Data Analysis
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market-sentiment-pulse

Aggregates and analyzes market sentiment for crypto and stock tickers by scanning news and social signals for quick trading vibe checks.

Introduction

Market Sentiment Pulse is an automated intelligence skill designed for traders and financial analysts who need real-time snapshots of market psychology. By monitoring diverse data streams—including news headlines, social media discourse, and market commentary—the agent distills complex noise into a readable sentiment index ranging from -1 (Extremely Fearful) to +1 (Extremely Greedy). This tool is essential for those employing sentiment-based trading strategies or those who require a quick sanity check before executing high-stakes orders in volatile markets.

The agent acts as a sentiment aggregator, utilizing natural language processing (NLP) and agentic reasoning to synthesize conflicting reports into a coherent narrative. It identifies key narrative drivers behind price movements, allowing users to understand not just whether the market is bullish or bearish, but why. Whether you are managing a portfolio of digital assets or tracking traditional equities, this skill bridges the gap between raw data and actionable insight, helping users avoid reactionary trading based on incomplete information.

  • Real-time sentiment scoring from -1 to +1 (Fear vs. Greed).

  • Multi-source data aggregation from financial news APIs and social signals.

  • Narrative driver identification to contextualize market movements.

  • Seamless integration into trade analysis workflows via natural language commands.

  • Automated Vibe Check capability for rapid portfolio review sessions.

  • Designed for individual traders, swing traders, and data-driven investors.

  • Input: Requires a specific asset identifier (e.g., $BTC, $TSLA) to trigger the scanning process.

  • Output: A concise summary report containing the current sentiment score, the prevailing market mood, and identified catalysts.

  • Constraints: Sentiment analysis is based on available data; it is not a prediction tool and should be used as one component of a broader risk management strategy.

  • Best practice: Trigger the skill during initial analysis sessions or as a recurring heartbeat check for active portfolio management.

Repository Stats

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4,456
Forks
1,217
Open Issues
7
Language
Python
Default Branch
main
Sync Status
Idle
Last Synced
Apr 30, 2026, 04:17 PM
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