stanley-druckenmiller-investment by tradermonty/claude-trading-skills
npx skills add https://github.com/tradermonty/claude-trading-skills --skill stanley-druckenmiller-investment将来自 8 个上游分析技能(5 个必需 + 3 个可选)的输出合成为一个综合信念分数(0-100),将市场分类为 4 种 Druckenmiller 模式之一,并生成可操作的配置建议。这是一个元技能,它使用来自其他技能的结构化 JSON 输出——它本身不需要任何 API 密钥。
英文:
日文:
---|---|---|---
1 | Market Breadth Analyzer | market_breadth_ | 市场参与广度
2 | Uptrend Analyzer | uptrend_analysis_ | 板块上升趋势比率
3 | Market Top Detector | market_top_ | 派发 / 顶部风险(防御)
4 | Macro Regime Detector | | 宏观体制转换(1-2年结构)
5 | FTD Detector | | 底部确认 / 重新入场(进攻)
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macro_regime_ftd_detector_---|---|---|---
6 | VCP Screener | vcp_screener_ | 动量股形态(VCP)
7 | Theme Detector | theme_detector_ | 主题 / 板块动量
8 | CANSLIM Screener | canslim_screener_ | 成长股形态 + M(市场方向)
首先运行必需技能。综合器从 reports/ 目录读取它们的 JSON 输出。
检查 reports/ 目录中是否存在 5 个必需技能的 JSON 报告,并且是最近生成的(< 72 小时)。如果缺少任何报告,请先运行相应的技能。
python3 skills/stanley-druckenmiller-investment/scripts/strategy_synthesizer.py \
--reports-dir reports/ \
--output-dir reports/ \
--max-age 72
脚本将:
呈现生成的 Markdown 报告,突出显示:
加载适当的参考文档以提供哲学背景:
references/case-studies.md 中的相关案例研究---|---|---|---|---
1 | 市场结构 | 18% | Breadth + Uptrend | 市场参与健康状况
2 | 派发风险 | 18% | Market Top(反向) | 机构抛售风险
3 | 底部确认 | 12% | FTD Detector | 回调后的重新入场信号
4 | 宏观一致性 | 18% | Macro Regime | 体制有利程度
5 | 主题质量 | 12% | Theme Detector | 板块动量健康状况
6 | 形态可用性 | 10% | VCP + CANSLIM | 优质股票形态
7 | 信号收敛 | 12% | 所有 5 个必需技能 | 跨技能一致性
| 模式 | 触发条件 | Druckenmiller 原则 |
|---|---|---|
| 政策转向预期 | 过渡性体制 + 高转换概率 | "关注中央银行和流动性" |
| 不可持续的扭曲 | 顶部风险 >= 60 + 收缩/通胀体制 | "犯错时的损失大小最重要" |
| 极端情绪逆向 | FTD 确认 + 高顶部风险 + 看跌广度 | "大部分钱是在熊市中赚的" |
| 等待与观察 | 低信念 + 混合信号(默认) | "看不到机会时,不要挥棒" |
| 分数 | 区域 | 风险敞口 | 指导 |
|---|---|---|---|
| 80-100 | 最大信念 | 90-100% | 甜点球 - 全力出击 |
| 60-79 | 高信念 | 70-90% | 标准风险管理 |
| 40-59 | 中等信念 | 50-70% | 减小仓位规模 |
| 20-39 | 低信念 | 20-50% | 保全资本,最小风险 |
| 0-19 | 资本保全 | 0-20% | 最大防御 |
druckenmiller_strategy_YYYY-MM-DD_HHMMSS.json — 结构化分析数据druckenmiller_strategy_YYYY-MM-DD_HHMMSS.md — 人类可读报告无。 此技能读取其他技能的 JSON 输出。无需 API 密钥。
references/investment-philosophy.mdreferences/market-analysis-guide.mdreferences/case-studies.mdreferences/conviction_matrix.mdinvestment-philosophy.md 以理解框架market-analysis-guide.md + conviction_matrix.mdcase-studies.md| 技能 | 关系 | 时间视野 |
|---|---|---|
| Market Breadth Analyzer | 输入(必需) | 当前快照 |
| Uptrend Analyzer | 输入(必需) | 当前快照 |
| Market Top Detector | 输入(必需) | 2-8 周战术性 |
| Macro Regime Detector | 输入(必需) | 1-2 年结构性 |
| FTD Detector | 输入(必需) | 天-周事件性 |
| VCP Screener | 输入(可选) | 形态特定 |
| Theme Detector | 输入(可选) | 周-月主题性 |
| CANSLIM Screener | 输入(可选) | 形态特定 |
| 此技能 | 综合器 | 统一信念 |
每周安装次数
138
代码仓库
GitHub 星标数
398
首次出现
Jan 26, 2026
安全审计
安装于
gemini-cli129
opencode129
cursor129
codex127
github-copilot125
amp125
Synthesize outputs from 8 upstream analysis skills (5 required + 3 optional) into a single composite conviction score (0-100), classify the market into one of 4 Druckenmiller patterns, and generate actionable allocation recommendations. This is a meta-skill that consumes structured JSON outputs from other skills — it requires no API keys of its own.
