worldmonitor-intelligence-dashboard

Q: How do I install worldmonitor-intelligence-dashboard?

Run npx skills add https://github.com/reason-machines/trending-skills --skill worldmonitor-intelligence-dashboard in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/worldmonitor-intelligence-dashboard/ (personal) or .claude/skills/worldmonitor-intelligence-dashboard/ (project).

by reason-machinesData & Databases

Real-time global intelligence dashboard with AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking

Installs: 1.4K
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/reason-machines/trending-skills --skill worldmonitor-intelligence-dashboard

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads worldmonitor-intelligence-dashboard automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

World Monitor Intelligence Dashboard

Skill by ara.so — Daily 2026 Skills collection.

World Monitor is a real-time global intelligence dashboard combining AI-powered news aggregation (435+ feeds, 15 categories), dual map engine (3D globe + WebGL flat map with 45 data layers), geopolitical risk scoring, finance radar (92 exchanges), and cross-stream signal correlation — all from a single TypeScript/Vite codebase deployable as web, PWA, or native desktop (Tauri 2).

Installation & Quick Start

git clone https://github.com/koala73/worldmonitor.git
cd worldmonitor
npm install
npm run dev          # Opens http://localhost:5173

No environment variables required for basic operation. All features work with local Ollama by default.

Site Variants

npm run dev:tech       # tech.worldmonitor.app variant
npm run dev:finance    # finance.worldmonitor.app variant
npm run dev:commodity  # commodity.worldmonitor.app variant
npm run dev:happy      # happy.worldmonitor.app variant

Production Build

npm run typecheck        # TypeScript validation
npm run build:full       # Build all variants
npm run build            # Build default (world) variant

Project Structure

worldmonitor/
├── src/
│   ├── components/       # UI components (TypeScript)
│   ├── feeds/            # 435+ RSS/API feed definitions
│   ├── layers/           # Map data layers (deck.gl)
│   ├── ai/               # AI synthesis pipeline
│   ├── signals/          # Cross-stream correlation engine
│   ├── finance/          # Market data (92 exchanges)
│   ├── variants/         # Site variant configs (world/tech/finance/commodity/happy)
│   └── protos/           # Protocol Buffer definitions (92 protos, 22 services)
├── api/                  # Vercel Edge Functions (60+)
├── src-tauri/            # Tauri 2 desktop app (Rust)
├── docs/                 # Documentation source
└── vite.config.ts

Environment Variables

Create a .env.local file (never commit secrets):

# AI Providers (all optional — Ollama works with no keys)
VITE_OLLAMA_BASE_URL=http://localhost:11434       # Local Ollama instance
VITE_GROQ_API_KEY=$GROQ_API_KEY                  # Groq cloud inference
VITE_OPENROUTER_API_KEY=$OPENROUTER_API_KEY      # OpenRouter multi-model

# Caching (optional, improves performance)
UPSTASH_REDIS_REST_URL=$UPSTASH_REDIS_REST_URL
UPSTASH_REDIS_REST_TOKEN=$UPSTASH_REDIS_REST_TOKEN

# Map tiles (optional, MapLibre GL)
VITE_MAPTILER_API_KEY=$MAPTILER_API_KEY

# Variant selection
VITE_SITE_VARIANT=world   # world | tech | finance | commodity | happy

Core Concepts

Feed Categories

World Monitor aggregates 435+ feeds across 15 categories:

// src/feeds/categories.ts pattern
import type { FeedCategory } from './types';

const FEED_CATEGORIES: FeedCategory[] = [
  'geopolitics',
  'military',
  'economics',
  'technology',
  'climate',
  'energy',
  'health',
  'finance',
  'commodities',
  'infrastructure',
  'cyber',
  'space',
  'diplomacy',
  'disasters',
  'society',
];

Country Intelligence Index

Composite risk scoring across 12 signal categories per country:

// Example: accessing country risk scores
import { CountryIntelligence } from './signals/country-intelligence';

const intel = new CountryIntelligence();

// Get composite risk score for a country
const score = await intel.getCountryScore('UA');
console.log(score);
// {
//   composite: 0.82,
//   signals: {
//     military: 0.91,
//     economic: 0.74,
//     political: 0.88,
//     humanitarian: 0.79,
//     ...
//   },
//   trend: 'escalating',
//   updatedAt: '2026-03-17T08:00:00Z'
// }

// Subscribe to real-time updates
intel.subscribe('UA', (update) => {
  console.log('Risk update:', update);
});

AI Synthesis Pipeline

// src/ai/synthesize.ts pattern
import { AISynthesizer } from './ai/synthesizer';

const synth = new AISynthesizer({
  provider: 'ollama',           // 'ollama' | 'groq' | 'openrouter'
  model: 'llama3.2',            // any Ollama-compatible model
  baseUrl: process.env.VITE_OLLAMA_BASE_URL,
});

