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Global Finance Radar
作者
ai-gaoqian
· GitHub ↗
· v1.0.0
· MIT-0
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在 OpenClaw 中安装
/install global-finance-radar
功能描述
Provides real-time global financial data analysis including central bank policies, macro indicators, market trends, valuations, and risk metrics with source...
使用说明 (SKILL.md)
Global Finance Radar
Capabilities
| # | Capability | Input | Output |
|---|---|---|---|
| 1 | Central Bank Policy Monitor | Bank(s) + time horizon | Current rate, forward guidance, dot-plot/rate-path, meeting calendar, market-implied probabilities |
| 2 | Macroeconomic Dashboard | Country(ies) + indicators | GDP growth, CPI, unemployment, PMI, trade balance, debt/GDP, FX reserves — with trend arrows |
| 3 | Cross-Asset Market Brief | Asset class(es) + region | Price action, YTD performance, volatility, fund flows, positioning, key catalysts |
| 4 | Yield Curve & Recession Signal | Country | 2s10s spread, 3m10y spread, near-term forward spread, historical recession lead time, probability estimate |
| 5 | Currency Fair-Value Analysis | Currency pair | PPP estimate, REER deviation, Big Mac Index, FEER, carry-to-risk ratio, positioning (CFTC COT) |
| 6 | Equity Valuation Scanner | Index / sector / stock | PE (trailing/forward), EV/EBITDA, PEG, dividend yield, vs. 5Y avg, vs. peers, DuPont decomposition |
| 7 | Commodity Supply-Demand Outlook | Commodity | Inventory levels, production forecasts, demand drivers, cost curve, geopolitical risk overlay |
| 8 | Crypto Market Intelligence | Token / sector | On-chain metrics (active addresses, TVL, hash rate), regulatory developments, institutional flow, correlation to risk assets |
| 9 | Fixed Income Relative Value | Bond / maturity range | Yield, duration, convexity, OAS (credit), breakeven inflation (TIPS), cross-market spread |
| 10 | Global Risk Matrix | Time horizon | VIX/VSTOXX, CDS spreads, EMBI spread, financial conditions indices, geopolitical risk index, tail-risk scenario |
Workflow
User Query
│
├─ [Step 1] Classify query → asset class(es) + geography + time horizon + analysis type
│
├─ [Step 2] Source selection:
│ └─ Macro: IMF, World Bank, OECD, Trading Economics
│ └─ Central banks: Fed (FRED), ECB (SDW), BIS
│ └─ Markets: Investing.com, Yahoo Finance, CoinGecko
│ └─ Commodities: WGC, OPEC MOMR
│
├─ [Step 3] Data retrieval + cross-validation (≥2 sources for key metrics)
│
├─ [Step 4] Apply relevant framework (DCF, DuPont, PPP, yield curve model)
│
├─ [Step 5] Generate structured output with data vintage, source URLs
│
└─ [Step 6] Risk disclosure: flag data gaps, model limitations, non-investment-advice disclaimer
Output Formats
Central Bank Policy Snapshot
| Bank | Current Rate | Last Change | Next Meeting | Market-Implied Path | Hawkish/Dovish Bias |
|---|---|---|---|---|---|
| Fed | X.XX% | ±XXbp (Date) | Date | CME FedWatch probabilities | ... |
| ECB | X.XX% | ... | ... | ... | ... |
Macro Dashboard
| Indicator | US | EU | CN | JP | IN | Trend |
|---|---|---|---|---|---|---|
| GDP Growth (YoY%) | ↑↓→ | |||||
| CPI (YoY%) | ||||||
| Unemployment (%) | ||||||
| Mfg PMI | ||||||
| 10Y Yield (%) |
Currency Fair-Value Table
| Pair | Spot | PPP Fair Value | Misvaluation % | REER Deviation | Carry (1Y) | Signal |
|---|---|---|---|---|---|---|
| EUR/USD | Over/Under/Fair |
Usage Guidelines
- Always cite data vintage — stale data misleads; flag any indicator >30 days old
- Cross-validate — use ≥2 sources for critical metrics (GDP, CPI, rates)
- Model transparency — disclose methodology (e.g., "PPP based on OECD 2020 benchmark, extrapolated with CPI differentials")
- Non-investment-advice disclaimer — mandatory on all outputs involving price forecasts or valuation signals
- Multi-language — search and summarize across English, Chinese, Japanese, German, French, Spanish
- Forward-looking statements — clearly distinguish between historical data, consensus forecasts, and model-generated projections
Examples
Example 1: Central Bank Divergence
User: "Compare Fed vs ECB vs BoJ policy outlook for H2 2026" Output: Rate path table with market-implied probabilities; divergence chart narrative; FX implications (EUR/USD, USD/JPY).
