
llms.txt Standard Skill
FreeAnalyze and generate llms.txt files for AI comprehension.
Free · Opens the source repo
What llms.txt Standard Skill does
The llms.txt Standard Skill is designed to facilitate the creation and validation of llms.txt files, a new standard aimed at enhancing how AI systems interpret website structures and content. This skill allows users to either validate existing llms.txt files or generate new ones by crawling their websites. By providing a structured, machine-readable summary of a site’s content, the skill ensures that AI models can quickly and accurately understand the most important aspects of a website without the need to crawl multiple pages.
The llms.txt file serves as a guide for AI systems, similar to how robots.txt informs crawlers about what to avoid. This skill empowers website owners to dictate which pages and information AI systems prioritize, leading to improved citation accuracy and reduced misrepresentation of key facts. As the adoption of the llms.txt standard grows, having a well-crafted file will become a competitive advantage, especially for early adopters.
The skill operates by fetching the llms.txt file from a specified domain, checking its existence and validity, and providing feedback on its compliance with the standard. Users can take advantage of the detailed format rules to ensure their files meet the necessary specifications, including required sections and formatting guidelines. This structured approach not only aids in the creation of a compliant llms.txt file but also enhances the overall visibility and representation of a website in AI-driven contexts.
In summary, this skill is ideal for web developers and digital marketers who want to optimize their websites for AI comprehension and improve their online presence. It simplifies the process of adhering to the emerging llms.txt standard, making it accessible for users with varying levels of technical expertise.
When to use it
Use this skill when you need to create or validate an `llms.txt` file to enhance AI understanding of your website.
When not to use it
This skill may not be suitable if your website does not require AI optimization or if you do not plan to implement the `llms.txt` standard.
What you can build with it
Creating a New llms.txt File
When launching a new website, use this skill to generate a compliant llms.txt file that outlines your site's structure and key content.
Validating Existing llms.txt Files
If you already have an llms.txt file, use this skill to check its validity and ensure it meets the latest specifications.
Optimizing for AI Systems
For businesses looking to enhance their online visibility, implementing an llms.txt file can help shape how AI systems represent their brand.
How to install llms.txt Standard Skill
View source1. Install with the skills CLI
npx skills add zubair-trabzada/geo-seo-claude/geo-llmstxt --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by zubair-trabzadallms.txt Standard Analysis and Generation Skill
Purpose
This skill handles everything related to the llms.txt standard -- an emerging convention (proposed by Jeremy Howard in September 2024, gaining adoption through 2025-2026) that allows websites to provide structured guidance to AI systems about their content, structure, and key information. It is analogous to robots.txt (which tells crawlers what NOT to access) but instead tells AI systems what IS most useful to understand about the site.
Why llms.txt Matters
AI language models face a fundamental challenge when processing websites: they must determine which pages are most important, what the site is about, and how content is organized -- typically by crawling many pages and inferring structure. llms.txt solves this by providing an explicit, machine-readable (and human-readable) summary.
Benefits of having a well-crafted llms.txt:
- Faster AI comprehension: AI systems can understand your site's purpose and structure from a single file rather than crawling dozens of pages.
- Controlled narrative: You choose which pages and facts AI systems see first, shaping how they represent your brand.
- Higher citation accuracy: AI systems that consult llms.txt can cite the correct, authoritative page for each topic.
- Reduced misrepresentation: Key facts (pricing, features, locations) are stated explicitly, reducing AI hallucination about your business.
- Early adopter advantage: As of early 2026, fewer than 5% of websites have an llms.txt file, making it a differentiator.
The llms.txt Specification
File Location
The file MUST be located at the root of the domain:
https://example.com/llms.txt
Format Specification
The file uses Markdown formatting with specific conventions:
# [Site Name]
> [One-sentence description of what the site/business does. Keep under 200 characters.]
## Docs
- [Page Title](https://example.com/page-url): Concise description of what this page covers and why it matters.
- [Another Page](https://example.com/another-page): Description of content.
