ClawHub

Global Trend Radar

Data & APIs

Monitors and analyzes global emerging trends across key sectors using multi-source data to provide structured, actionable insights and forecasts.

Install

openclaw skills install global-trend-radar

Global Trend Radar (鍏ㄧ悆瓒嬪娍闆疯揪)

Description

A comprehensive trend intelligence skill that monitors, analyzes, and synthesizes emerging global trends across technology, economics, geopolitics, climate, demographics, and innovation. Powered by multi-source web intelligence and structured trend taxonomy, it provides forward-looking analysis with actionable insights for decision-makers, researchers, and strategists worldwide.

Keywords: trends, global, forecasting, technology, innovation, market intelligence, future, megatrends, horizon scanning

Triggers

  • "what are the latest trends in [domain]"
  • "analyze global [industry/sector] trends"
  • "is [technology] trending worldwide"
  • "compare trends between [region A] and [region B]"
  • "what megatrends will shape the next [N] years"
  • "emerging technologies to watch in [year]"
  • "global market forecast for [sector]"

Capabilities

1. Trend Discovery & Monitoring

  • Execute multi-source web searches across 10+ authoritative trend data sources (Google Trends, Gartner, WIPO, WEF, OECD, McKinsey, Pew Research, arXiv, CB Insights, Statista)
  • Track 8 persistent trend categories: AI & Automation, Climate & Sustainability, Digital Transformation, Biotech & Health, Geopolitics & Economics, Future of Work, Space & Deep Tech, Global Demographics
  • Perform cross-regional trend comparison (US, EU, China, India, SE Asia, MENA, LATAM)
  • Detect early signals via patent data analysis (WIPO PatentScope) and academic preprint surges (arXiv)

2. Trend Analysis Framework

  • Hype Cycle Assessment: Map technologies to Gartner-style maturity phases (Innovation Trigger 鈫?Peak of Inflated Expectations 鈫?Trough of Disillusionment 鈫?Slope of Enlightenment 鈫?Plateau of Productivity)
  • Adoption S-Curve: Estimate current adoption phase and trajectory for any trend
  • Impact 脳 Probability Matrix: Score trends on potential impact (economic, social, environmental) vs. realization probability
  • Cross-Domain Ripple Analysis: Identify second-order effects where trends in one domain cascade into others

3. Output Formats

Always structure trend reports with:

  1. Executive Summary (3-5 bullet points)
  2. Trend Landscape (categorized table with urgency/impact scores)
  3. Deep Dives (2-3 most significant trends with evidence, data points, and timeline)
  4. Regional Comparison (heatmap table: US vs EU vs APAC)
  5. Actionable Implications (for businesses, policymakers, individuals)
  6. Monitoring Dashboard (key metrics and indicators to watch going forward)

4. Data-Driven Requirements

  • Cite at least 3 distinct sources per trend (URLs + publication dates required)
  • Include quantitative data points where available (market size, growth rate, adoption %)
  • Note conflicting viewpoints and uncertainties explicitly
  • Distinguish between consensus trends and speculative projections
  • Flag data freshness: mark sources older than 6 months as potentially stale

Workflow

User Query
    鈫?[Step 1] Identify trend category & regions from structured taxonomy
    鈫?[Step 2] Execute parallel web_search across 3-5 relevant data sources
    鈫?[Step 3] Execute web_fetch on top 2-3 most promising results for depth
    鈫?[Step 4] Cross-reference findings: compare data points, identify consensus
    鈫?[Step 5] Apply analysis frameworks (Hype Cycle, S-Curve, Impact Matrix)
    鈫?[Step 6] Generate structured report with citations, tables, and visual indicators
    鈫?Final Output: Formatted report + monitoring recommendations

Usage Guidelines

  1. Default scope: When user doesn't specify timeframe, default to 1-3 year outlook
  2. Default regions: When user doesn't specify region, cover global + regional highlights
  3. Confidence levels: Always self-assess confidence (HIGH: multiple corroborating sources, MEDIUM: 2 sources aligned, LOW: single source or speculative)
  4. Language: Match response language to user's query language; support multi-language trend searches using keyword translations from references/data_sources.json
  5. Persistence: This skill tracks long-cycle trends (5-20 year horizons); avoid chasing viral fads

Examples

Query: "What are the top AI trends shaping the next 3 years globally?"

Response Structure:

  1. Executive Summary with top 5 AI trends ranked by impact
  2. Trend Landscape table with columns: Trend | Maturity Phase | Impact Score | Adoption Velocity | Key Players
  3. Deep Dive on #1 trend: Multi-modal AI / AI Agents - market data, patent surge, key papers
  4. Regional comparison: US (foundation models, venture funding) vs EU (regulation-first, industrial AI) vs China (application layer, manufacturing AI)
  5. Actionable implications for software companies, enterprises, and regulators
  6. Metrics to watch: GPU shipments, AI patent filings, AI regulation milestones

References

  • references/data_sources.json: Complete data source catalog with URLs, coverage regions, and keyword mappings for 10 authoritative sources across 8 trend categories 锛堝唴瀹圭敱AI鐢熸垚锛屼粎渚涘弬鑰冿級
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