Example 2: Recession Check
User: "What's the recession probability for the US right now?" Output: Yield curve spreads (2s10s, 3m10y, near-term forward), Sahm Rule indicator, LEI trend, consensus probability from surveys, historical context.
Example 3: Commodity Outlook
User: "Gold price outlook for next 6 months" Output: Real yield correlation, central bank buying trends, ETF flows, technical levels, geopolitical risk premium, consensus range.
Data Base: references/finance_sources.json — 12 data sources, 8 central banks, 9 economic indicators, 5 asset classes, 6 valuation frameworks.
Last Updated: June 2026
Free Tier: Available. This skill aggregates public financial data; no proprietary terminal data accessed.
（内容由AI生成，仅供参考）
安全使用建议
Before installing, understand that this skill may browse and summarize public financial sources, including non-English sources, and may produce forecasts or valuation signals. Ask it to cite source dates, disclose assumptions, and limit languages or regions if needed; do not rely on it as personalized investment, tax, legal, or trading advice.
能力标签
能力评估
Purpose & Capability
The stated purpose is broad financial research across macro, markets, FX, commodities, crypto, valuation, and risk metrics; those capabilities match the skill name and reference source list, but users should treat outputs as research rather than personalized investment advice.
Instruction Scope
The instructions disclose data vintage, cross-validation, methodology transparency, and non-investment-advice disclaimers, but they do not define strong refusal boundaries for personalized trading, regulated advice, or insufficient-context requests.
Install Mechanism
The package contains only SKILL.md and a JSON reference file; there are no executable scripts, declared dependencies, package installs, or install-time commands.
Credentials
External data retrieval from public financial sources is proportionate to a global finance research skill and is explicitly described in the workflow and reference database.
Persistence & Privilege
No artifact requests credentials, local profile/session access, background execution, persistent storage, privilege escalation, trading authority, or mutation of user accounts or financial data.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install global-finance-radar - 安装完成后，直接呼叫该 Skill 的名称或使用
/global-finance-radar触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Global-finance-radar v1.0.0 – Initial Release
- Launches a multi-asset financial analysis toolkit with 10 core capabilities, including central bank policy, macroeconomic dashboards, equity/FX/commodity/crypto insights, and global risk monitoring.
- Provides standardized output templates for easy comparison and clarity across asset classes and regions.
- Implements a transparent workflow: query classification, multi-source data retrieval and cross-validation, financial model application, structured reporting, and mandatory risk disclosure.
- Supports usage guidelines emphasizing data freshness, methodology transparency, and multi-language data handling.
- Includes practical examples for common financial queries and outlines referenced data sources.
- Free tier available; aggregates public financial data only.
元数据
常见问题
Global Finance Radar 是什么？
Provides real-time global financial data analysis including central bank policies, macro indicators, market trends, valuations, and risk metrics with source... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 43 次。
如何安装 Global Finance Radar？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install global-finance-radar」即可一键安装，无需额外配置。
Global Finance Radar 是免费的吗？
是的，Global Finance Radar 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Global Finance Radar 支持哪些平台？
Global Finance Radar 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Global Finance Radar？
由 ai-gaoqian（@ai-gaoqian）开发并维护，当前版本 v1.0.0。
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