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    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIGitHub CopilotGitHub CopilotGemini CLIGemini CLI+17 more

    SEO-to-Code Pipeline for Next.js

    1

    Turn target keywords into production-ready, search-optimized Next.js App Router components with JSON-LD schema & Cursor rules.

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    See it in action

    You say

    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.

    Your agent does

    // 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 (

    What you get

    Generate production-ready Next.js pages with built-in metadata exportsAutomate Schema.org JSON-LD creation for rich search snippetsEnforce semantic HTML structures across your entire React codebaseTranslate SEO keyword strategies directly into technical component architecture

    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 (`` -> `

    ` -> `

    `) without skipped levels, mapping LSI keywords naturally into component sections. * **Schema.org Integration**: Generates valid JSON-LD payloads for `Article`, `SoftwareApplication`, `Product`, or `FAQPage` schemas alongside OpenGraph and Twitter card parameters. * **App Router Native**: Outputs clean TypeScript (`page.tsx`) featuring native `generateMetadata` implementation, strict semantic HTML tags (``, ``, ``), and zero generic `` bloat. * **Cursor Rules Generation**: Automatically writes a `.cursor/rules/seo.mdc` file to lock in SEO standards across your entire codebase. ### Generated Deliverables 1. `page.tsx`: Fully typed, semantic Next.js App Router page. 2. `schema.json`: Validated Schema.org structured data script. 3. `.cursor/rules/seo.mdc`: Machine-readable IDE rules to enforce standards in future edits.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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