Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add ZachArticulateV/designer-pro-and-seo/plugin install designer-pro-and-seoWrote 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/zacharticulatev/designer-pro-and-seo/seo-geo)<a href="https://agentmods.dev/skills/zacharticulatev/designer-pro-and-seo/seo-geo"><img src="https://agentmods.dev/badge/skills/zacharticulatev/designer-pro-and-seo/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/zacharticulatev/designer-pro-and-seo/seo-geo"><img src="https://agentmods.dev/badge/skills/zacharticulatev/designer-pro-and-seo/seo-geo.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 | $0.00132 | $0.02020 |
| Opus 5 | $0.00066 | $0.01010 |
| Sonnet 5 | $0.00026 | $0.00404 |
| Haiku 4.5 | $0.00013 | $0.00202 |
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 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
seo-geo
Family: seo Status: Stable
Purpose
Optimize for AI-powered search, where the win condition is being cited inline by the AI answer, not ranking #1. That requires different content patterns: passages that make specific, verifiable, standalone claims; discoverability via llms.txt and AI-crawler access; and structured data (a top-5 GEO citation factor in the GEO study, Aggarwal et al., KDD 2024).
Triggers
- "ai overviews" / "SGE" / "GEO" / "generative engine optimization"
- "AI search" / "LLM optimization" / "AI visibility optimization" / "ai citations"
- "perplexity" / "chatgpt search" / "bing copilot" / "llms.txt"
Inputs
- A page URL and/or its content (file)
- An optional
robots.txt(file or live) for the AI-crawler-policy verdict - Target platforms (AI Overviews / Perplexity / ChatGPT / all)
Steps
- Run the GEO checker (with the weighted scorecard):
It scores each passage's citability (sourced + self-contained + answer-first → 0-100), counts structured-data blocks, reads the robots AI-crawler policy, and rolls those signals into a weighted 0-100 GEO score with a per-category breakdown (re-normalized over whatever signals are present, so a content-only offline run still scores). Addpython3 "${CLAUDE_PLUGIN_ROOT}/scripts/seo/geo_check.py" --content page.html \ --robots robots.txt --scorecard --human--url https://site.comto also check/llms.txtand fetch live robots. Seereferences/geo-scorecard.mdfor the weight rationale, the passage rubric, and the crawler-verdict semantics. - Passage citability — rewrite the weak passages it lists so each leads with one specific, sourced claim (number/date/named source) that survives extraction.
- llms.txt — if absent, create a Markdown
/llms.txtsummarizing the site's key pages for LLMs. - AI-crawler access — read the checker's crawler-policy verdict
(
citable-training-blockedis best practice;retrieval-blockedis the anti-pattern). Ensure retrieval bots (OAI-SearchBot, PerplexityBot, Claude-SearchBot) are allowed so the site stays citable, even if training crawlers are blocked. - Structured data — add Article/Organization/Breadcrumb schema via
seo-schema. - Brand mentions — recommend earning mentions on sources LLMs trust; if the DataForSEO extension is present, pull LLM-mention tracking, else note it.
- Render platform-specific action items (AI Overviews favors structured, sourced answers; Perplexity favors fresh, citation-dense pages).
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 · 127 lines · 132 tokens per session scan A 3e613313b2b3
seo-geo is a skill published in the GitHub repository ZachArticulateV/designer-pro-and-seo (8 stars, last pushed 2mo ago), licensed MIT. It adds 132 tokens to every session and 2,020 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 2026-08-31.
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