Building a Crypto Market Analysis and Alert Workflow

Summary

This tutorial describes a visual workflow for producing and distributing cryptocurrency market analysis. Scheduled market data requests collect 15-minute, hourly, and daily candles; the workflow labels and combines them. A separate news request gathers recent articles, trims them to titles and descriptions, and sends them to a language model for short- and long-horizon sentiment scores. Another model prompt combines sentiment with the candle data to create spot and leveraged trade proposals, which are then sent to Telegram.

The document explains each stage and gives example node configurations, data transformations, and prompts. It proposes extending the workflow with order execution and monitoring nodes. It does not provide evidence that the generated analysis is profitable or reliable. The sample content-splitting logic also appears inconsistent: after detecting the leverage section, it returns variables from the fallback branch rather than the calculated blocks. News coverage, model judgments, timing, and trade levels depend on external services and prompt behavior, so the workflow is best understood as an automation pattern rather than a validated strategy.

Key ideas

• A scheduled workflow can combine candle data from multiple timeframes into one analysis input.
• Recent news can be reduced to article titles and descriptions for a separate sentiment assessment.
• The proposed analysis combines technical inputs and sentiment to generate spot and leveraged trade plans.
• Telegram can distribute generated reports, while further nodes could connect analysis to execution and monitoring.
• The document provides no performance validation, and its example text-splitting logic contains an apparent variable error.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.