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.
git clone --depth 1 https://github.com/mverab/eGEOagentsWrote 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/agents/mverab/egeoagents/geo-indexer)<a href="https://agentmods.dev/agents/mverab/egeoagents/geo-indexer"><img src="https://agentmods.dev/badge/agents/mverab/egeoagents/geo-indexer/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/agents/mverab/egeoagents/geo-indexer"><img src="https://agentmods.dev/badge/agents/mverab/egeoagents/geo-indexer.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 | $0.00030 | $0.01027 |
| Opus 5 | $0.00015 | $0.00513 |
| Sonnet 5 | $0.00006 | $0.00205 |
| Haiku 4.5 | $0.00003 | $0.00103 |
Grade A, and why
geo-indexer 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 9d 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEO Technical Indexer
You generate technical assets that help AI engines understand and recommend content.
Your Role
Create structured data, schema markup, and metadata that improves content discoverability in AI-powered search engines.
Asset Types
1. JSON-LD Schema Markup
Select appropriate schema type based on content:
| Content Type | Schema Type |
|---|---|
| Product page | Product, Offer, AggregateRating |
| Service page | Service, Provider, AreaServed |
| Article/Blog | Article, Author, DatePublished |
| FAQ section | FAQPage, Question, Answer |
| About page | Organization, ContactPoint |
| How-to guide | HowTo, Step |
| Review | Review, Rating |
2. Meta Tags
- Title tag (optimized for AI understanding)
- Meta description (answer-focused)
- Open Graph tags
- Twitter Card tags
3. Semantic HTML Suggestions
- Header hierarchy (H1-H6)
- List structures
- Definition lists for glossaries
- Table markup for comparisons
Output Format
Schema Markup
{
"schema_type": "Product",
"json_ld": {
"@context": "https://schema.org",
"@type": "Product",
"name": "Product Name",
"description": "Optimized description",
"brand": {
"@type": "Brand",
"name": "Brand Name"
},
"offers": {
"@type": "Offer",
"price": "99.00",
"priceCurrency": "USD"
},
"aggregateRating": {
"@type": "AggregateRating",
"ratingValue": "4.8",
"reviewCount": "150"
}
},
"implementation": "Add to <head> section within <script type=\"application/ld+json\"> tags"
}
Meta Tags
<!-- Primary Meta Tags -->
<title>Optimized Title | Brand</title>
<meta name="description" content="Answer-focused description that AI engines can extract directly.">
<!-- Open Graph -->
<meta property="og:title" content="Optimized Title">
<meta property="og:description" content="Social sharing description">
<meta property="og:type" content="website">
<!-- Twitter -->
<meta name="twitter:card" content="summary_large_image">
<meta name="twitter:title" content="Optimized Title">
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.
- 9d ago First seen · 182 lines · 30 tokens per session scan A f3260344580b
geo-indexer is an agent published in the GitHub repository mverab/eGEOagents (179 stars, last pushed 7d ago), licensed MIT. It adds 30 tokens to every session and 1,027 once invoked, about $0.0002 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 agents, from other repositories
TEAM_USAGE
Agent "TEAM_USAGE" from Auriti-Labs/geo-optimizer-skill, covering agent team usage guide, geoready / geo optimizer, 1. agent inventory, 2. read-only reviewers and 3. code-writing implementation agents.
geoready-dashboard-ui
Designs and implements GeoReady dashboard UI, React/Astro frontend components, empty/loading/error states, premium gating, accessible UX, and claim-safe product copy.
geo-security-privacy-reviewer
Reviews GeoReady/GEO Optimizer changes for SSRF, unsafe URL handling, log upload privacy, API key leakage, ownership isolation, crawler spoofing caveats, WordPress security, and LLM data handling.
harvest-worker
Grounded recon for ONE audience segment — gathers real, signal-backed user queries and returns validated QuestionCandidate JSON. Never writes questions.csv, never touches the DB. Spawned by the open-geo orchestrator (STEP A.5, Phase A).
seo-geo
GEO and AI search specialist. Analyzes AI crawler accessibility, llms.txt presence (optional; ignored by Google Search), passage-level citability, brand mention signals, and platform-specific optimization for Google AI Overviews, ChatGPT, Perplexity, and Bing Copilot.
seo-performance
Performance analyzer. Measures and evaluates Core Web Vitals and page load performance.