// Synthesize a news brief from multiple feed items
const brief = await synth.synthesize({
  items: feedItems,             // FeedItem[]
  category: 'geopolitics',
  region: 'Europe',
  maxTokens: 500,
  language: 'en',
});

console.log(brief.summary);    // AI-generated synthesis
console.log(brief.signals);    // Extracted signals array
console.log(brief.confidence); // 0-1 confidence score

Cross-Stream Signal Correlation

// src/signals/correlator.ts pattern
import { SignalCorrelator } from './signals/correlator';

const correlator = new SignalCorrelator();

// Detect convergence across military, economic, disaster signals
const convergence = await correlator.detectConvergence({
  streams: ['military', 'economic', 'disaster', 'escalation'],
  timeWindow: '6h',
  threshold: 0.7,
  region: 'Middle East',
});

if (convergence.detected) {
  console.log('Convergence signals:', convergence.signals);
  console.log('Escalation probability:', convergence.probability);
  console.log('Contributing events:', convergence.events);
}

Map Engine Integration

3D Globe (globe.gl)

// src/components/globe/GlobeView.ts
import Globe from 'globe.gl';
import { getCountryRiskData } from '../signals/country-intelligence';

export function initGlobe(container: HTMLElement) {
  const globe = Globe()(container)
    .globeImageUrl('//unpkg.com/three-globe/example/img/earth-dark.jpg')
    .backgroundImageUrl('//unpkg.com/three-globe/example/img/night-sky.png');

  // Load country risk layer
  const riskData = await getCountryRiskData();

  globe
    .polygonsData(riskData.features)
    .polygonCapColor(feat => riskToColor(feat.properties.riskScore))
    .polygonSideColor(() => 'rgba(0, 100, 0, 0.15)')
    .polygonLabel(({ properties: d }) =>
      `<b>${d.name}</b><br/>Risk: ${(d.riskScore * 100).toFixed(0)}%`
    );

  return globe;
}

function riskToColor(score: number): string {
  if (score > 0.8) return 'rgba(220, 38, 38, 0.8)';   // critical
  if (score > 0.6) return 'rgba(234, 88, 12, 0.7)';   // high
  if (score > 0.4) return 'rgba(202, 138, 4, 0.6)';   // elevated
  if (score > 0.2) return 'rgba(22, 163, 74, 0.5)';   // low
  return 'rgba(15, 118, 110, 0.4)';                    // minimal
}

WebGL Flat Map (deck.gl + MapLibre GL)

// src/components/map/DeckMap.ts
import { Deck } from '@deck.gl/core';
import { ScatterplotLayer, ArcLayer, HeatmapLayer } from '@deck.gl/layers';
import maplibregl from 'maplibre-gl';

export function initDeckMap(container: HTMLElement) {
  const map = new maplibregl.Map({
    container,
    style: 'https://basemaps.cartocdn.com/gl/dark-matter-gl-style/style.json',
    center: [0, 20],
    zoom: 2,
  });

  const deck = new Deck({
    canvas: 'deck-canvas',
    initialViewState: { longitude: 0, latitude: 20, zoom: 2 },
    controller: true,
    layers: [
      // Event scatter layer
      new ScatterplotLayer({
        id: 'events',
        data: getActiveEvents(),
        getPosition: d => [d.lng, d.lat],
        getRadius: d => d.severity * 50000,
        getFillColor: d => severityToRGBA(d.severity),
        pickable: true,
      }),
      // Supply chain arc layer
      new ArcLayer({
        id: 'supply-chains',
        data: getSupplyChainData(),
        getSourcePosition: d => d.source,
        getTargetPosition: d => d.target,
        getSourceColor: [0, 128, 200],
        getTargetColor: [200, 0, 80],
        getWidth: 2,
      }),
    ],
  });

  return { map, deck };
}

Finance Radar

// src/finance/radar.ts pattern
import { FinanceRadar } from './finance/radar';

const radar = new FinanceRadar();

// Get market composite (7-signal)
const composite = await radar.getMarketComposite();
console.log(composite);
// {
//   score: 0.62,
//   signals: {
//     volatility: 0.71,
//     momentum: 0.58,
//     sentiment: 0.65,
//     liquidity: 0.44,
//     correlation: 0.78,
//     macro: 0.61,
//     geopolitical: 0.82
//   },
//   exchanges: 92,
//   timestamp: '2026-03-17T08:00:00Z'
// }

