# Telegram Bot

Sheerluck Telegram bot is available both in private chats and in group chats. It is the first utility which started Sheerluck ecosystem. 

**Features**

* Analyze tokens from contract address
* Analyze GitHub repositories
* Find wallets from PNL data
* Supports natural queries

**Analyzing Tokens**

To use token analysis you just have to message our [T](https://t.me/sheerluckai_bot)[elegram bot](https://t.me/sheerluckai_bot) (There is also [Chinese Version](https://t.me/sheerluckai_zh_bot)). You can either message it with token address or use `/analyze TOKEN_ADDRESS` (This is the only supported way in group chats)

<figure><img src="/files/sySLOIGFBfN3cIvJjsLx" alt="Sample analysis of token with Sheerluck Telegram Bot" width="243"><figcaption><p>Example analysis of a token through the bot</p></figcaption></figure>

To see capabilities and data points for token analysis, please see [token analysis data points page.](/data-points/token-analysis.md)

**Analyzing Repositories**

To use repository analysis you just have to message our [T](https://t.me/sheerluckai_bot)[elegram bot](https://t.me/sheerluckai_bot) (There is also [Chinese Version](https://t.me/sheerluckai_zh_bot)). You can either message it with GitHub repository link or use `/repo TOKEN_ADDRESS` (This is the only supported way in group chats)

<figure><img src="/files/yAT52h4ZoyWCiUtYI0MN" alt="Example repository analysis" width="243"><figcaption><p>Example analysis of a repository through the bot</p></figcaption></figure>

To see capabilities and data points for repository analysis, please see repository [analysis data points page.](/data-points/repository-analysis.md)


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.sheerluck.ai/ecosystem/telegram-bot.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.