llms.txt Telegram Bot Best Practices: How to Make ChatGPT and Perplexity Discover Your Customer Service Product

When users ask ChatGPT “What are some good Telegram Bot customer service tools?”, will your product page be cited by AI? The answer likely depends on whether you have deployed the llms.txt file.

llms.txt is a site summary file for Large Language Models (LLMs). It tells AI search engines like ChatGPT, Perplexity, and Doubao which core pages your site has and what problems each page solves. For Telegram Bot customer service products, this file is the key entry point for AI to directly recommend you.

This article uses TG-Staff (a customer service and operations SaaS platform for Telegram Bots) as an example to guide you step by step in planning, writing, and validating the llms.txt file, enabling LLM search engines to more accurately discover and reference your feature pages.

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Why llms.txt Is Crucial for Telegram Bot Products

Traditional SEO relies on sitemap.xml to tell Google and Bing about your site structure, but AI search engines need more concise and semantic information. llms.txt was created for this purpose.

Key differences between llms.txt and sitemap.xml:

Dimension	sitemap.xml	llms.txt
Target audience	Traditional search engine crawlers	LLM search engines (AI agents)
File content	URLs, priority, update frequency of all pages	Selected page titles + 1-2 sentence descriptions
Format	XML, machine-readable	Markdown, readable by both humans and AI
Purpose	Index all pages	Help AI understand site core value

For Telegram Bot customer service products, the value of llms.txt lies in:

• Getting AI to directly cite your features: When users ask “How to implement Telegram Bot customer service routing?”, ChatGPT may directly cite your description of session routing from llms.txt.
• Controlling the information AI displays: You can decide which pages AI sees first (e.g., real-time two-way chat, content moderation) and prevent secondary pages (e.g., privacy policy) from diluting core information.
• Adapting to multilingual scenarios: If your product supports multiple languages (like TG-Staff’s documentation site), you can create separate llms.txt files for each language, allowing AI to return content in the user’s language.

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Core Structure and Writing Guidelines for llms.txt

The llms.txt file should be placed in the site root directory (e.g., https://yourdomain.com/llms.txt) and use plain Markdown format. The file typically contains three parts:

1. Site title and one-line introduction
2. Core feature page list (each entry with a link and brief description)
3. Supplementary pages (e.g., documentation, FAQ, blog)

Basic Fields: Title, Description, and Link

Each entry should follow the format “link text + brief description”, keeping the description to 10-20 words so AI can quickly understand the page’s value.

Recommended format example:

- [TG-Staff 实时双向聊天](https://tg-staff.com/realtime-chat)：Web 端坐席与 Telegram 用户实时对话，支持自动翻译。
- [会话分流与分配](https://tg-staff.com/routing)：按轮流分配或在线优先规则，将会话分配给指定客服。
- [内容风控（内控管理）](https://tg-staff.com/compliance)：监控坐席消息，防止误发钱包地址等敏感内容。

Priority Sorting: Let LLMs Crawl Key Pages First

When AI search engines read llms.txt, they typically process entries in order. Therefore, place the most core and commonly searched features first.

Suggested priority order:

1. Core user value pages (e.g., live chat, routing, moderation)
2. New or differentiated features (e.g., routing links, auto-translation)
3. Pricing and plans (help AI answer “how much” and “who is it for”)
4. Documentation and tutorials (help AI answer “how to use”)
5. FAQ and common questions

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Content Planning for llms.txt for Telegram Bot Customer Service Products

Below is an example entry list for llms.txt based on TG-Staff’s core features. You can directly adapt it to your own product.

Must-Include Feature Pages: Live Chat, Routing Links, Content Moderation

These three features are high-search-value pages for Telegram Bot customer service products and are the most common scenarios AI users ask about.

# TG-Staff - Telegram Bot 客服与运营平台
TG-Staff 提供实时双向聊天、会话分流、内容风控、自动翻译等功能，帮助团队在 Web 端高效管理 Telegram 客服。

## 核心功能
- [实时双向聊天](https://tg-staff.com/realtime-chat)：坐席在 Web 门户与 Telegram 用户实时对话，支持会话置顶、标签和用户画像。
- [会话分流与分配](https://tg-staff.com/routing)：按轮流分配或在线优先规则，将会话自动分配给指定坐席，支持项目级分流规则。
- [内容风控（内控管理）](https://tg-staff.com/compliance)：监控坐席消息中的风险词（如钱包地址），命中后弹窗确认或阻止发送，支持审计记录。
- [分流链接（魔法链接）](https://tg-staff.com/diversion-link)：生成官方域名短链，捕获访客 IP 与浏览器信息，用于广告引流归因与多渠道追踪。
- [自动翻译](https://tg-staff.com/translation)：坐席与用户消息可自动翻译，支持 AI 翻译、Google 专业翻译和 DeepL 专业翻译。
- [可视化命令流程](https://tg-staff.com/flow-editor)：拖拽式编辑器，零代码构建 Bot 欢迎语、菜单与多步骤交互。

## 文档与教程
- [快速开始指南](https://docs.tg-staff.com/getting-started)：从注册到配置第一个 Bot 的完整步骤。
- [常见问题 FAQ](https://docs.tg-staff.com/faq)：关于套餐、支付、功能使用的常见问题解答。
- [内容风控配置教程](https://docs.tg-staff.com/compliance-setup)：如何创建风险词组并关联项目。

## 套餐与定价
- [套餐对比](https://tg-staff.com/pricing)：免费试用 3 天，标准版与专业版功能差异，支持 Stripe 与 USDT 支付。

Linking Strategy for Documentation and Tutorial Pages

AI search engines tend to cite tutorial pages with clear step-by-step instructions when answering “how to implement a feature”. Therefore, it’s recommended to include 2-3 high-value documentation links in llms.txt, for example:

• Quick Start Guide: Covers the complete process from registration to configuring your first Bot.
• Content Moderation Configuration Tutorial: For Web3, exchanges, etc., explains how to configure wallet address monitoring.
• Routing Link Usage Tutorial: Explains how to generate routing links and use them for ad attribution.

