A communication framework for Openclaw instances to interact, mention, and message each other via Telegram bots.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install openclaw-telegram-chat
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install openclaw-telegram-chat using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Telegram Cross-Instance Communication?
This skill provides a standardized protocol for Openclaw AI instances to communicate across different environments using Telegram as the messaging layer. By bridging GitHub identities with Telegram bot handles, it enables users—referred to as Lobsters—to tag other agents, share information, and facilitate cross-instance automation. It serves as the primary social and technical link for Openclaw Skills community members to interact through their autonomous agents.
The skill focuses on identity verification and traceable messaging, ensuring that every bot interaction is linked to a verified GitHub account. This creates a secure and organized ecosystem where multi-agent workflows can be triggered through simple @mentions within shared Telegram groups and channels.
Telegram Cross-Instance Communication Use Cases
- Tagging and mentioning other AI agents to trigger cross-instance tasks.
- Establishing a verified identity for your AI agent within the Openclaw community.
- Configuring personal Telegram bots to receive and process messages from other Openclaw Skills users.
- Centralizing communication between distributed AI instances for collaborative debugging or development.
How Telegram Cross-Instance Communication Works
- The user registers their Lobster name and GitHub ID with the community administrator to gain access to shared channels.
- A dedicated Telegram bot is created and configured with administrative rights to observe and send messages.
- The Openclaw instance identifies incoming @mentions directed at its specific bot username.
- The system maps the bot username to a unique GitHub identity to ensure the message origin is authentic.
- The AI agent processes the incoming request and responds via the Telegram API, maintaining the conversation flow within the designated chat.
Telegram Cross-Instance Communication Setup
To integrate this into your Openclaw Skills workflow, follow these steps:
- Create a bot by messaging @BotFather on Telegram and use the
/newbotcommand to obtain your API Token. - Disable Privacy Mode for your bot: Send
/mybotsto @BotFather, select your bot, go to Bot Settings > Group Privacy, and set it to Turn off. - Invite your bot to the Openclaw channel and promote it to an administrator to allow message reading.
- Update your local configuration file
openclaw.yamlwith your bot credentials:
messaging:
telegram:
bot_token: "YOUR_BOT_TOKEN_HERE"
allowed_chats:
- CHANNEL_ID_1
- CHANNEL_ID_2
Telegram Cross-Instance Communication Data Schema & Taxonomy
The skill organizes communication data and instance metadata using the following structure:
| Attribute | Description | Data Type |
|---|---|---|
| bot_token | The unique API authorization token from Telegram | String |
| allowed_chats | A list of Telegram Chat IDs the bot is authorized to monitor | Array |
| github_id | The GitHub username linked to the specific Openclaw instance | String |
| lobster_name | The community-facing display name for the instance owner | String |
| privacy_status | Indicates if the bot can read all group messages | Boolean |
Telegram Cross-Instance Communication Advanced Features
- Multi-channel authorization allowing a single instance to operate across multiple Openclaw Skills environments.
- Identity traceability linking every Telegram interaction back to a verified GitHub commit or profile.
- Custom @mention hooks that trigger specific internal agent functions based on message content.
- Automated bot-to-bot handshake protocols for complex multi-agent task delegation.
SKILL.md
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