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/jondoescoding/jondoescoding-coding-rulesWrote 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/rules/jondoescoding/jondoescoding-coding-rules/seo-google-rules)<a href="https://agentmods.dev/rules/jondoescoding/jondoescoding-coding-rules/seo-google-rules"><img src="https://agentmods.dev/badge/rules/jondoescoding/jondoescoding-coding-rules/seo-google-rules/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/rules/jondoescoding/jondoescoding-coding-rules/seo-google-rules"><img src="https://agentmods.dev/badge/rules/jondoescoding/jondoescoding-coding-rules/seo-google-rules.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 | $0.00017 | $0.05162 |
| Opus 5.5 | $0.00007 | $0.02065 |
| Sonnet 5.5 | $0.00003 | $0.01032 |
| Haiku 4.5 | $0.00002 | $0.00516 |
Grade A, and why
seo-google-rules 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 1mo 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 — 770 lines — stays where its author put it; the contents beside it link to each section on GitHub.
13. Monitoring & Testing
SEO Checklist for Every Page
- Unique title tag (50-60 characters)
- Meta description (150-160 characters)
- One H1 tag with target keyword
- Proper heading hierarchy (H1 → H2 → H3)
- Alt text for all images
- [ ]# SEO-Optimized Cursor Rules for Next.js Business Website
Project Context
You are developing a SEO-optimized business website using Next.js 15+, React 19, Tailwind CSS, and MongoDB. Follow Google's SEO Starter Guide principles strictly. Prioritize technical SEO and mobile-first development. This project uses the App Router architecture.
Core SEO Principles
1. Technical SEO Foundation
- Always use semantic HTML5 elements (
<header>,<nav>,<main>,<article>,<section>,<aside>,<footer>) - Implement proper heading hierarchy - Only one
<h1>per page, followed by<h2>,<h3>in logical order - Generate XML sitemaps automatically using
next-sitemappackage - Create robots.txt with proper directives
- Implement canonical URLs to prevent duplicate content issues
- Use Server-Side Rendering (SSR) or Static Site Generation (SSG) for all public pages
2. Next.js SEO Implementation
Metadata API Usage (Next.js 15)
// Always use Next.js 15 Metadata API for SEO
import type { Metadata } from 'next';
export const metadata: Metadata = {
title: 'Page Title - Business Name',
description: 'Compelling description under 160 characters that includes target keywords naturally',
keywords: ['relevant', 'keywords', 'for', 'SEO'],
authors: [{ name: 'Author Name' }],
creator: 'Business Name',
publisher: 'Business Name',
formatDetection: {
email: false,
address: false,
telephone: false,
},
metadataBase: new URL('https://yourdomain.com'),
openGraph: {
title: 'Page Title - Business Name',
description: 'Compelling description for social sharing',
url: 'https://yourdomain.com/current-page',
siteName: 'Business Name',
images: [
{
url: '/og-image.jpg',
width: 1200,
height: 630,
alt: 'Descriptive alt text for OG image',
}
],
locale: 'en_US',
type: 'website',
},
twitter: {
card: 'summary_large_image',
title: 'Page Title - Business Name',
description: 'Compelling description for Twitter',
creator: '@yourtwitterhandle',
images: ['/twitter-image.jpg'],
},
alternates: {
canonical: 'https://yourdomain.com/current-page',
languages: {
'en-US': 'https://yourdomain.com/en-US',
'es-ES': 'https://yourdomain.com/es-ES',
},
},
robots: {
index: true,
follow: true,
nocache: true,
googleBot: {
index: true,
follow: true,
'max-video-preview': -1,
'max-image-preview': 'large',
'max-snippet': -1,
},
},
verification: {
google: 'google-site-verification-code',
yandex: 'yandex-verification-code',
yahoo: 'yahoo-verification-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.
- 1mo ago First seen · 770 lines · 17 tokens per session scan A de99f68004b2
seo-google-rules is a cursor rule published in the GitHub repository jondoescoding/jondoescoding-coding-rules (2 stars, last pushed 2mo ago), licensed MIT. It adds 17 tokens to every session and 5,162 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other cursor rules, from other repositories
app-router-patterns
Next.js 14+ App Router patterns — Server Components, Client Components, Route Handlers, Server Actions, and metadata API.
monitoring
Monitoring, observability, and alerting rules.
data-fetching
Data fetching patterns with TanStack Query, Server Components, and Supabase.
token-efficiency
Token optimization rules to reduce AI costs by 30%+.
performance
Frontend performance optimization rules. Apply when optimizing UI or bundle.
new_features
Guidelines for integrating new features into the Task Master CLI.