// Watch specific exchange
const exchange = await radar.getExchange('NYSE');
const crypto = await radar.getCrypto(['BTC', 'ETH', 'SOL']);
const commodities = await radar.getCommodities(['GOLD', 'OIL', 'WHEAT']);

Language & RTL Support

World Monitor supports 21 languages with native-language feeds:

// src/i18n/config.ts pattern
import { setLanguage, getAvailableLanguages } from './i18n';

const languages = getAvailableLanguages();
// ['en', 'ar', 'zh', 'ru', 'fr', 'es', 'de', 'ja', 'ko', 'pt',
//  'hi', 'fa', 'tr', 'pl', 'uk', 'nl', 'sv', 'he', 'it', 'vi', 'id']

// Switch language (handles RTL automatically)
await setLanguage('ar');  // Arabic — triggers RTL layout
await setLanguage('he');  // Hebrew — triggers RTL layout
await setLanguage('fa');  // Farsi — triggers RTL layout

// Configure feed language filtering
import { FeedManager } from './feeds/manager';
const feeds = new FeedManager({ language: 'ar', includeEnglish: true });

Protocol Buffers (API Contracts)

// src/protos — 92 proto definitions, 22 services
// Example generated client usage:

import { IntelligenceServiceClient } from './protos/generated/intelligence_grpc_web_pb';
import { CountryRequest } from './protos/generated/intelligence_pb';

const client = new IntelligenceServiceClient(
  process.env.VITE_API_BASE_URL || 'http://localhost:8080'
);

const request = new CountryRequest();
request.setCountryCode('DE');
request.setTimeRange('24h');
request.setSignalTypes(['military', 'economic', 'political']);

client.getCountryIntelligence(request, {}, (err, response) => {
  if (err) console.error(err);
  else console.log(response.toObject());
});

Vercel Edge Function Pattern

// api/feeds/aggregate.ts — Edge Function example
import type { VercelRequest, VercelResponse } from '@vercel/node';
import { aggregateFeeds } from '../../src/feeds/aggregator';
import { getCachedData, setCachedData } from '../../src/cache/redis';

export const config = { runtime: 'edge' };

export default async function handler(req: VercelRequest, res: VercelResponse) {
  const { category, region, limit = '20' } = req.query as Record<string, string>;

  const cacheKey = `feeds:${category}:${region}:${limit}`;
  const cached = await getCachedData(cacheKey);
  if (cached) return res.json(cached);

  const items = await aggregateFeeds({
    categories: category ? [category] : undefined,
    region,
    limit: parseInt(limit),
  });

  await setCachedData(cacheKey, items, { ttl: 300 }); // 5 min TTL
  return res.json(items);
}

Desktop App (Tauri 2)

# Install Tauri CLI
cargo install tauri-cli

# Development
npm run tauri:dev

# Build native app
npm run tauri:build
# Outputs: .exe (Windows), .dmg/.app (macOS), .AppImage (Linux)

// src-tauri/src/main.rs — IPC command example
#[tauri::command]
async fn fetch_intelligence(country: String) -> Result<CountryData, String> {
    // Sidecar Node.js process handles feed aggregation
    // Tauri handles secure IPC between renderer and backend
    Ok(CountryData::default())
}

fn main() {
    tauri::Builder::default()
        .invoke_handler(tauri::generate_handler![fetch_intelligence])
        .run(tauri::generate_context!())
        .expect("error while running tauri application");
}

Docker / Self-Hosting

# Docker single-container
docker build -t worldmonitor .
docker run -p 3000:3000 \
  -e VITE_SITE_VARIANT=world \
  -e UPSTASH_REDIS_REST_URL=$UPSTASH_REDIS_REST_URL \
  -e UPSTASH_REDIS_REST_TOKEN=$UPSTASH_REDIS_REST_TOKEN \
  worldmonitor

# Docker Compose with Redis
docker compose up -d

# docker-compose.yml
version: '3.9'
services:
  app:
    build: .
    ports: ['3000:3000']
    environment:
      - VITE_SITE_VARIANT=world
      - REDIS_URL=redis://redis:6379
    depends_on: [redis]
  redis:
    image: redis:7-alpine
    volumes: ['redis_data:/data']
volumes:
  redis_data:

Vercel Deployment

npm i -g vercel
vercel --prod
# Set env vars in Vercel dashboard or via CLI:
vercel env add GROQ_API_KEY production
vercel env add UPSTASH_REDIS_REST_URL production
vercel env add UPSTASH_REDIS_REST_TOKEN production

Common Patterns

Custom Feed Integration

// Add a custom RSS feed to the aggregation pipeline
import { FeedRegistry } from './src/feeds/registry';

