News Intelligence

Use this skill to perform deep, structured analysis on a stream of unstructured text and news data. It goes beyond simple fetching; it de-duplicates, extracts entities, assesses market impact, and generates actionable alerts or insights from global news flow.

When to use

User asks for a deep dive into recent news regarding a specific topic, sector, or company (e.g., /news AI chips).
The system needs to cluster, filter, or evaluate the credibility of a surge in media attention.
Another skill (like market-discovery or market-monitor) requests an impact assessment of a breaking headline.

Core Processing Pipeline

Treat news analysis as an 11-step data refinement pipeline. Depending on the user's prompt, execute the relevant steps to form the final response.

1-2. Collection, Deduplication & Filtering

Fetch: Gather news across Bloomberg, Reuters, Financial Times, X (Twitter), and company announcements for the target topics or region.
Browser fallback: If a relevant source is dynamic, login-gated, or stronger in site-native search, use browser_site for Xueqiu, Eastmoney, Reddit, Zhihu, or YouTube context.
Verification path: If the claim looks noisy, incomplete, or repost-driven, load browser-news-verifier before concluding impact.
Filter: Remove duplicate stories, PR spam, and low-credibility sources. Only pass clean text to the next phase.

3-4. Event & Entity Extraction

Entities: Identify all Companies, People, Countries, and Products mentioned (e.g., NVIDIA, US, AI GPU).
Events: Classify the core action into a category: Earnings, M&A, Product Launch, Regulation, Partnership, or Lawsuit.

5-6. Sentiment & Market Impact Analysis

Sentiment: Score the news conceptually as Bullish, Neutral, or Bearish.
Impact: Determine the blast radius of the event:
- Primary Impact: Which specific ticker is affected directly?
- Sector Impact: Which industry group moves in sympathy?
- Market Impact: Does this move macro indices?
- Time Horizon: Is this a Short-Term shock or Long-Term structural change?

7-8. Trending & Clustering

Group multiple related articles into a single News Cluster (e.g., "AI Chip Competition").
Compare term frequencies vs. historical baselines to detect emerging Trending Topics.
When prior collected intel matters, use intel_search to pull earlier related items from the workspace store before concluding that a topic is truly new.
If the user asks for a causal explanation, transmission path, or a more visual artifact, use logic_chain_visualizer to render the chain instead of burying it in prose.

9. Risk Detection

Flag negative catalysts specifically as Risk Alerts (e.g., Regulatory investigations, geopolitical tension, CEO departures) and assign a Severity (Low, Medium, High).

10-11. AI Insight & Alert Generation

Synthesize the entire pipeline into a coherent human-readable insight or trigger an urgent alert format if the impact is severe.

Output Formats

Standard Insight Report

For general queries (e.g., "What's the latest on the semiconductor sector?"):

# 📰 News Intelligence Report: <Topic/Sector>

## 📌 Trending Cluster: <Cluster Topic>
- **Entities Involved**: <Company 1>, <Company 2>
- **Core Event**: <M&A / Product Launch / etc.>

## ⚖️ Sentiment & Impact Assessment
- **Sentiment**: <Bullish/Neutral/Bearish>
- **Primary Impact**: <Ticker> (<Positive/Negative>)
- **Sector Impact**: <Sector>
- **Time Horizon**: <Short/Medium/Long-Term>

## ⚠️ Risk & Regulatory Radar
- **Detected Risks**: <None / Describe risk>
- **Severity**: <Low/Medium/High>

## 🤖 AI Final Insight
<2-3 sentences summarizing the structural shift or immediate trading implication>

Breaking News Alert

For high-severity or high-impact events:

# 🚨 BREAKING NEWS ALERT

**Headline**: <Summary of the breaking event>
**Event Type**: <e.g., Product Launch, Regulation>
**Immediate Impact Radius**: <Tickers or Sectors affected>
**Initial Sentiment Read**: <Bullish/Bearish>

API / Programmatic Interface Format

If queried programmatically by another skill, return a structural representation:

{
  "cluster_topic": "AI Chip Competition",
  "articles_processed": 12,
  "events": [{"type": "Product Launch", "company": "NVDA"}],
  "sentiment": {"score": 0.82, "label": "Bullish"},
  "market_impact": {"primary": "NVDA", "sector": "Semiconductors", "horizon": "Long-Term"},
  "risks": []
}