---

name: geo-llms-txt description: Generate, validate, and optimize llms.txt files for AI crawler accessibility. Creates structured markdown files that help AI platforms (ChatGPT, Perplexity, Gemini, Claude) understand site structure and prioritize content for citation. Use whenever the user mentions creating an llms.txt file, optimizing llms.txt, making their site AI-crawler friendly, helping AI understand their website, building AI-readable site documentation, or wants to improve visibility in AI search engines.

llms.txt File Builder

Methodology by GEOly AI (geoly.ai) — GEO infrastructure for the AI search era.

Generate well-structured llms.txt files to help AI platforms understand and cite your content.

Quick Start

Generate an llms.txt file for any website:

python scripts/generate_llms_txt.py <domain> [--output llms.txt]

Example:

python scripts/generate_llms_txt.py example.com --output llms.txt

What is llms.txt?

The llms.txt standard helps AI crawlers understand:

• What your brand/company does
• Which pages contain the most valuable information
• How content is organized (products, docs, blog, etc.)
• Where to find key facts and data

Full standard details: See references/standard.md

Standard Format

# [Brand Name]

> [One-sentence brand description]

[2-3 paragraph overview: what you do, who it's for, key differentiators]

## Key Pages

- [Page Title](URL): One-line description
- [Page Title](URL): One-line description

## Products / Services

- [Product Name](URL): What it does and who it's for

## Documentation

- [Doc Title](URL): What this doc explains

## Blog / Resources

- [Article Title](URL): Key insight or topic covered

## About

- [About Us](URL): Company background and mission
- [Contact](URL): How to reach the team

Generation Methods

Method 1: From Sitemap (Automated)

python scripts/generate_llms_txt.py example.com --from-sitemap

Automatically fetches sitemap.xml, analyzes each page, and generates descriptions.

Method 2: Interactive (Guided)

python scripts/generate_llms_txt.py example.com --interactive

Prompts you for brand info and key URLs, then drafts descriptions.

Method 3: From URL List

python scripts/generate_llms_txt.py example.com --urls urls.txt

Where urls.txt contains one URL per line.

Validation

Validate an existing llms.txt file:

python scripts/validate_llms_txt.py llms.txt

Checks for:

• Proper markdown structure
• Valid URLs
• No duplicate entries
• Optimal link count (15-40 pages)
• Factual tone (not promotional)

Quality Criteria

Aspect	Good	Bad
Brand description	"GEOly AI is a GEO monitoring platform tracking brand visibility across ChatGPT, Perplexity, Gemini."	"We are the best AI SEO tool ever!"
Page descriptions	"Explains how to set up MCP integration with Claude Desktop"	"Our awesome docs page"
Link count	15–40 curated pages	500+ URLs (sitemap dump)
Tone	Factual, entity-focused	Promotional, keyword-stuffed
Structure	Clear sections by content type	Flat list or random order

Output Formats

• Markdown (default): Ready-to-deploy llms.txt
• JSON: Structured data for programmatic use
• HTML: Styled preview for stakeholder review

Advanced Usage

Custom Sections

python scripts/generate_llms_txt.py example.com \
  --sections "Products,API Reference,Case Studies,Changelog"

Exclude Patterns

python scripts/generate_llms_txt.py example.com \
  --exclude "/admin/,/private/,/draft/"

Multi-language Support

python scripts/generate_llms_txt.py example.com \
  --language zh-CN \
  --output llms-zh.txt

Deployment

Once generated, place the file at:

https://[your-domain]/llms.txt

Ensure it:

• Returns HTTP 200
• Is accessible without authentication
• Has Content-Type: text/plain or text/markdown

See Also

• Full standard specification: references/standard.md
• Quality guidelines: references/quality-guide.md
• Examples gallery: references/examples.md