News Sentiment Analyst

Aggregate and classify financial news sentiment into Risk-On / Risk-Off signals for market and individual stocks using the Finskills API.

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Install skill "News Sentiment Analyst" with this command: npx skills add finskills/news-sentiment-analyst

News Sentiment Analyst

Aggregate and analyze financial news and market sentiment using the Finskills API news endpoints. Extract actionable signals from headlines, classify sentiment by ticker and sector, and surface market-moving catalysts — so you can react to information before it's fully priced in.


Setup

API Key requiredRegister at https://finskills.net to get your free key.
Header: X-API-Key: <your_api_key>

Get your API key: Register at https://finskills.net — free tier available, Pro plan unlocks real-time quotes, history, and financials.


When to Activate This Skill

Activate when the user:

  • Asks "what's happening in the market today?"
  • Wants to check sentiment for a specific stock before trading
  • Asks about recent news for a company or sector
  • Wants to understand why a stock moved (news catalyst identification)
  • Asks to summarize financial media themes or narratives

Data Retrieval — Finskills API Calls

1. General Financial News Feed

GET https://finskills.net/v1/free/news/finance

Extract: title, summary, source, published timestamp, sentiment score (if provided), tickers mentioned

2. Latest News (Pro — broader coverage)

GET https://finskills.net/v1/news/latest

Extract: same fields as above, with more sources and more recent latency

3. Symbol-Specific News

GET https://finskills.net/v1/news/by-symbol/{SYMBOL}

Extract: news articles filtered to a specific stock — title, summary, sentiment, source, timestamp


Analysis Workflow

Step 1 — News Aggregation

Collect and deduplicate articles across sources. Sort by:

  1. Recency (most recent first)
  2. Estimated impact (market-moving stories: Fed decisions, earnings, M&A, macro data)

Source trust tiers:

  • Tier 1 (high authority): Reuters, Bloomberg, WSJ, FT, CNBC
  • Tier 2 (solid): MarketWatch, Barron's, Seeking Alpha (News), Yahoo Finance
  • Tier 3 (background): General blogs, press releases

Step 2 — Market-Wide Sentiment Classification

For each article, classify:

SignalBearishNeutralBullish
Fed/PolicyRate hike surprise, hawkish tonePolicy hold expectedRate cut, dovish language
EarningsMiss + lowered guidanceBeat, maintained guidanceBeat + raised guidance
Economic DataWeak jobs, poor PMIMixed dataStrong GDP, low unemployment
GeopoliticsNew conflicts, trade warOngoing tensionsPeace/trade deal
M&ADeal collapse, hostile bidRumored dealsFriendly acquisition at premium
MacroRecession signalsSoft landing narrativeGrowth acceleration

Assign an overall Market Sentiment Score for the day:

  • 🟢 Risk-On: Majority of market-moving news is bullish
  • 🟡 Mixed: Conflicting signals across sectors
  • 🔴 Risk-Off: Majority bearish, defensive positioning

Step 3 — Ticker/Sector Sentiment Map

Group articles by stocks/sectors mentioned:

  • For each ticker mentioned 2+ times: assign net sentiment (positive/negative/neutral)
  • Identify sectors with bullish news clusters (potential sector momentum)
  • Identify sectors with bearish news clusters (potential sector rotation out)

Step 4 — Catalyst Identification

Flag high-impact event types:

  • 🔴 Earnings: Beat/miss/guidance change
  • 🔴 Merger/Acquisition: Target premium, integration cost
  • 🔴 FDA/Regulatory: Drug approval, regulatory violation
  • 🔴 Management change: CEO/CFO departure or appointment
  • 🟡 Analyst action: Upgrade, downgrade, price target change
  • 🟡 Macro data: CPI, NFP, GDP, FOMC minutes
  • 🟡 Insider activity: Large insider buy/sell (link to insider-trade-tracker)
  • 🟢 Buyback announcement: Often positive signal
  • 🟢 Contract win / Partnership: Revenue catalyst

Step 5 — Summary and Recommendations

Generate:

  1. 3-bullet market summary (most important macro/market stories)
  2. Top 3 bullish catalysts (specific stocks/sectors)
  3. Top 3 bearish risks (specific stocks/sectors)
  4. Sector rotation signal: which sectors are in/out of favor today

Output Format

╔══════════════════════════════════════════════════════╗
║     NEWS & SENTIMENT REPORT  —  {DATE} {TIME}       ║
╚══════════════════════════════════════════════════════╝

🌡️ OVERALL MARKET SENTIMENT: {RISK-ON / MIXED / RISK-OFF}
   Sources analyzed: {N}  |  Timeframe: Last {hours}h

📌 TOP MARKET THEMES
  1. {Most important market-moving story}
  2. {Second important story}
  3. {Third important story}

📈 BULLISH CATALYSTS
  🟢 {TICKER/SECTOR}: {headline}
     Source: {source} | Sentiment: Positive | Impact: {High/Medium/Low}
     Signal: {one-line interpretation}

  🟢 {TICKER/SECTOR}: {headline}
     ...

📉 BEARISH RISKS
  🔴 {TICKER/SECTOR}: {headline}
     Source: {source} | Sentiment: Negative | Impact: {High/Medium/Low}
     Signal: {one-line interpretation}

  🔴 {TICKER/SECTOR}: {headline}
     ...

🏭 SECTOR SENTIMENT MAP
  Sector          Sentiment   Key Driver
  Technology      🟢 Bullish  AI chip demand stories, NVDA + SMCI positive
  Energy          🔴 Bearish  Crude oil supply glut concerns
  Financials      🟡 Mixed    Rate cut hopes vs. credit risk headlines
  Healthcare      🟡 Neutral  No major catalysts today
  ...

🔍 STOCK-SPECIFIC NEWS
  [If user specified a ticker]
  {TICKER} — {N} stories in last 24h:
    {timestamp}: {headline} [{Positive/Negative/Neutral}]
    {timestamp}: {headline} [{sentiment}]
  Net Sentiment: {Positive/Mixed/Negative}

⚡ HIGH-IMPACT EVENTS TO WATCH
  • {Event 1} — scheduled {date/time}
  • {Event 2} — expected announcement

Limitations

  • News latency varies by source; some articles may be 15–60 minutes delayed.
  • Sentiment classification is AI-assisted and may miss nuanced or sarcastic language.
  • This skill surfaces information signals, not guaranteed trading signals.
  • Always verify high-impact news with primary sources (company IR, official filings).

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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