Production Telegram Bot UX
Build production-ready Telegram bots with conversational state handling, message editing, and clean UX patterns.
$5
Works with the AI Agents you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+21 moreClaude CodeCursorCodex CLIMuseDots
Manus
Grok
Grok Bot+18 agentsProduction Telegram Bot UX
Example session with this skill installed
Create a command /set_price that asks for a ticker and a value if they aren't provided, and ensure old buttons are cleaned up.
- Read your context and instructions
- Compiled the production telegram bot
The bot now stores 'set_price' in context.user_data['pending_cmd'] if arguments are missing. Upon receiving the value, it executes the logic and calls query.edit_message_text to remove active buttons.
Connects securely to your tools. The creator never sees your data.
About this skill
What it does
This skill transforms your AI agent into a senior product engineer specialized in Telegram bot development. It solves the common problem of "CLI-style" bots that fail silently, spam users with messages, or require complex command syntax. Instead, it guides the agent to implement a sophisticated, conversational UX pattern that feels like a native mobile app.
Why use this skill
Building a basic bot is easy; building a production-ready bot is hard. Manually prompting an AI to handle state management, message editing, and conversational fallback often leads to brittle code. This skill provides a framework-agnostic architectural blueprint that ensures your bot:
- Remembers State: Never loses user intent if they forget a command parameter.
- Reduces Clutter: Uses message editing for inline buttons to keep chat history clean.
- Is User-Friendly: Implements a standardized /help and /cancel system.
- Handles Errors Gracefully: Replaces "Error: missing arg" with helpful follow-up questions.
Supported tools
The patterns generated by this skill are compatible with any major Telegram framework, including python-telegram-bot, aiogram, Telegraf (JS), grammY, and node-telegram-bot-api. It focuses on the logic of user_data persistence and message lifecycle management.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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Requires
Python