llms.txt for Agencies: GEO as a New Service Offering

GEO (Generative Engine Optimization) is what clients are starting to ask about: "Why does ChatGPT mention our competitor and not us?" The honest answer is uncomfortable – nobody can guarantee an AI citation. But there is a handful of technical prerequisites that can be checked, established and proven. That is what a credible service offering is made of. This article shows how agencies and freelancers can offer GEO, what they may promise, how to price it and how to demonstrate results.

GEO as a Measurable Service Offering

The main problem with new technologies is measurability. AI visibility sounds abstract – until you present a concrete score. The AI Visibility Check tool gives every website a score from 0–100 based on:

• Presence of llms.txt and llms-full.txt
• Schema.org markup (types and completeness)
• AI crawler configuration in robots.txt
• Metadata quality and structure
• FAQ content and structured answers

This score is your entry point into the client conversation – as a diagnosis, not a promise: "Your website meets 34 of 100 points of the technical prerequisites. Three of them we can establish within two weeks." The score measures inputs (access, structure, files), not the outcome in an AI answer. Keeping the two apart saves you the later argument about promises not kept.

What GEO Actually Is for Agencies – and What It Is Not

An AI system can only mention a website in an answer if three things are true: the crawler is allowed to access it (robots.txt), it can read the content unambiguously (structure, Schema.org, llms.txt), and it has actually fetched the content (verifiable in the server logs). These three layers are what you as an agency can influence and prove. Everything above that – whether the system then cites your client, in which position, with which wording – is decided by the model, and no provider has publicly committed to a procedure.

GEO is therefore not a "ranking service for ChatGPT". It is technical hygiene plus content structure plus measurement – comparable to technical SEO ten years ago, when nobody could promise position 1 but everyone could fix a broken canonical setup. The difference from SEO: there is no Search Console for ChatGPT. What you can show the client are the prerequisites and the crawler hits, not rankings.

Agency Workflow: 3 Projects per Day

What You May Promise the Client – and What You May Not

The most common mistake in GEO offerings is the wording. "We'll get you into ChatGPT" is a promise you cannot keep, and a problem in a dispute. Phrasings that can be substantiated:

• "We make sure AI crawlers are allowed and able to read your website." – verifiable with the robots.txt check and the Schema score, before and after.
• "We deliver an llms.txt and llms-full.txt to specification and keep them current." – verifiable with the validator; the file sits in the root.
• "We prove whether and which AI crawlers fetch your content." – verifiable with bot tracking or server logs, with date and frequency.
• "We document monthly whether your brand is mentioned for ten defined buyer questions in ChatGPT, Perplexity and Claude." – verifiable through documented queries; honestly labelled a sample, not a statistic.

What you should not promise: mentions, positions, traffic or revenue growth from AI answers. Anyone promising that is selling something they cannot deliver – and an informed client knows it by now.

Service Package: Audit, Implementation, Evidence

In practice a three-tier structure has proven itself, and each tier can be sold separately:

1. GEO audit (one-off). Inventory with the free tools, complemented by a manual sample of ten buyer questions in three AI systems. Result: a document with score, findings and prioritised actions. The audit is the entry point and justifies itself through the clarity it creates – even if the client commissions nothing afterwards.
2. Implementation (fixed fee). Clean up robots.txt, add missing Schema.org markup, generate and upload llms.txt and llms-full.txt, account for shop-system specifics. For stores, add the product drill-down so that prices and availability end up in the llms-full.txt. Effort: one to three days depending on the system.
3. Evidence and maintenance (monthly). Evaluate bot tracking, update the llms.txt when catalogue or structure change, repeat the ten buyer questions and document changes. This is the part that carries the subscription – not because it is laborious, but because without it the client never learns whether the work had any effect.

On pricing logic: the audit should be priced so a client can approve it without lengthy alignment; implementation by effort; maintenance as a small monthly amount that funds the measurement. Actual numbers depend on your positioning – what matters more is that each tier has its own verifiable result.

API Access for Batch Processing

For agencies with many clients, the Agency Plan offers REST API access. This allows llms.txt generation to be automated and integrated into existing workflows:

• Batch generation: Process multiple domains in one run
• CI/CD integration: Automatic updates on content changes
• JSON output: Structured data for custom dashboards and reports
• 100 requests/day: Up to 500 URLs per request

The Complete GEO Audit Package

llmstxtgenerator.de offers agencies a complete audit toolkit:

• AI Visibility Check: Overall score + recommendations
• robots.txt AI Check: Are GPTBot, ClaudeBot etc. blocked?
• Schema Score: Which Schema.org types are missing?
• llms.txt Validator: Does the file meet the standard?
• llms.txt Generator: With drill-down for store clients

All checking tools are free and usable without an account. That makes it possible to test a GEO offering with the first two or three clients before investing in processes and subscription models.

Frequently Asked Questions for Agencies