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Telegram Crypto Token Tracker Bot with TP/SL Monitoring

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Telegram Crypto Token Tracker Bot with TP/SL Monitoring
Client
Crypto Tracking System
Budget
$2000
Duration
3 weeks

A Telegram bot for tracking tokens launched inside Telegram with real-time price monitoring, TP/SL level tracking, and post-buy signal behavior analysis.

Problem

The goal was not just to track token prices, but to build a system that shows how an asset behaves after a buy signal and how effectively it moves toward profit or risk thresholds.
The main challenges included:

  • getting up-to-date token data in real time
  • tracking asset behavior after a buy signal
  • monitoring progress toward take profit and stop loss levels
  • logging the best entries, holds, and exits
  • giving users a clearer view of token performance
  • helping improve risk management in volatile markets

Process

The project was built around token monitoring logic, signal-following mechanics, and practical analytics inside Telegram.

  • developed a Telegram bot for tracking crypto tokens
  • implemented real-time price monitoring logic
  • added post-buy signal tracking
  • configured TP/SL level monitoring for each token
  • integrated logging for best entries, holds, and exits
  • focused on giving users a more structured understanding of asset behavior after a signal

Solution

The final result was a Telegram bot for token performance monitoring that combines price tracking, TP/SL monitoring, and signal outcome analysis in one tool.

Key solutions delivered:

  • Telegram-based token monitoring
  • real-time price tracking
  • buy signal follow-up logic
  • TP/SL progress tracking
  • logging of entries, holds, and exits
  • clearer token behavior visibility
  • a practical tool for improved risk management

Result

The result was an analytical Telegram tool that helps users better understand how tokens behave after a buy signal and provides a more structured view of entries, holding phases, and exits.
The project improved visibility into token performance and added more transparency to risk evaluation and signal quality analysis.

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