usd-reserve-loss-gold-revaluation
在「美元/某貨幣失去儲備地位、黃金成為唯一錨」的假設下,用央行貨幣負債 ÷ 黃金儲備,推演「資產負債表可承受的隱含金價」,並輸出各國/各貨幣的槓桿程度、缺口與排名。
Profile →npx skills add majiayu000/claude-skill-registry --skill usd-reserve-loss-gold-revaluation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
<essential_principles> <principle name="gold_anchor_hypothesis"> **黃金錨定假說** 本模型基於極端情境假設:若法定貨幣體系瓦解、黃金成為唯一錨定資產,則: - **隱含金價** = 貨幣負債 ÷ 黃金儲備 - 這不是「預測」,而是「壓力測試」:資產負債表要撐得住需要多高的金價 典型論述來源:VanEck「$39k gold」分析(M0 + FX turnover 加權) </principle> <principle name="two_aggregates"> **兩種貨幣口徑差異** | 口徑 | 定義 | 隱含金價 | 解讀 | |------|------|----------|------| | M0 (Monetary Base) | 央行直接負債(通貨 + 準備金) | ~$39k | 央行資產負債表壓力 | | M2 (Broad Money) | 含銀行體系信用擴張 | ~$184k | 全體信用體系壓力 | **關鍵洞察**:兩者差距反映「信用乘數」的槓桿效應。 </principle> <principle name="weighting_logic"> **加權方法的直覺** | 方法 | 數據來源 | 直覺 | |------|----------|------| | fx_turnover | BIS 三年調查 | 外匯交易份額 ≈ 國際結算/儲備使用強度 | | reserve_share | IMF COFER | 官方外匯儲備幣別佔比 | | equal | - | 不考慮貨幣重要性差異 | | custom | 用戶自訂 | 可配合特定情境分析 | 加權的直覺:份額越高的貨幣,在「重新錨定」時需吸收的負債壓力越大。 </principle> <principle name="backing_ratio"> **黃金支撐率 (Backing Ratio)** ``` backing_ratio = (gold_oz × gold_spot) / money_base ``` 解讀: - backing_ratio ≈ 3% → 黃金僅支撐 3% 的貨幣負債(高槓桿) - backing_ratio ≈ 60% → 黃金接近完全支撐(低槓桿) 貼文中「日本黃金只支撐約 3% 的 M0」即此概念。 </principle> <principle name="data_access"> **資料取得方式** 本 skill 使用**公開數據**: - **黃金儲備**:World Gold Council / IMF IFS(tonnes) - **貨幣量**:各國央行 / FRED / IMF IFS(M0/M2) - **FX Turnover**:BIS T
cd skills/usd-reserve-loss-gold-revaluation pip install pandas numpy requests yfinance # 首次使用 python scripts/gold_revaluation.py --quick python scripts/gold_revaluation.py \
What does the usd-reserve-loss-gold-revaluation skill do?
在「美元/某貨幣失去儲備地位、黃金成為唯一錨」的假設下,用央行貨幣負債 ÷ 黃金儲備,推演「資產負債表可承受的隱含金價」,並輸出各國/各貨幣的槓桿程度、缺口與排名。
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill usd-reserve-loss-gold-revaluation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.