## Optional
- [Less Critical Page](https://example.com/optional-page): Description.
Detailed Format Rules
1. Title (Required)
# Site Name
- Must be the first line of the file.
- Should be the official business/site name.
- Use the H1 heading format (single
#).
2. Description (Required)
> Brief description of the site/business
- Must appear immediately after the title.
- Use Markdown blockquote format (
>). - Keep under 200 characters.
- Should clearly state what the business does and who it serves.
- Avoid marketing fluff -- be factual and specific.
3. Main Sections (Required -- at least one)
Use H2 headings (##) to organize pages by category. Common section names:
| Section Name | Purpose | Example Content |
|---|---|---|
## Docs | Primary documentation or key pages | Product pages, service descriptions, core content |
## Optional | Secondary pages worth knowing about | Blog posts, supplementary resources |
## API | API documentation | API reference, authentication guides |
## Blog | Blog or news content | Recent/popular articles |
## Products | Product catalog | Product pages, pricing |
## Services | Service offerings | Service descriptions, process pages |
## About | Company information | About page, team, mission |
## Resources | Educational/reference content | Guides, tutorials, whitepapers |
## Legal | Legal documents | Terms of service, privacy policy |
## Contact | Contact information | Contact page, support channels |
4. Page Entries (Required)
Each entry follows the format:
- [Page Title](URL): Description of page content
Rules for page entries:
- Title: Use the actual page title or a clear descriptive title.
- URL: Must be a full, absolute URL (not relative paths).
- Description: 10-30 words describing what the page covers. Be specific about the information available.
- Order: List pages in order of importance within each section.
- Limit: Include 10-30 page entries total. Prioritize your most authoritative and useful pages.
5. Key Facts Section (Recommended)
## Key Facts
- Founded in [year] by [founder(s)]
- Headquarters: [City, Country]
- [X] customers/users in [Y] countries
- Key products: [Product A], [Product B], [Product C]
- Industry: [Industry classification]
This section provides quick reference data that AI systems frequently need to answer user queries about your business.
6. Contact Section (Recommended)
## Contact
- Website: https://example.com
- Email: hello@example.com
- Support: support@example.com
- Phone: +1-555-123-4567
- Address: 123 Main St, City, State, ZIP, Country
llms-full.txt (Extended Version)
In addition to llms.txt, sites can provide /llms-full.txt -- an extended version with more detail.
Differences from llms.txt:
| Feature | llms.txt | llms-full.txt |
|---|---|---|
| Length | Concise (50-150 lines) | Comprehensive (150-500+ lines) |
| Page entries | 10-30 key pages | 30-100+ pages |
| Descriptions | 10-30 words per entry | 30-100 words per entry, may include key facts from each page |
| Audience | Quick AI comprehension | Deep AI analysis |
| Sections | 3-6 sections | 8-15 sections |
| Key facts | Business-level facts | Page-level facts and data points |
Both files can coexist. AI systems check for llms.txt first, then may optionally load llms-full.txt for deeper understanding.
Analysis Mode
When checking an existing llms.txt file:
Step 1: Fetch the File
- Use WebFetch to retrieve
[domain]/llms.txt. - Also check for
[domain]/llms-full.txt. - Record HTTP status code:
- 200: File exists -- proceed to validation.
- 404: File does not exist -- recommend generation.
- 403: File exists but is blocked -- flag as misconfiguration.
- 301/302: Redirect -- follow and note the redirect.
Step 2: Validate Format
Check each structural element:
| Element | Check | Severity if Missing |
|---|---|---|
| H1 Title | Present, matches business name | Critical |
| Blockquote description | Present, under 200 chars, factual | High |
| At least one H2 section | Present | Critical |
| Page entries with URLs | At least 5 entries present | High |
| URLs are absolute | All URLs use full https:// paths | High |
| URLs are valid | All URLs return 200 status | Medium |
| Descriptions present | Every entry has a description after the colon | Medium |
| Key Facts section | Present with business information | Medium |
| Contact section | Present with at least email | Low |
| Reasonable length | 30-200 lines | Low |
| No broken Markdown | Proper formatting throughout | Medium |
Step 3: Assess Content Quality
Rate the llms.txt on these dimensions:
Completeness (0-100):
- Does it cover all major site sections visible in the navigation?
