market-sentiment-monitor

Aggregate on-chain, social, and technical data into JSON trading signals.

17|45|Updated Jan 23, 2026

Search Tags:#risk-management #anomaly-detection #on-chain #market #sentiment #trading-signal #whale-tracking

Ready to run

npx skills add https://github.com/XSpoonAi/spoon-awesome-skill --skill market-sentiment-monitor

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: market-sentiment-monitor
Source: https://github.com/XSpoonAi/spoon-awesome-skill/tree/main/web3-data-intelligence/market-sentiment-monitor
Command: npx skills add https://github.com/XSpoonAi/spoon-awesome-skill --skill market-sentiment-monitor

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes scripts (resource) components.

What problem does it solve?

This Skill consolidates fragmented market signals from on-chain data, social sentiment, and technical trends to provide clear, actionable trading insights.

Core Features & Use Cases

Unified sentiment analysis across on-chain metrics, news/social sentiment, and market trends.
Real-time trading signals with confidence scores and risk context for crypto assets and DeFi tokens.
Scenario use cases include proactive risk management, portfolio rebalancing, and dip-buy opportunities.

Quick Start

Analyze real-time sentiment across sources and obtain a unified trading signal with recommendations.

Frequently Asked Questions about market-sentiment-monitor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate crypto trading signals from on-chain data and social sentiment?▼

Unified sentiment analysis combines on-chain data, social sentiment, and technical trends into a single composite score. This method provides real-time trading signals with confidence scores and risk context, preventing fragmented analysis across crypto assets and DeFi tokens.

Can I use whale tracking for risk management in a multi-asset portfolio?▼

Yes, whale tracking and on-chain anomaly detection support proactive risk management across crypto assets and DeFi tokens. Monitoring real-time sentiment and volatility indicators enables timely portfolio rebalancing and risk-aware dip-buy decisions.

Does this sentiment analysis approach require integrating external volatility indicators?▼

Yes, generating accurate trading signals requires integrating external volatility indicators, on-chain feeds, and social sentiment sources. The analysis returns a JSON response containing the composite score, confidence level, and actionable recommendations.

What is the best way to consolidate fragmented DeFi token market signals?▼

The best way to consolidate fragmented DeFi token market signals is to unify on-chain metrics, news sentiment, and technical trends into a single composite score. This provides clear, actionable trading insights with confidence scores and risk context.

What data format does the real-time market sentiment analysis return?▼

The real-time market sentiment analysis returns a JSON structure containing the composite score, confidence level, and trading recommendations. This format supports direct integration into automated crypto trading systems and portfolio management workflows.

When should I not rely on composite sentiment scores for trading decisions?▼

You should not rely solely on composite sentiment scores when on-chain data feeds or social sentiment sources experience latency or anomalies. Always cross-reference the generated confidence scores and risk context with external volatility indicators before executing trades.