
Worldmonitor Intelligence Dashboard
- 1.4k installs
- 66 repo stars
- Updated July 9, 2026
- aradotso/trending-skills
World Monitor Intelligence Dashboard is an agent skill for setting up and customizing a real-time global intelligence dashboard with news feeds, maps, AI synthesis, and finance radar.
About
World Monitor Intelligence Dashboard is an agent skill for building and self-hosting a real-time global intelligence dashboard from the worldmonitor TypeScript and Vite codebase. It aggregates 435 plus feeds across 15 categories, renders a dual map engine with a 3D globe.gl view and a deck.gl plus MapLibre flat map supporting 45 data layers, scores geopolitical risk across 12 signal categories per country, and tracks finance radar data from 92 exchanges. AI synthesis runs through local Ollama by default or optional Groq and OpenRouter keys, while cross-stream signal correlation detects convergence across military, economic, disaster, and escalation feeds. The project ships web, PWA, and Tauri 2 desktop targets, Vercel edge functions for feed APIs, optional Upstash Redis caching, and site variants such as tech, finance, commodity, and happy. Developers clone the repo, run npm install and npm run dev, configure .env.local for AI and map keys, register custom feeds and deck.gl layers, and deploy via Docker, Vercel, or desktop builds with troubleshooting for maps, Ollama, Redis 429s, and RTL languages.
- 435 plus feeds across 15 categories with AI synthesis and signal correlation
- Dual map engine: 3D globe.gl and deck.gl plus MapLibre with 45 data layers
- Country intelligence index with 12-signal composite risk scoring per country
- Finance radar covering 92 exchanges plus crypto and commodity composites
- Deploy as web, PWA, Tauri desktop, Docker, or Vercel with optional Redis cache
Worldmonitor Intelligence Dashboard by the numbers
- 1,380 all-time installs (skills.sh)
- +12 installs in the week ending Jul 28, 2026 (Skillselion tracking)
- Ranked #299 of 2,277 Frontend Development skills by installs in the Skillselion catalog
- Security screen: HIGH risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
worldmonitor-intelligence-dashboard capabilities & compatibility
- Capabilities
- clone and run the worldmonitor vite app with npm · configure ai providers from ollama through groq · render globe.gl 3d and deck.gl flat maps with ri · subscribe to country intelligence scores and cro · register custom feeds and deck.gl layers plus si
What worldmonitor-intelligence-dashboard says it does
No environment variables required for basic operation. All features work with local Ollama by default.
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| Installs | 1.4k |
|---|---|
| repo stars | ★ 66 |
| Security audit | 0 / 3 scanners passed |
| Last updated | July 9, 2026 |
| Repository | aradotso/trending-skills ↗ |
How do you integrate a production-grade geopolitical and finance monitoring dashboard with feeds, maps, risk scoring, and local or cloud AI without rebuilding the stack from scratch?
Set up, customize, and deploy the World Monitor real-time global intelligence dashboard with feeds, maps, AI synthesis, and finance radar.
Who is it for?
Developers building situational awareness, OSINT, or finance monitoring surfaces who want the worldmonitor TypeScript codebase with maps, feeds, and AI synthesis pipelines.
Skip if: Skip when you only need a simple static news reader without maps, risk scoring, or the worldmonitor repository layout.
When should I use this skill?
Use when setting up worldmonitor, adding geopolitical monitoring, integrating news feeds, building a situational awareness dashboard, or self-hosting worldmonitor with custom layers.
What you get
A running World Monitor instance with configured feeds, map layers, AI provider, optional Redis cache, and a deployable web, PWA, or desktop build for your chosen site variant.
- Running World Monitor dev or production build for a chosen site variant
- Configured feeds, map layers, and AI synthesis provider
- Deployment artifacts for web, Docker, Vercel, or desktop targets
By the numbers
- 435 plus feeds across 15 categories with 45 map data layers
- 92 exchange finance radar with 12-signal country risk composites and 21 supported languages
Files
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:5173No 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 variantProduction 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 scoreCross-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/tagsVerify 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
Related skills
How it compares
Choose worldmonitor-intelligence-dashboard for geospatial OSINT dashboards rather than generic BI chart integrations.
FAQ
What do I need to run World Monitor locally?
Clone the worldmonitor repository, run npm install and npm run dev to open localhost:5173; basic features work with local Ollama and no API keys required.
Which environment variables are optional versus recommended?
Ollama runs with no keys by default; optional VITE_GROQ_API_KEY, VITE_OPENROUTER_API_KEY, VITE_MAPTILER_API_KEY, and UPSTASH_REDIS_REST credentials improve AI, maps, and feed caching performance.
How can I deploy or extend the dashboard?
Use npm run build or build:full for variants, vercel --prod for edge APIs, Docker or docker compose for self-hosting, npm run tauri:build for desktop, and FeedRegistry or LayerRegistry for custom feeds and deck.gl layers.
Is Worldmonitor Intelligence Dashboard safe to install?
skills.sh reports 0 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.