- Are the most important/highest-traffic pages included?
- Is the Key Facts section present with accurate business data?
- Does it include recent/updated content?
Accuracy (0-100):
- Do descriptions accurately reflect page content?
- Are URLs valid and pointing to the correct pages?
- Are Key Facts verifiable and current?
- Is the business description accurate?
Usefulness (0-100):
- Would an AI system understand the site's purpose from this file alone?
- Are descriptions specific enough to differentiate pages?
- Are the most citation-worthy pages highlighted?
- Is the organization logical and intuitive?
Overall llms.txt Score = (Completeness * 0.40) + (Accuracy * 0.35) + (Usefulness * 0.25)
Step 4: Compare Against Site Content
- Crawl the site's main navigation and sitemap.
- Identify important pages NOT listed in llms.txt.
- Check if any listed URLs are broken or redirected.
- Verify that the business description matches current homepage messaging.
- Flag stale entries (pages that have been significantly updated since the llms.txt was written).
Generation Mode
When creating a new llms.txt file from scratch:
Step 1: Site Discovery
- Fetch the homepage and extract:
- Site name (from
<title>,<meta property="og:site_name">, or H1) - Business description (from meta description or hero section)
- Main navigation links
- Footer links
- Site name (from
- Fetch
/sitemap.xmlto discover all public pages. - Identify the site's primary business type (SaaS, E-commerce, Local, Publisher, Agency).
Step 2: Page Prioritization
Categorize all discovered pages and select the most important ones:
Always Include:
- Homepage
- About / Company page
- Pricing page (if exists)
- Primary product/service pages (top 3-5)
- Contact page
- Documentation landing page (if exists)
Include if High Quality:
- Top blog posts (by apparent importance, recency, or comprehensiveness)
- Case studies or customer stories
- Key resource/guide pages
- FAQ page
- Careers page (for large companies)
Skip:
- Thin category/tag pages
- Pagination pages
- Login/signup pages
- Legal boilerplate (unless specifically relevant)
- Duplicate or near-duplicate content
- Pages with minimal unique content
Step 3: Write Descriptions
For each selected page:
- Fetch the page content using WebFetch.
- Read the H1, meta description, and first 2-3 paragraphs.
- Write a description that:
- Is 10-30 words long
- States what information is on the page
- Mentions specific topics, data, or features covered
- Avoids marketing language ("best," "leading," "revolutionary")
- Uses factual, informative language
Good description examples:
Explains the three pricing tiers (Free, Pro, Enterprise) with feature comparison and annual/monthly costs.Details the company's founding in 2018, team of 45 employees, and office locations in Austin and London.Covers integration setup for Slack, Salesforce, and HubSpot with step-by-step guides and API endpoints.
Bad description examples:
Our amazing pricing page!(marketing language, no specifics)Learn more about our company.(too vague)Click here for details.(not descriptive)
Step 4: Compile Key Facts
Gather key business facts from the site:
- Year founded
- Founder name(s)
- Headquarters location
- Number of employees (if public)
- Number of customers/users (if public)
- Key products or services (list top 3-5)
- Industry classification
- Notable clients or partnerships (if public)
- Key differentiators (what makes this business unique)
- Recent milestones or achievements (last 12 months)
Step 5: Assemble the File
Construct the llms.txt following this template:
# [Site Name]
> [One clear sentence: what the business does, who it serves, and its primary value proposition. Under 200 characters.]
## Docs
- [Most Important Page](https://example.com/page): Description covering the key content on this page.
- [Second Page](https://example.com/page-2): Description of this page's content and value.
- [Third Page](https://example.com/page-3): What users and AI systems will find here.