FeedRegistry.register({
  id: 'my-custom-feed',
  name: 'My Intelligence Source',
  url: 'https://example.com/feed.xml',
  category: 'geopolitics',
  region: 'Asia',
  language: 'en',
  weight: 0.8,           // 0-1, affects signal weighting
  refreshInterval: 300,  // seconds
  parser: 'rss2',        // 'rss2' | 'atom' | 'json'
});

Custom Map Layer

// Register a custom deck.gl layer in the 45-layer system
import { LayerRegistry } from './src/layers/registry';
import { IconLayer } from '@deck.gl/layers';

LayerRegistry.register({
  id: 'my-custom-layer',
  name: 'Custom Events',
  category: 'infrastructure',
  defaultVisible: false,
  factory: (data) => new IconLayer({
    id: 'my-custom-layer-deck',
    data,
    getPosition: d => [d.lng, d.lat],
    getIcon: d => 'marker',
    getSize: 32,
    pickable: true,
  }),
});

Site Variant Configuration

// src/variants/my-variant.ts
import type { SiteVariant } from './types';

export const myVariant: SiteVariant = {
  id: 'my-variant',
  name: 'My Monitor',
  title: 'My Custom Monitor',
  defaultCategories: ['geopolitics', 'economics', 'military'],
  defaultRegion: 'Europe',
  defaultLanguage: 'en',
  mapStyle: 'dark',
  enabledLayers: ['country-risk', 'events', 'supply-chains'],
  aiProvider: 'ollama',
  theme: {
    primary: '#0891b2',
    background: '#0f172a',
    surface: '#1e293b',
  },
};

Troubleshooting

Problem	Solution
Map not rendering	Check `VITE_MAPTILER_API_KEY` or use free CartoBasemap style
AI synthesis slow/failing	Ensure Ollama is running: `ollama serve && ollama pull llama3.2`
Feeds returning 429 errors	Enable Redis caching via `UPSTASH_REDIS_REST_*` env vars
Desktop app won't build	Ensure Rust + `cargo install tauri-cli` + platform build tools
RTL layout broken	Confirm `lang` attribute set on `<html>` by `setLanguage()`
TypeScript errors on build	Run `npm run typecheck` — proto generated files must exist
Redis connection refused	Check `REDIS_URL` or use Upstash REST API instead of TCP
`npm run build:full` fails mid-variant	Build individually: `npm run build -- --mode finance`

Ollama Setup for Local AI

# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh

# Pull recommended model
ollama pull llama3.2          # Fast, good quality
ollama pull mistral           # Alternative
ollama pull gemma2:9b         # Larger, higher quality

# Verify Ollama is accessible
curl http://localhost:11434/api/tags

Verify Installation

npm run typecheck   # Should exit 0
npm run dev         # Should open localhost:5173
# Navigate to /api/health for API status
curl http://localhost:5173/api/health

Resources

Live App: worldmonitor.app
Documentation: docs.worldmonitor.app
Architecture: docs.worldmonitor.app/architecture
Self-Hosting Guide: docs.worldmonitor.app/getting-started
Contributing: docs.worldmonitor.app/contributing
Security Policy: SECURITY.md
License: AGPL-3.0 (non-commercial); commercial license required for SaaS/rebranding

FAQ

What does the worldmonitor-intelligence-dashboard skill do?

Real-time global intelligence dashboard with AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking

How do I install worldmonitor-intelligence-dashboard?

Run npx skills add https://github.com/reason-machines/trending-skills --skill worldmonitor-intelligence-dashboard in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/worldmonitor-intelligence-dashboard/ (personal) or .claude/skills/worldmonitor-intelligence-dashboard/ (project).

Which AI agents can use worldmonitor-intelligence-dashboard?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is worldmonitor-intelligence-dashboard safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains worldmonitor-intelligence-dashboard?

It is published by reason-machines in reason-machines/trending-skills. It has 1,422 recorded installs.

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worldmonitor-intelligence-dashboard

Install

Install

Describe the task

Review the result

SKILL.md

World Monitor Intelligence Dashboard

Installation & Quick Start

Site Variants

Production Build

Project Structure

Environment Variables

Core Concepts

Feed Categories

Country Intelligence Index

AI Synthesis Pipeline

Cross-Stream Signal Correlation

Map Engine Integration

3D Globe (globe.gl)

WebGL Flat Map (deck.gl + MapLibre GL)

Finance Radar

Language & RTL Support

Protocol Buffers (API Contracts)

Vercel Edge Function Pattern

Desktop App (Tauri 2)

Docker / Self-Hosting

Vercel Deployment

Common Patterns

Custom Feed Integration

Custom Map Layer

Site Variant Configuration

Troubleshooting

Ollama Setup for Local AI

Verify Installation

Resources

FAQ

More from reason-machines/trending-skills

Popular data & databases skills