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llm-discoverability

Configure llms.txt, for-llms page, RSS feed, robots.txt, and Schema.org markup for AI discoverability.

Updated Aug 27, 2026
Search Tags:#llm#discoverability#llms.txt#robots.txt#schema.org#web-optimization
One-click install
npx skills add https://github.com/edhumbling/luminaoracles --skill llm-discoverability
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llm-discoverability
Source: https://github.com/edhumbling/luminaoracles/tree/main/.agent/skills/llm-discoverability
Command: npx skills add https://github.com/edhumbling/luminaoracles --skill llm-discoverability

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides proven techniques to help AI assistants discover, understand, and cite your website content, reducing misinterpretation and outdated results.

Core Features & Use Cases

  • llms.txt file: A machine-readable site context at /public/llms.txt following the llmstxt.org specification.
  • /for-llms page: A human-readable webpage at /app/for-llms/page.tsx that mirrors the llms.txt content for AI parsing.
  • RSS Feed: An RSS 2.0 feed at /app/rss.xml/route.ts to surface structured content for AI indexing.
  • Crawling & Schema: robots.txt permissions and Schema.org structured data to guide AI understanding and citation.
  • Best Practices: Consistent naming, clear content structure, and explicit citation guidelines to improve AI reliability.

Quick Start

  • Create /public/llms.txt with site context in the standard llms.txt format.
  • Implement /app/for-llms/page.tsx mirroring the llms.txt content in a readable page.
  • Configure /public/robots.txt to allow AI crawlers and add essential Schema.org markup on pages.
  • Validate discoverability using common AI queries and adjust content for consistency.

Frequently Asked Questions about llm-discoverability

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

FAQPage Schema
What is an llms.txt file and how does it improve AI discoverability?▼

To implement AI discoverability, create a machine-readable llms.txt file, build a readable for-llms page mirroring its content, configure robots.txt to allow AI crawlers, and add Schema.org structured data across your pages.

Do I need external dependencies or libraries to make my site readable for LLMs?▼

No external dependencies are required to make your site readable for LLMs. The solution is immediately deployable using standard web assets like public llms.txt, app pages, RSS feeds, and JSON-LD Schema.org markup.

How does Schema.org structured data help AI tools understand website content?▼

Schema.org structured data helps AI tools understand website content by providing explicit context that guides AI crawlers, reducing outdated results and ensuring accurate citation when your site is surfaced in AI responses.

Can I use an RSS feed to surface content for AI indexing?▼

To validate AI discoverability, test your site using common AI queries to see if content is accurately surfaced and cited. Adjust your llms.txt, for-llms page, and Schema.org markup for consistency if misinterpretations occur.

What is the best way to stop AI tools from misinterpreting my website?▼

To validate AI discoverability, test your site using common AI queries to see if content is accurately surfaced and cited. Adjust your llms.txt, for-llms page, and Schema.org markup for consistency if misinterpretations occur.

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