- name
- News Sentiment Analyst
- version
- 1.0.3
- description
- Aggregate and classify financial news sentiment into Risk-On / Risk-Off signals for market and individual stocks using the Finskills API.
- author
- finskills
- metadata
- openclaw
- requires
- env
- primaryEnv
- FINSKILLS_API_KEY
- homepage
- https://github.com/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 required — Register 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/financeExtract: title, summary, source, published timestamp, sentiment score (if provided), tickers mentioned
2. Latest News (Pro — broader coverage)
GET https://finskills.net/v1/news/latestExtract: 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:
- Recency (most recent first)
- 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:
| Signal | Bearish | Neutral | Bullish |
|---|---|---|---|
| Fed/Policy | Rate hike surprise, hawkish tone | Policy hold expected | Rate cut, dovish language |
| Earnings | Miss + lowered guidance | Beat, maintained guidance | Beat + raised guidance |
| Economic Data | Weak jobs, poor PMI | Mixed data | Strong GDP, low unemployment |
| Geopolitics | New conflicts, trade war | Ongoing tensions | Peace/trade deal |
| M&A | Deal collapse, hostile bid | Rumored deals | Friendly acquisition at premium |
| Macro | Recession signals | Soft landing narrative | Growth 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:
- 3-bullet market summary (most important macro/market stories)
- Top 3 bullish catalysts (specific stocks/sectors)
- Top 3 bearish risks (specific stocks/sectors)
- 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 announcementLimitations
- 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).