English:
Japanese:
---|---|---|---
1 | Market Breadth Analyzer | market_breadth_ | Market participation breadth
2 | Uptrend Analyzer | uptrend_analysis_ | Sector uptrend ratios
3 | Market Top Detector | market_top_ | Distribution / top risk (defense)
4 | Macro Regime Detector | macro_regime_ | Macro regime transition (1-2Y structure)
5 | FTD Detector | ftd_detector_ | Bottom confirmation / re-entry (offense)
---|---|---|---
6 | VCP Screener | vcp_screener_ | Momentum stock setups (VCP)
7 | Theme Detector | theme_detector_ | Theme / sector momentum
8 | CANSLIM Screener | canslim_screener_ | Growth stock setups + M(Market Direction)
Run the required skills first. The synthesizer reads their JSON output from reports/.
Check that the 5 required skill JSON reports exist in reports/ and are recent (< 72 hours). If any are missing, run the corresponding skill first.
python3 skills/stanley-druckenmiller-investment/scripts/strategy_synthesizer.py \
--reports-dir reports/ \
--output-dir reports/ \
--max-age 72
The script will:
Present the generated Markdown report, highlighting:
Load appropriate reference documents to provide philosophical context:
references/case-studies.md---|---|---|---|---
1 | Market Structure | 18% | Breadth + Uptrend | Market participation health
2 | Distribution Risk | 18% | Market Top (inverted) | Institutional selling risk
3 | Bottom Confirmation | 12% | FTD Detector | Re-entry signal after correction
4 | Macro Alignment | 18% | Macro Regime | Regime favorability
5 | Theme Quality | 12% | Theme Detector | Sector momentum health
6 | Setup Availability | 10% | VCP + CANSLIM | Quality stock setups
7 | Signal Convergence | 12% | All 5 required | Cross-skill agreement
| Pattern | Trigger Conditions | Druckenmiller Principle |
|---|---|---|
| Policy Pivot Anticipation | Transitional regime + high transition probability | "Focus on central banks and liquidity" |
| Unsustainable Distortion | Top risk >= 60 + contraction/inflationary regime | "How much you lose when wrong matters most" |
| Extreme Sentiment Contrarian | FTD confirmed + high top risk + bearish breadth | "Most money made in bear markets" |
| Wait & Observe | Low conviction + mixed signals (default) | "When you don't see it, don't swing" |
| Score | Zone | Exposure | Guidance |
|---|---|---|---|
| 80-100 | Maximum Conviction | 90-100% | Fat pitch - swing hard |
| 60-79 | High Conviction | 70-90% | Standard risk management |
| 40-59 | Moderate Conviction | 50-70% | Reduce position sizes |
| 20-39 | Low Conviction | 20-50% | Preserve capital, minimal risk |
| 0-19 | Capital Preservation | 0-20% | Maximum defense |
druckenmiller_strategy_YYYY-MM-DD_HHMMSS.json — Structured analysis datadruckenmiller_strategy_YYYY-MM-DD_HHMMSS.md — Human-readable reportNone. This skill reads JSON outputs from other skills. No API keys required.
references/investment-philosophy.mdreferences/market-analysis-guide.mdreferences/case-studies.mdreferences/conviction_matrix.mdinvestment-philosophy.md for framework understandingmarket-analysis-guide.md + conviction_matrix.mdcase-studies.md| Skill | Relationship | Time Horizon |
|---|---|---|
| Market Breadth Analyzer | Input (required) | Current snapshot |
| Uptrend Analyzer | Input (required) | Current snapshot |
| Market Top Detector | Input (required) | 2-8 weeks tactical |
| Macro Regime Detector | Input (required) | 1-2 years structural |
| FTD Detector | Input (required) | Days-weeks event |
| VCP Screener | Input (optional) | Setup-specific |
| Theme Detector | Input (optional) | Weeks-months thematic |
| CANSLIM Screener | Input (optional) | Setup-specific |
| This Skill | Synthesizer |
Weekly Installs
138
Repository
GitHub Stars
398
First Seen
Jan 26, 2026
Security Audits
Gen Agent Trust HubPassSocketPassSnykPass
Installed on
gemini-cli129
opencode129
cursor129
codex127
github-copilot125
amp125
Excel财务建模规范与xlsx文件处理指南:专业格式、零错误公式与数据分析
46,700 周安装
| Unified conviction |