Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing.
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方法一:命令行安装(推荐)
推荐(无需提前安装 clawhub)
npx clawhub@latest --dir ~/.claude/skills install us-market-bubble-detector或使用 clawhub CLI(需提前安装)
clawhub --dir ~/.claude/skills install us-market-bubble-detector⚠️ 需要 Node.js 18+,没有 Node?请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二:手动下载安装(无需 Node)
下载 ZIP,解压后将文件夹放到以下路径,重启 Agent 即可:
安装路径
~/.claude/skills/us-market-bubble-detector/💡解压后将文件夹放到上方路径,重启 Agent 即可生效
--- name: us-market-bubble-detector description: Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing. ---
Critical Changes from v2.0:
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Use this skill when:
English:
Japanese:
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CRITICAL: Always collect the following data before starting evaluation
□ Put/Call Ratio (CBOE Equity P/C)
- Source: CBOE DataShop or web_search "CBOE put call ratio"
- Collect: 5-day moving average
□ VIX (Fear Index)
- Source: Yahoo Finance ^VIX or web_search "VIX current"
- Collect: Current value + percentile over past 3 months
□ Volatility Indicators
- 21-day realized volatility
- Historical position of VIX (determine if in bottom 10th percentile)
□ FINRA Margin Debt Balance
- Source: web_search "FINRA margin debt latest"
- Collect: Latest month + Year-over-Year % change
□ Breadth (Market Participation)
- % of S&P 500 stocks above 50-day MA
- Source: web_search "S&P 500 breadth 50 day moving average"
□ IPO Count & First-Day Performance
- Source: Renaissance Capital IPO or web_search "IPO market 2025"
- Collect: Quarterly count + median first-day return
⚠️ CRITICAL: Do NOT proceed with evaluation without Phase 1 data collection
---
Score mechanically based on collected data using the following criteria:
Scoring Criteria:
- 2 points: P/C < 0.70 (excessive optimism, call-heavy)
- 1 point: P/C 0.70-0.85 (slightly optimistic)
- 0 points: P/C > 0.85 (healthy caution)
Rationale: P/C < 0.7 is historically characteristic of bubble periods
Scoring Criteria:
- 2 points: VIX < 12 AND major index within 5% of 52-week high
- 1 point: VIX 12-15 AND near highs
- 0 points: VIX > 15 OR more than 10% from highs
Rationale: Extreme low volatility + highs indicates excessive complacency
Scoring Criteria:
- 2 points: YoY +20% or more AND all-time high
- 1 point: YoY +10-20%
- 0 points: YoY +10% or less OR negative
Rationale: Rapid leverage increase is a bubble precursor
Scoring Criteria:
- 2 points: Quarterly IPO count > 2x 5-year average AND median first-day return +20%+
- 1 point: Quarterly IPO count > 1.5x 5-year average
- 0 points: Normal levels
Rationale: Poor-quality IPO flood is characteristic of late-stage bubbles
Scoring Criteria:
- 2 points: New high AND < 45% of stocks above 50DMA (narrow leadership)
- 1 point: 45-60% above 50DMA (somewhat narrow)
- 0 points: > 60% above 50DMA (healthy breadth)
Rationale: Rally driven by few stocks is fragile
Scoring Criteria:
- 2 points: Past 3-month return exceeds 95th percentile of past 10 years
- 1 point: Past 3-month return in 85-95th percentile of past 10 years
- 0 points: Below 85th percentile
Rationale: Rapid price acceleration is unsustainable
---
Limit: +3 points maximum (REDUCED from +5 in v2.0)
⚠️ CONFIRMATION BIAS PREVENTION CHECKLIST:
Before adding ANY qualitative points:
□ Do I have concrete, measurable data? (not impressions)
□ Would an independent observer reach the same conclusion?
□ Am I avoiding double-counting with Phase 2 scores?
□ Have I documented specific evidence with sources?
+1 point: ALL THREE criteria must be met:
✓ Direct user report of non-investor recommendations
✓ Specific examples with names/dates/conversations
✓ Multiple independent sources (minimum 3)
+0 points: Any criteria missing
⚠️ INVALID EXAMPLES:
- "AI narrative is prevalent" (unmeasurable)
- "I saw articles about retail investors" (not direct report)
- "Everyone is talking about stocks" (vague, unverified)
✅ VALID EXAMPLE:
"My barber asked about NVDA (Nov 1), dentist mentioned AI stocks (Nov 2),
Uber driver discussed crypto (Nov 3)"
+1 point: BOTH criteria must be met:
✓ Google Trends showing 5x+ YoY increase (measured)
✓ Mainstream coverage confirmed (Time covers, TV specials with dates)
+0 points: Search trends <5x OR no mainstream coverage
⚠️ CRITICAL: "Elevated narrative" without data = +0 points
HOW TO VERIFY:
1. Search "[topic] Google Trends 2025" and document numbers
2. Search "[topic] Time magazine cover" for specific dates
3. Search "[topic] CNBC special" for episode confirmation
✅ VALID EXAMPLE:
"Google Trends: 'AI stocks' at 780 (baseline 150 = 5.2x).
Time cover 'AI Revolution' (Oct 15, 2025).
CNBC 'AI Investment Special' (3 episodes Oct 2025)."
⚠️ INVALID EXAMPLE:
"AI/technology narrative seems elevated" (unmeasurable)
+1 point: ALL criteria must be met:
✓ P/E >25 (if NOT already counted in Phase 2 quantitative)
✓ Fundamentals explicitly ignored in mainstream discourse
✓ "This time is different" documented in major media
+0 points: P/E <25 OR fundamentals support valuations
⚠️ SELF-CHECK QUESTIONS (if ANY is YES, score = 0):
- Is P/E already in Phase 2 quantitative scoring?
- Do companies have real earnings supporting valuations?
- Is the narrative backed by fundamental improvements?
✅ VALID EXAMPLE for +1:
"S&P P/E = 35x (vs historical 18x).
CNBC article: 'Earnings don't matter in AI era' (Oct 2025).
Bloomberg: 'Traditional metrics obsolete' (Nov 2025)."
⚠️ INVALID EXAMPLE:
"P/E 30.8 but companies have real earnings and AI has fundamental backing"
(fundamentals support = +0 points)
Phase 3 Total: Maximum +3 points
---
Final Score = Phase 2 Total (0-12 points) + Phase 3 Adjustment (0 to +3 points)
Range: 0 to 15 points
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将技能文件夹放到 ~/.claude/skills/us-market-bubble-detector/ 目录(个人级,所有项目可用),或 .claude/skills/us-market-bubble-detector/(项目级)。重启 AI 客户端后,用 /us-market-bubble-detector 主动调用,或让 AI 根据上下文自动发现并使用。
Us Market Bubble Detector 支持 Claude、Cursor、OpenClaw,可与这些 AI 平台无缝集成,扩展其能力。
Us Market Bubble Detector 可免费安装使用。请查阅仓库了解许可证信息。
Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing.
Automate my finance & investment tasks using Us Market Bubble Detector
Identifies repetitive steps in your workflow and sets up Us Market Bubble Detector to handle them automatically
Us Market Bubble Detector 属于「Finance & Investment」分类,该分类的技能帮助 AI 智能体在此领域执行专业任务。