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- SEO-to-Code Pipeline for Next.js
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SEO-to-Code Pipeline for Next.js
Turn target keywords into production-ready, search-optimized Next.js App Router components with JSON-LD schema & Cursor rules.
$5
SEO-to-Code Pipeline for Next.js
Example session with this skill installed
Create a search-optimized landing page for an AI code review tool named "CodeGuard".
- Primary Keyword: "AI code reviewer for Next.js"
- Secondary Keywords: "automated pull request analysis", "TypeScript code quality tool", "Cursor IDE rules"
- Page Type: SoftwareApplication
- Page Goal: Product landing page with feature breakdown, pricing snippet, and FAQ section.
- Read your context and instructions
- Compiled the seo-to-code pipeline
// app/code-reviewer/page.tsx
import { Metadata } from 'next';
export const metadata: Metadata = {
title: 'CodeGuard - AI Code Reviewer for Next.js & TypeScript',
description: 'Automate pull request analysis and enforce Cursor IDE rules with CodeGuard, the intelligent AI code review tool.',
openGraph: {
title: 'CodeGuard - AI Code Reviewer for Next.js',
description: 'Automate pull request analysis with deep TypeScript static inspection.',
type: 'website',
},
};
export default function CodeReviewerPage() {
const jsonLd = {
'@context': 'https://schema.org',
'@type': 'SoftwareApplication',
'name': 'CodeGuard',
'applicationCategory': 'DeveloperApplication',
'operatingSystem': 'Web, Cursor IDE',
'offers': {
'@type': 'Offer',
'price': '0',
'priceCurrency': 'USD'
}
};
return (
<main className="max-w-7xl mx-auto px-4 py-12">
<script
type="application/ld+json"
dangerouslySetInnerHTML={{ __html: JSON.stringify(jsonLd) }}
/>
<header className="mb-12 text-center">
<h1 className="text-4xl font-bold tracking-tight">
AI Code Reviewer for Next.js Applications
</h1>
<p className="mt-4 text-xl text-gray-600">
Automate pull request analysis and maintain code quality across engineering teams.
</p>
</header>
<section className="my-16">
<h2 className="text-2xl font-semibold mb-6">Automated Pull Request Analysis</h2>
<article className="prose lg:prose-xl">
<p>
CodeGuard integrates with your GitHub repository to deliver instant static analysis and automated TypeScript checks...
</p>
</article>
</section>
</main>
);
}
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
Automate your Technical SEO workflow directly inside your AI workspace. The SEO-to-Code Pipeline takes target keywords, entity specifications, and content goals, converting them into structured, production-ready Next.js React code.
Core Capabilities
- Keyword & Entity Mapping: Automatically generates strict heading trees (
<h1>-><h2>-><h3>) without skipped levels, mapping LSI keywords naturally into component sections. - Schema.org Integration: Generates valid JSON-LD payloads for
Article,SoftwareApplication,Product, orFAQPageschemas alongside OpenGraph and Twitter card parameters. - App Router Native: Outputs clean TypeScript (
page.tsx) featuring nativegenerateMetadataimplementation, strict semantic HTML tags (<article>,<section>,<header>), and zero generic<div>bloat. - Cursor Rules Generation: Automatically writes a
.cursor/rules/seo.mdcfile to lock in SEO standards across your entire codebase.
Generated Deliverables
page.tsx: Fully typed, semantic Next.js App Router page.schema.json: Validated Schema.org structured data script..cursor/rules/seo.mdc: Machine-readable IDE rules to enforce standards in future edits.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
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- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
Skills folder by agent
Click the path to copy it. Create the folder if it does not exist yet.
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