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 yaojingang/GEOHub --skill geo-discovergit clone --depth 1 https://github.com/yaojingang/GEOHubWrote 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/yaojingang/geohub/geo-discover)<a href="https://agentmods.dev/skills/yaojingang/geohub/geo-discover"><img src="https://agentmods.dev/badge/skills/yaojingang/geohub/geo-discover/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/yaojingang/geohub/geo-discover"><img src="https://agentmods.dev/badge/skills/yaojingang/geohub/geo-discover.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 | $0.00057 | $0.00353 |
| Opus 5 | $0.00028 | $0.00177 |
| Sonnet 5 | $0.00011 | $0.00071 |
| Haiku 4.5 | $0.00006 | $0.00035 |
Grade A, and why
geo-discover 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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
12 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.
- agents/interface.yaml 1.0 KB
- evals/output/cases.jsonl 2.1 KB
- evals/semantic_config.json 479 B
- evals/trigger_cases.json 603 B
- manifest.json 1.1 KB
- references/discovery-method-v2.md 1.5 KB
- references/discovery-method.md 1.8 KB
- references/input-example.json 277 B
- reports/output_quality_scorecard.md 427 B
- reports/skill-ir.json 2.7 KB
- reports/trust-report.md 348 B
- scripts/run_discover.py 445 B runs code
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 · 23 lines · 57 tokens per session scan A e2e19069513f
geo-discover is a skill published in the GitHub repository yaojingang/GEOHub (156 stars, last pushed 10d ago), licensed AGPL-3.0. It adds 57 tokens to every session and 353 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.
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-visibility
Get cited and recommended by AI engines (ChatGPT, AI Overviews and AI Mode, Perplexity, Claude, Gemini). Input: a page or piece of content. Output: passage-level citability fixes (answer-first H2 blocks, self-contained chunks, definitions, sourced stats, comparison tables), a 5-pillar GEO score (0-100), an AI-crawler…
seo-content-blog
Write blog articles that rank on Google and get cited by AI engines (ChatGPT, Perplexity, AI Overviews). Input: a keyword, topic, or existing draft. Output: a publish-ready article, outline, or brief built on a 12-element answer-first skeleton (question H2s, expert quotes, stats, FAQ, internal links, SERP-benchmarked…
seo-content-collection-page
Optimize e-commerce collection, category, and product listing pages (PLPs) for Google and AI assistants. Input: a collection or category page (Shopify, WooCommerce, Magento, BigCommerce, PrestaShop, or custom). Output: a bottom-of-page SEO text block, faceted-navigation and filter URL control, pagination canonicals…