News Impact Scale

Analyzes a news article URL to provide a personalized, data-driven impact timeline with historical benchmarks and confidence levels based on your location an...

News Impact Scale — Skill Specification

What It Does

Analyzes a news article from a URL and returns a structured prev/current/future impact analysis in plain English — tailored to you, based on your stored location, interests, and travel plans.

No opinions. Real data. Historical benchmarks. Extrapolated futures.

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Activation Triggers

Any of these will activate the skill:

• analyze news <url>
• analyze this news article <url>
• news impact <url>
• what's the impact of this news <url>
• analyze this <url>

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How It Works (3 Stages)

Stage 1 — Analyze

Triggered when you provide a URL. The skill:

1. Fetches the article
2. Classifies the event type (natural disaster, corporate, political, etc.)
3. Identifies affected geographic location and systems
4. Checks historical benchmark cache
5. Generates benchmark research queries for the agent to run
6. Produces a preliminary timeline (Medium/High confidence if benchmarks exist)

Stage 2 — Benchmark Research (Agent does this)

The agent takes the benchmark queries from Stage 1 and runs web searches to find real historical data (e.g., "how long did roads take to restore after the 2011 Japan earthquake"). Results are fed into Stage 3.

Stage 3 — Final Report

Produces the complete written analysis with:

• Prev/Current/Future timeline for each affected system
• Real historical benchmarks used as projection basis
• Confidence scores (grounded in how many comparable events exist)
• Trend direction (worsening / stable / improving)
• Plain-English explanation of what the news means for you personally

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Setup — Fill In Your Context

Before first use, edit context.json in this skill directory:

json

{
  "location": {
    "city": "Belgrade",
    "country": "Serbia",
    "coordinates": "44.7866, 20.4489"
  },
  "interests": ["technology", "finance", "energy", "geopolitics"],
  "travelPlans": [
    { "destination": "Japan", "dates": "Q4 2026" }
  ],
  "exposure": {
    "industry": "technology",
    "companies": [],
    "assets": []
  }
}

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Output Sections

📰 What the News Says

Plain-English summary as a regular person would understand it.

🌍 Why It Matters to You

• Geographic relevance — near you? same country?
• Thematic relevance — touches your interests or industry?
• Overall personal impact — High / Moderate / Low

📊 Three-State Impact Timeline

For each affected system (roads, power grid, markets, etc.):

	State	Description
Previous	What was true before	e.g., "Roads fully operational"
Current	What is true now	e.g., "Highways closed, diversions in place"
Future	What historical data suggests	e.g., "Roads restored within 18 days (based on 2011 Tōhoku benchmark)"

Each row includes:

• Trend — 🟢 Improving / 🟡 Stable / 🔴 Worsening
• Confidence — High / Medium / Low (based on number of comparable cases)
• Benchmark source — the actual historical case used

📈 Trend Direction

Overall trend across all affected systems.

🔍 Confidence & Caveats

What data was used, what the limitations are.

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Confidence Scoring

Level	When
High	3+ comparable historical events in the same location
Medium	1–2 comparable cases found
Low	No precedent — projections are general patterns, not data-driven

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File Structure

text

news-impact-scale/
├── SKILL.md              ← This file
├── analyze.js             ← Main engine (Stage 1 + Stage 3)
├── context.json           ← Your personal context (fill in)
├── benchmarks.json        ← Historical benchmark database (auto-updated)
├── stage1_output.json     ← Intermediate output from Stage 1
└── lib/
    ├── fetcher.js         ← Fetch + extract article text
    ├── classifier.js      ← Classify event type, location, systems
    ├── benchmarker.js     ← Historical data research + storage
    ├── projector.js       ← Build prev/current/future timeline
    └── explainer.js       ← Plain-English explanations

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Example Flow

text

You:    "analyze news https://example.com/article"
Agent:  (runs Stage 1) → generates benchmark queries → runs web searches → runs Stage 3
        → delivers full written report

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Notes

• Benchmarks are location-specific: Japan events benchmark against Japan history, not generic data
• Future projections are extrapolations, not guarantees — always shown with confidence
• benchmarks.json grows over time — the more you use it, the smarter it gets
• Some sites (BBC, WSJ) may block scraping — try Reuters or open-access sources if needed