geo-seo-claude is a Claude Code skill for improving how websites appear in AI-powered search while retaining traditional search-engine optimization. It is used by marketers and website practitioners for analysis such as citation scoring, crawler review, authority assessment, structured data, and platform-specific recommendations. The catalogue entries are skills and agents that carry out this optimization workflow.
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 zubair-trabzada/geo-seo-claude --skill geo-auditgit clone --depth 1 https://github.com/zubair-trabzada/geo-seo-claudeWrote 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/zubair-trabzada/geo-seo-claude/geo-audit)<a href="https://agentmods.dev/skills/zubair-trabzada/geo-seo-claude/geo-audit"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/geo-seo-claude/geo-audit/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/zubair-trabzada/geo-seo-claude/geo-audit"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/geo-seo-claude/geo-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- 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 | $0.00060 | $0.02893 |
| Opus 5 | $0.00030 | $0.01447 |
| Sonnet 5 | $0.00012 | $0.00579 |
| Haiku 4.5 | $0.00006 | $0.00289 |
Grade A, and why
geo-audit 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 — 338 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEO Audit Orchestration Skill
Purpose
This skill performs a comprehensive Generative Engine Optimization (GEO) audit of any website. GEO is the practice of optimizing web content so that AI systems (ChatGPT, Claude, Perplexity, Gemini, etc.) can discover, understand, cite, and recommend it. This audit measures how well a site performs across all GEO dimensions and produces an actionable improvement plan.
Key Insight
Traditional SEO optimizes for search engine rankings. GEO optimizes for AI citation and recommendation. Sites that score high on GEO metrics see 30-115% more visibility in AI-generated responses (Georgia Tech / Princeton / IIT Delhi 2024 study). The two disciplines overlap but have distinct requirements.
Audit Workflow
Phase 1: Discovery and Reconnaissance
Step 1: Fetch Homepage and Detect Business Type
-
Use WebFetch to retrieve the homepage at the provided URL.
-
Extract the following signals:
- Page title, meta description, H1 heading
- Navigation menu items (reveals site structure)
- Footer content (reveals business info, location, legal pages)
- Schema.org markup on homepage (Organization, LocalBusiness, etc.)
- Pricing page link (SaaS indicator)
- Product listing patterns (E-commerce indicator)
- Blog/resource section (Publisher indicator)
- Service pages (Agency indicator)
- Address/phone/Google Maps embed (Local business indicator)
-
Classify the business type using these patterns:
| Business Type | Detection Signals |
|---|---|
| SaaS | Pricing page, "Sign up" / "Free trial" CTAs, app.domain.com subdomain, feature comparison tables, integration pages |
| Local Business | Physical address on homepage, Google Maps embed, "Near me" content, LocalBusiness schema, service area pages |
| E-commerce | Product listings, shopping cart, product schema, category pages, price displays, "Add to cart" buttons |
| Publisher | Blog-heavy navigation, article schema, author pages, date-based archives, RSS feeds, high content volume |
| Agency/Services | Case studies, portfolio, "Our Work" section, team page, client logos, service descriptions |
| Hybrid | Combination of above signals -- classify by dominant pattern |
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 · 338 lines · 60 tokens per session scan A 7cc197e07bac
geo-audit is a skill published in the GitHub repository zubair-trabzada/geo-seo-claude (10,540 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 2,893 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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