web discoverability skill

    1

    Evidence-based technical SEO and AI discoverability auditing for modern JavaScript and TypeScript web applications.

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    web discoverability skill

    Example session with this skill installed

    Run a recommended audit and implementation on my Next.js project to improve AI crawler discoverability and fix structured data gaps.

    • Read your context and instructions
    • Compiled the web discoverability
    • Generated the document

    I have completed the discovery audit and implementation for the target project. I first verified the skill freshness (v1.2.4-verified) and generated a project profile identifying a Next.js 14 frontend with internationalized routing.

    Discovery Audit and Implementation Report

    IDRequirementStatusEvidence
    SEO-012AI Crawler PolicyIMPLEMENTEDAdded robots.txt with specific GPTBot and CCBot directives.
    SEO-045JSON-LD BreadcrumbsFIXEDInjected structured data into app/products/[id]/page.tsx.
    SEO-089Canonical Link TagsIMPLEMENTEDConfigured next/head dynamic canonicals in root layout.
    SEO-102OpenGraph MetadataPROPOSEDReview required for social preview images in public/og/.
    SEO-033Sitemap XMLALREADY_CORRECTVerified existing sitemap.ts generation logic.

    Summary of Changes:

    • Modified robots.txt to include User-agent: GPTBot and User-agent: PerplexityBot with defined allow/disallow paths.
    • Updated layout.tsx to include dynamic metadata generation based on the current route.
    • Validated structured data against the Schema.org registry for product and breadcrumb types.

    Next steps

    1. Review the proposed OpenGraph image assets in the /public directory.
    2. Deploy changes to a staging environment and run node tools/cli.ts audit <url> to verify runtime served HTML.
    3. Update Google Search Console to trigger a re-crawl of the updated sitemap.xml.

    page.tsx

    PDF · document

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Modern web discovery requires more than just meta tags. This skill provides an evidence-based framework for auditing and implementing technical SEO, crawlability, and AI-readiness across modern JavaScript stacks. It moves beyond generic advice by using a canonical registry of requirements to verify project-specific compliance.

    What it does

    • Profile detection identifies project facts, frameworks, and discovery surfaces from source code.
    • Requirement selection filters a canonical registry of SEO and AI-readiness standards based on project profile.
    • Automated auditing scans for technical gaps in indexing, canonicals, metadata, and structured data.
    • Implementation engineering applies fixes for discovered issues across routing, templates, and configuration.
    • AI policy management configures crawler access and LLM/AEO readiness based on current search-surface matrices.

    How it works

    1. Freshness check verifies the local skill version against the upstream registry before execution.
    2. Project profiling runs a discovery scan to detect technology stacks, locales, and content types.
    3. Audit and selection maps the project against four complexity levels (Lite to Ultra) to identify gaps.
    4. Targeted implementation applies code changes to resolve high-priority discoverability requirements.

    Frameworks & tools

    Built for modern web ecosystems including Next.js, React, Remix, Astro, Vite, and Node.js. It integrates with TypeScript and JavaScript projects using a CLI tool to interface with a JSONL-based requirement registry.

    Why this beats prompting it yourself

    Generic prompts often hallucinate SEO rules or miss framework-specific implementation details for AI crawlers. This skill uses a versioned, evidence-based registry that maps specific requirements to file-level changes and verified search-surface guardrails.

    Use cases

    • Auditing a Next.js application for proper JSON-LD structured data and canonical hygiene.
    • Implementing AI crawler policies to control how LLMs ingest repository content.
    • Preparing an ecommerce site for multi-surface search visibility and Merchant Center readiness.
    • Validating multilingual and sub-domain indexing configurations across hybrid applications.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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    Requires

    Node.js
    Git

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