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sentiment-vs-fundamental

Identify stocks with negative sentiment and solid fundamentals using yfinance, Alpha Vantage, and Tavily.

Updated Mar 20, 2026

Search Tags:#fundamentals #data-sources #sentiment-analysis #market-news #contrarian-investing #financial-metrics #stock-picking

Ready to run

npx skills add https://github.com/Eveyz/agentskills --skill sentiment-vs-fundamental

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: sentiment-vs-fundamental
Source: https://github.com/Eveyz/agentskills/tree/main/sentiment-vs-fundamental
Command: npx skills add https://github.com/Eveyz/agentskills --skill sentiment-vs-fundamental

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Identify stocks where sentiment is negative yet fundamentals remain robust, enabling proactive contrarian idea generation.

Core Features & Use Cases

Three-source policy: Use yfinance-market-data for prices, alphavantage-api for fundamentals, and tavily_search for sentiment and narrative context.
Freshness and checks: Always fetch latest filings, earnings materials, and news context at run time; re-check fundamentals and sentiment on each run.
Output and workflow: Normalize data, apply a sentiment-vs-fundamentals mismatch logic, and emit a strict JSON per templates/output_schema.json describing each idea with ticker, sentiment_issue, fundamental_strength, and entry_signal.
Use Case: Surface contrarian stock ideas where negative sentiment is not supported by deteriorating fundamentals and where a clear entry signal exists.
These features ensure a robust, evidence-based screening process.

Quick Start

Prompt the AI to generate a strict JSON with ideas where sentiment is negative but fundamentals are solid.

Frequently Asked Questions about sentiment-vs-fundamental

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

FAQPage Schema

How do I find contrarian stock ideas where negative sentiment diverges from solid fundamentals?▼

To find contrarian stock ideas, this Skill cross-references recent news sentiment and social media chatter against key financial metrics to surface stocks where negative market sentiment is not supported by deteriorating fundamentals.

What data sources are needed for sentiment analysis and fundamental stock screening?▼

Sentiment analysis and fundamental stock screening require a three-source policy: yfinance-market-data for prices, alphavantage-api for fundamentals, and tavily_search for news tone and narrative context.

Can I use market news tone and financial metrics to generate a strict JSON output of entry signals?▼

Yes, you can prompt the AI to generate a strict JSON output detailing each contrarian idea with the ticker, sentiment issue, fundamental strength, and entry signal based on normalized market news tone and financial metrics.

How do I screen for stocks with robust fundamentals despite negative public chatter?▼

You screen for stocks with robust fundamentals by applying a sentiment-vs-fundamentals mismatch logic at run time, which re-checks the latest earnings materials and public social-media chatter against current financial metrics.

Does this approach fetch real-time filings and earnings materials for contrarian investing analysis?▼

Yes, this approach always fetches the latest filings, earnings materials, and news context at run time to ensure the contrarian investing analysis reflects real-time freshness and accurate fundamental strength.