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 EliasOulkadi/shokunin --skill seo-geogit clone --depth 1 https://github.com/EliasOulkadi/shokuninWrote 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/eliasoulkadi/shokunin/seo-geo)<a href="https://agentmods.dev/skills/eliasoulkadi/shokunin/seo-geo"><img src="https://agentmods.dev/badge/skills/eliasoulkadi/shokunin/seo-geo/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/eliasoulkadi/shokunin/seo-geo"><img src="https://agentmods.dev/badge/skills/eliasoulkadi/shokunin/seo-geo.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 | $0.00148 | $0.02629 |
| Opus 5 | $0.00074 | $0.01314 |
| Sonnet 5 | $0.00030 | $0.00526 |
| Haiku 4.5 | $0.00015 | $0.00263 |
Grade A, and why
seo-geo 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 13d 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 — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEO & GEO Architect
Optimize for traditional search AND AI-powered engines. Based on Google Search Central, Moz, and GEO research (2025-2026).
Sub-Commands
| Command | Description |
|---|---|
audit-seo |
Run full SEO audit (titles, meta, schema, speed, mobile) |
audit-geo |
Run GEO audit (llms.txt, entity clarity, AI answer format) |
schema |
Generate JSON-LD structured data for any page type |
optimize |
Implement priority fixes ranked by impact |
llms |
Generate/update llms.txt for AI crawler discovery |
Workflow
Step 1: Run SEO audit
Check: title tags (< 60 chars, keyword first), meta descriptions (< 155 chars, value prop), H1 (one per page, keyword), img alt text, OG tags, canonical, robots.txt, sitemap.xml, Core Web Vitals.
Score: 90-100% good. 70-89% fix flagged. < 70% structural issues first.
Step 2: Run GEO audit
Check: llms.txt presence, ai-plugin.json, FAQ/HowTo schema, entity clarity, brand mention structure, answer format (direct answer in first 2 paragraphs).
Step 3: Prioritized fixes
| Fix | Impact | Effort |
|---|---|---|
| Fix crawl errors (GSC) | High | Low |
| Improve LCP < 2.5s | High | Medium |
| Add structured data (JSON-LD) | High | Medium |
| Create llms.txt | High | Low |
| Fix meta titles/descriptions | Medium | Low |
| Add hreflang (if multilingual) | Medium | Low |
| Improve internal linking | Medium | Medium |
Step 4: Structured data (must implement)
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Brand Name",
"description": "One sentence. What you do.",
"url": "https://example.com",
"logo": "https://example.com/logo.png",
"sameAs": ["https://twitter.com/handle", "https://github.com/handle"]
}
Also: Article, FAQPage, HowTo, Product, BreadcrumbList, LocalBusiness (if applicable).
Step 5: llms.txt
# Brand Name
> One-line description.
## Core pages
- https://example.com/: Home
- https://example.com/about: About
## Docs
- https://docs.example.com/api: API reference
## Blog
- https://example.com/blog/post: Title
What ships with it
5 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.
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.
- 13d ago First seen · 246 lines · 148 tokens per session scan A 2cd9d09e988f
seo-geo is a skill published in the GitHub repository EliasOulkadi/shokunin (113 stars, last pushed 1mo ago), licensed MIT. It adds 148 tokens to every session and 2,629 once invoked, about $0.0007 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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refresh
Use when an existing contextualizer's references may have drifted from current upstream state — typically weekly, or whenever a few days of upstream changes have accumulated — to bring them back into agreement.
apply
Use when a staged proposal has been reviewed and signed off — REVIEW.md Step 3 ticked reviewed or provisional — and is ready to promote into the live contextualizer.
config-set
Use when changing an engine-wide config value — currently diff.tool, the command /skill-engine:review prints for inspecting a proposed-vs-live diff.