: Expert Diagnosis Before Implementation
Most SEO work fails because it follows checklists instead of asking diagnostic questions.
The Pattern:
Checklist approach: "Add JSON-LD Article schema to every page"
Expert approach: "Which pages have search demand? What structured data
feeds the RAG pipeline? Does the title survive Google's
rewrite algorithm?"
Always diagnose before implementing.
The Expert Perspectives Framework
Apply these expert lenses IN ORDER. Each perspective asks different questions.
Perspective 1: Eli Schwartz (Product-Led SEO)
Background: Author of Product-Led SEO. Growth consultant for WordPress, Coinbase, Shutterstock, Quora, Zendesk. Coined the Product-Led SEO methodology.
Core belief: "If you aren't helping a human solve a problem, you're just making digital noise."
Questions to ask:
- Does search demand actually exist for this page?
- What problem does a searcher solve by landing here?
- Is this programmatic page generation from real inventory, or content generation from nothing?
- Would a human find this page useful if they landed on it from search?
What ships with it
1 file 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.
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.
- 12d ago First seen · 448 lines · 108 tokens per session scan A 2d4ff3ffdfd0
SEO & AEO Expert Perspectives is a skill published in the GitHub repository jacob-dietle/context-os (108 stars, last pushed 29d ago), licensed MIT. It adds 108 tokens to every session and 4,400 once invoked, about $0.0005 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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