## Products
- [Product A](https://example.com/product-a): Core features, target users, and pricing model for Product A.
- [Product B](https://example.com/product-b): What Product B does and how it differs from Product A.
## Resources
- [Guide Title](https://example.com/guide): Comprehensive guide covering [topic] with [X] sections and practical examples.
- [Blog Post](https://example.com/blog/post): Analysis of [topic] with original data from [source].
## Key Facts
- Founded in [year] by [name(s)]
- Headquartered in [City, Country]
- [Specific metric: e.g., "Serves 10,000+ businesses in 40 countries"]
- [Key differentiator: e.g., "Only platform offering real-time X and Y integration"]
- Industry: [Classification]
## Contact
- Website: https://example.com
- Email: [primary contact email]
- Support: [support URL or email]
Step 6: Validate the Generated File
Before outputting:
- Verify all URLs are reachable (200 status).
- Confirm total entry count is between 10-30.
- Check that no description exceeds 50 words.
- Verify the overall file length is 50-150 lines.
- Ensure Markdown formatting is clean and consistent.
Output Format
For Analysis Mode
Generate GEO-LLMSTXT-ANALYSIS.md:
# llms.txt Analysis: [Domain]
**Analysis Date:** [Date]
**llms.txt Status:** [Found at URL / Not Found / Error]
**llms-full.txt Status:** [Found / Not Found]
---
## Overall llms.txt Score: [X]/100
| Dimension | Score |
|---|---|
| Completeness | [X]/100 |
| Accuracy | [X]/100 |
| Usefulness | [X]/100 |
---
## Format Validation
| Element | Status | Notes |
|---|---|---|
| H1 Title | [Pass/Fail] | [Notes] |
| Description blockquote | [Pass/Fail] | [Notes] |
| H2 Sections | [Pass/Fail] | [X sections found] |
| Page entries | [Pass/Fail] | [X entries found] |
| URL validity | [Pass/Fail] | [X broken URLs] |
| Entry descriptions | [Pass/Fail] | [X missing descriptions] |
| Key Facts | [Pass/Fail] | [Notes] |
| Contact section | [Pass/Fail] | [Notes] |
---
## Missing Pages
These important pages were found on the site but not in llms.txt:
1. [Page Title](URL) -- [Why it should be included]
2. [Page Title](URL) -- [Why it should be included]
## Improvement Recommendations
1. [Specific recommendation]
2. [Specific recommendation]
3. [Specific recommendation]
## Suggested Updated llms.txt
[Complete rewritten llms.txt file if significant improvements are needed]
For Generation Mode
Output the complete llms.txt file content, ready to be saved to the site's root directory. Also output a brief GEO-LLMSTXT-GENERATION.md report explaining:
- How many pages were discovered and how many were selected
- The prioritization rationale
- Any pages that were borderline (might add later)
- Recommended update frequency (e.g., monthly for active blogs, quarterly for stable sites)
Best Practices Reference
- Update regularly. If your site publishes weekly blog posts, update llms.txt monthly. If your product changes quarterly, update after each release.
- Lead with your strongest content. The first entries in each section should be your most authoritative, comprehensive pages.
- Be specific in descriptions. "Comprehensive 3,000-word guide to React Server Components with code examples" is far more useful than "React guide."
- Include your differentiators. If your site has unique data, original research, or exclusive features, highlight these in descriptions and Key Facts.
- Keep it concise. The llms.txt should be scannable in under 60 seconds. Save detail for llms-full.txt.
- Use absolute URLs. Always include the full
https://URL, never relative paths. - Test after deployment. After uploading, verify the file is accessible at
https://yourdomain.com/llms.txtwith no redirects. - Coordinate with robots.txt. Ensure pages listed in llms.txt are not blocked in robots.txt for AI crawlers.
- Mirror your site structure. Section names in llms.txt should roughly correspond to your main navigation categories.
- Avoid sensitive pages. Do not include internal tools, admin panels, or pages with sensitive information.
Frequently asked questions about llms.txt Standard Skill
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