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pseo-llm-visibility

Configure robots.txt and schema markup for LLM search engine visibility.

Updated Sep 16, 2025
Search Tags:#llm#content optimization#citation#seo#ai search#generative engine optimization
One-click install
npx skills add https://github.com/finan-eu/finan-website --skill pseo-llm-visibility-finan-eu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pseo-llm-visibility
Source: https://github.com/finan-eu/finan-website/tree/main/.agents/skills/pseo-llm-visibility
Command: npx skills add https://github.com/finan-eu/finan-website --skill pseo-llm-visibility-finan-eu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill optimizes web content to be discoverable, extractable, and citable by AI-powered search engines and LLMs, ensuring your content appears in AI-generated answers.

Core Features & Use Cases

  • AI Crawler Configuration: Manages robots.txt rules for AI bots like GPTBot and PerplexityBot.
  • Content Structuring: Guides the creation of "answer capsules" for optimal LLM extraction.
  • Entity Optimization: Enhances content with structured data and entity recognition for AI understanding.
  • Use Case: A programmatic SEO team wants to ensure their newly generated product pages are not only found by traditional search engines but also appear as direct answers in ChatGPT or Google AI Overviews.

Quick Start

Use the pseo-llm-visibility skill to configure AI crawler access in robots.txt.

Frequently Asked Questions about pseo-llm-visibility

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize my content for citation in AI-generated search answers?▼

AI search citation optimization requires configuring AI crawler access, structuring content into answer capsules for LLM extraction, and implementing schema markup to ensure your pages appear in generative engine results.

What is generative engine optimization and how does it differ from traditional SEO?▼

Generative engine optimization focuses on making content discoverable and extractable by LLM-powered search engines, using entity-based optimization and machine-readable formats rather than traditional keyword-based ranking strategies.

How do I configure robots.txt to allow GPTBot and PerplexityBot crawling?▼

Configuring robots.txt for AI crawlers involves setting explicit access rules for bots like GPTBot and PerplexityBot, ensuring your programmatic SEO pages are accessible for indexing by LLM-powered search engines.

Does structured data schema markup improve visibility in ChatGPT and Google AI Overviews?▼

Structured data schema markup improves AI search visibility by enhancing content with entity recognition, making it easier for LLMs to understand and extract your information for generated answers.

What is llms.txt and do I need it for AI search engine indexing?▼

llms.txt is a machine-readable file that guides LLM crawlers to your content. Implementing it alongside schema markup ensures your programmatic SEO pages meet multi-engine indexation requirements for AI search visibility.

Can I use entity-based content structuring for programmatic SEO pages at scale?▼

Entity-based content structuring scales for programmatic SEO by creating standardized answer capsules optimized for LLM extraction, ensuring newly generated product pages are citable across AI-powered search engines.

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