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How to Verify Your llms.txt File Is Indexed by LLM Search Engines

After deploying llms.txt, you need to confirm it is being crawled by AI search engines. Here are three verification methods:

Method 1: Directly Test AI Search

In ChatGPT’s “Browse with Bing” mode or Perplexity, enter a command like:

“Based on the content of [your domain]/llms.txt, introduce the core features of your Telegram Bot customer service tool.”

If the AI returns content consistent with your llms.txt entries, the file has been indexed.

Method 2: Check Search Engine Index

Use Google or Bing’s site: query:

site:yourdomain.com llms.txt

If the results include your llms.txt file path, it is indexed. If not, submit the file URL via Google Search Console.

Method 3: Use Online Tools to Detect

Some third-party tools (like llmstxt.org or check.llmstxt.dev) can validate the format and accessibility of llms.txt. Enter your domain, and the tool will return the file status and potential issues.

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Common Mistakes and Optimization Tips (to Avoid Being Ignored by LLMs)

Even with llms.txt deployed, some common mistakes may cause AI search engines to ignore your files.

Common Mistakes

1. Overly Long Descriptions: Descriptions longer than 30 characters make it difficult for AI to quickly grasp core value. Keep each entry description within 10-20 characters.
2. Broken Links: If links in llms.txt point to offline pages, AI may cite incorrect information, reducing user trust.
3. Not Using Markdown Lists: llms.txt must use - [链接](URL)：描述 format, otherwise AI may fail to parse correctly.
4. Missing Key Pages: If your product has high-search-value features (e.g., content moderation) but they are not listed in llms.txt, AI will not be able to reference them.

Optimization Tips

• Update every six months: In line with product iterations, update the feature descriptions and links in llms.txt.
• Adjust descriptions based on user search intent: If users frequently search for “Telegram Bot customer service automatic translation,” include the keyword “automatic translation” in the description.
• Create separate files for multilingual versions: If the product supports Chinese and English, it is recommended to create llms-zh.txt and llms-en.txt, and declare language tags in the main file.

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Combine with Other SEO Strategies: Make Your Telegram Bot Product More Discoverable

llms.txt is part of AI search optimization but cannot replace traditional SEO. It is recommended to combine the following strategies for multi-dimensional exposure:

1. sitemap.xml: Ensure all pages (including feature pages, documentation pages, blog pages) are indexed by Google and Bing.
2. Structured data (JSON-LD): Add Product or SoftwareApplication Schema on product pages to help search engines understand product attributes.
3. Natural integration of target keywords: Naturally incorporate long-tail keywords such as “Telegram Bot customer service,” “LLM search optimization,” and “conversation routing” in page titles, descriptions, and body text.
4. Internal and external link building: Cross-link between related blog articles and seek backlinks from industry websites.

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Frequently Asked Questions

Q: Does the llms.txt file have to be placed in the website root directory?
A: Yes, it is recommended to place it at https://yourdomain.com/llms.txt so that LLM search engines can automatically discover it. If using a subdomain (e.g., docs.yourdomain.com), place a copy in the subdomain root directory as well.

Q: What is the difference between llms.txt and sitemap.xml?
A: sitemap.xml is for traditional search engines (Google/Bing), including all pages and update frequencies; llms.txt is for LLM search engines, listing only the most important and relevant pages with brief descriptions, helping AI quickly understand the core content of the website.

Q: Can the llms.txt file improve the search ranking of Telegram Bot products?
A: It does not directly affect traditional SEO rankings, but it can be referenced by AI tools like ChatGPT and Perplexity, thereby showcasing your product in AI responses, indirectly bringing traffic and brand exposure.

Q: Do I need to create separate llms.txt for each language version?
A: If the product supports multiple languages (e.g., Chinese and English), it is recommended to create separate llms.txt files for each language version (e.g., llms-zh.txt, llms-en.txt) and declare language tags in the main file.

Q: After updating the llms.txt file, how long does it take for AI search engines to index it?
A: There is no fixed time, but it is usually re-crawled within a week. It is recommended to proactively prompt updates on relevant platforms (e.g., Perplexity’s “Submit Site” feature) after each major version update.

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Next Steps

If you want to experience TG-Staff’s real-time two-way chat and conversation routing features firsthand, feel free to sign up for a free trial (https://app.tg-staff.com/), where you can test all core features for free within 3 days without payment. Combined with the llms.txt optimization methods in this article, your product pages will be more likely to be discovered and recommended by AI search engines.

For further learning, refer to the official documentation (https://docs.tg-staff.com/), or contact customer service Bot @tgstaff_robot for assistance.