geo-llms-txt
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.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/geoly-geo/geo-llms-txtllms.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
Metadata
Not sure this is the right skill?
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-geoly-geo-geo-llms-txt": {
"enabled": true,
"auto_update": true
}
}
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Analyze competitor GEO (Generative Engine Optimization) strategies by examining their content structure, Schema markup, llms.txt, and AI citation signals. Benchmark your brand against competitors and identify strategic gaps and opportunities. Use whenever the user mentions scanning competitor GEO strategies, comparing AI search performance, analyzing competitor content for AI citations, finding GEO gaps, or wants to understand how competitors win AI citations.
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