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 Thibaultbm/claude-seo-geo --skill geo-trackinggit clone --depth 1 https://github.com/Thibaultbm/claude-seo-geoWrote 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/thibaultbm/claude-seo-geo/geo-tracking)<a href="https://agentmods.dev/skills/thibaultbm/claude-seo-geo/geo-tracking"><img src="https://agentmods.dev/badge/skills/thibaultbm/claude-seo-geo/geo-tracking/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/thibaultbm/claude-seo-geo/geo-tracking"><img src="https://agentmods.dev/badge/skills/thibaultbm/claude-seo-geo/geo-tracking.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 | $0.00121 | $0.04954 |
| Opus 5 | $0.00060 | $0.02477 |
| Sonnet 5 | $0.00024 | $0.00991 |
| Haiku 4.5 | $0.00012 | $0.00495 |
Grade A, and why
geo-tracking 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 11d 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 — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEO Tracking: Measuring AI Visibility
AI visibility is measurable today, for free, at three layers of the funnel. Each layer answers a different question:
| Layer | Data source | Question it answers | Lag |
|---|---|---|---|
| Traffic | GA4 | How many visits and conversions do AI assistants send? | Trailing (after the click) |
| Answers | Prompt panel | What do AI engines say about the brand when buyers ask? | Current state |
| Retrieval | Server logs | Are AI systems reading the pages right now? | Leading (before citations appear) |
Run all three. GA4 alone undercounts structurally, panels alone miss revenue proof, logs alone say nothing about what answers contain. The combination is the measurement system; paid platforms are an optional layer on top, never the starting point.
This skill is the canonical measurement reference in this repo. Build the prompt panel with seo-keyword-research; act on the gaps with geo-visibility.
Company knowledge first (Obsidian)
If the working environment contains an Obsidian vault or any local knowledge base (a folder of .md notes, often with a .obsidian directory), read the relevant notes before acting: brand and product facts, target keywords, competitors, and the SEO action log of what was already tried. Ground every recommendation in that context instead of asking the user for facts the vault already holds. At the end of the session, append the actions taken to the vault's SEO action log so the next session starts informed. Vault structure, read-first and write-back protocols: the obsidian-brain skill.
When to use this skill
Use this skill when the user:
- Asks how much traffic comes from ChatGPT, Perplexity, Gemini, Claude, or Copilot.
- Wants AI traffic visible in GA4, Looker Studio, or a client report.
- Wants to track brand mentions, citations, or share of voice in AI answers (prompt tracking, AI rank tracking).
- Asks whether AI bots crawl the site, or what ChatGPT-User hits in the logs mean.
- Needs a monthly GEO report, a baseline before a GEO project, or proof of GEO results for a client.
- Asks whether to buy an AI visibility tool (Profound, Otterly, Brand Radar, Semrush AI tools).
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.
- 11d ago First seen · 301 lines · 121 tokens per session scan A 2feb4df162fb
geo-tracking is a skill published in the GitHub repository Thibaultbm/claude-seo-geo (16 stars, last pushed today), licensed MIT. It adds 121 tokens to every session and 4,954 once invoked, about $0.0006 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.
Other skills, from other repositories
geo-audit
Full website GEO+SEO audit with parallel subagent delegation. Orchestrates a comprehensive Generative Engine Optimization audit across AI citability, platform analysis, technical infrastructure, content quality, and schema markup. Produces a composite GEO Score (0-100) with prioritized action plan.
geo
GEO-first SEO analysis tool. Optimizes websites for AI-powered search engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) while maintaining traditional SEO foundations. Performs full GEO audits, citability scoring, AI crawler analysis, llms.txt generation, brand mention scanning, platform-specific…
geo-brand-mentions
Brand mention and authority scanner for AI visibility. Analyzes brand presence across platforms that AI models rely on for entity recognition and citation decisions. Produces a Brand Authority Score (0-100) with platform-specific recommendations.
geo-llmstxt
Analyzes and generates llms.txt files -- the emerging standard for helping AI systems understand website structure and content. Can validate existing llms.txt files or generate new ones from scratch by crawling the site.
agent-readiness-scan
Use when a client audit, GEO/AI-visibility snapshot, or remediation re-scan needs the Cloudflare agent-readiness score from isitagentready.com — e.g. Theo client audits, "is the site agent-ready", markdown negotiation / MCP / llms.txt / Content-Signal checks, or tracking score deltas after Tier 0/1 fixes.
found-by-ai
Measure whether AI engines actually recommend a business when buyers ask. Runs the free live scan at areyoufoundbyai.com (no auth, 60s), reads the verdict and the rivals AI names instead, hands back the fix plan, and wires monitored sites into a fix-and-re-measure loop over MCP.