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stanley-druckenmiller-investment — Claude Code skill: how to install

Combines outputs from up to eight trading analysis skills into a single 0 to 100 conviction score. Helps determine portfolio exposure and market regime using Stanley Druckenmiller principles.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add tradermonty/claude-trading-skills --skill stanley-druckenmiller-investment -a claude-code
Open on GitHub

What stanley-druckenmiller-investment does

This is a meta-skill designed for portfolio decisions. It requires no API keys because it never fetches market quotes directly. Without upstream reports, the skill is useless. It runs strategy_synthesizer.py to aggregate JSON files stored in the reports/ folder. If those files are missing or older than 72 hours, execution stops immediately.

The synthesizer relies on five required skills: Market Breadth, Uptrend Analysis, Market Top Detector, Macro Regime, and FTD Detector. Three optional screeners (VCP, Theme Detector, CANSLIM) provide additional confirmation. The script weights seven components from 10% to 18%, producing a composite conviction score from 0 to 100.

Market conditions map to one of four Druckenmiller patterns, defaulting to Wait & Observe when signals conflict. The skill writes a Markdown summary and a JSON file to reports/ with target exposures for equities, bonds, alternatives, and cash.

What it helps with

  • Synthesize five upstream market reports into a single conviction score
  • Classify current market conditions into four Druckenmiller patterns
  • Determine portfolio exposure targets across equities, bonds, and cash
  • Aggregate breadth, trend, macro, and distribution signals into one Markdown report

Example prompts for the agent

  • What is my conviction level based on recent market reports?
  • Run the strategy synthesizer on the reports directory
  • How should I position my portfolio according to Druckenmiller analysis?

How to install stanley-druckenmiller-investment

1Skills CLI (Vercel)

npx skills add tradermonty/claude-trading-skills --skill stanley-druckenmiller-investment -a claude-code

2Manually: put the files in place

~/.claude/skills/stanley-druckenmiller-investment/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/stanley-druckenmiller-investment/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about stanley-druckenmiller-investment

How to install stanley-druckenmiller-investment in Claude Code?

Run the command npx skills add tradermonty/claude-trading-skills --skill stanley-druckenmiller-investment -a claude-code in your terminal.

What does stanley-druckenmiller-investment do?

It runs strategy_synthesizer.py to combine JSON data from five required and three optional trading skills. The script generates a conviction score between 0 and 100, identifies a market pattern, and suggests portfolio exposure limits.

Does stanley-druckenmiller-investment require an API key?

No API keys are required. The skill operates locally by reading upstream JSON files that must be less than 72 hours old from the reports/ directory.

Source text

SKILL.md · MIT
---
name: stanley-druckenmiller-investment
description: Druckenmiller Strategy Synthesizer - Integrates 8 upstream skill outputs (Market Breadth, Uptrend Analysis, Market Top, Macro Regime, FTD Detector, VCP Screener, Theme Detector, CANSLIM Screener) into a unified conviction score (0-100), pattern classification, and allocation recommendation. Use when user asks about overall market conviction, portfolio positioning, asset allocation, strategy synthesis, or Druckenmiller-style analysis. Triggers on queries like "What is my conviction level?", "How should I position?", "Run the strategy synthesizer", "Druckenmiller analysis", "総合的な市場判断", "確信度スコア", "ポートフォリオ配分", "ドラッケンミラー分析".
---

# Druckenmiller Strategy Synthesizer

## Purpose

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.

## When to Use This Skill

**English:**
- User asks "What's my overall conviction?" or "How should I be positioned?"
- User wants a unified view synthesizing breadth, uptrend, top risk, macro, and FTD signals
- User asks about Druckenmiller-style portfolio positioning
- User requests strategy synthesis after running individual analysis skills
- User asks "Should I increase or decrease exposure?"
- User wants pattern classification (policy pivot, distortion, contrarian, wait)

**Japanese:**
- 「総合的な市場判断は?」「今のポジショニングは?」
- ブレッドス、アップトレンド、天井リスク、マクロの統合判断
- 「エクスポージャーを増やすべき?減らすべき?」
- 「ドラッケンミラー分析を実行して」
- 個別スキル実行後の戦略統合レポート

---

## Input Requirements

### Required Skills (5)

| # | Skill | JSON Prefix | Role |
|---|-------|-------------|------|
| 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) |

### Optional Skills (3)

| # | Skill | JSON Prefix | Role |
|---|-------|-------------|------|
| 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/`.

---

## Execution Workflow

### Phase 1: Verify Prerequisites

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.

### Phase 2: Execute Strategy Synthesizer

```bash
python3 skills/stanley-druckenmiller-investment/scripts/strategy_synthesizer.py \
  --reports-dir reports/ \
  --output-dir reports/ \
  --max-age 72
```

The script will:
1. Load and validate all upstream skill JSON reports
2. Extract normalized signals from each skill
3. Calculate 7 component scores (weighted 0-100)
4. Compute composite conviction score
5. Classify into one of 4 Druckenmiller patterns
6. Generate target allocation and position sizing
7. Output JSON and Markdown reports

### Phase 3: Present Results

Present the generated Markdown report, highlighting:
- Conviction score and zone
- Detected pattern and match strength
- Strongest and weakest components
- Target allocation (equity/bonds/alternatives/cash)
- Position sizing parameters
- Relevant Druckenmiller principle

### Phase 4: Provide Druckenmiller Context

Load appropriate reference documents to provide philosophical context:
- **High conviction:** Emphasize concentration and "fat pitch" principles
- **Low conviction:** Emphasize capital preservation and patience
- **Pattern-specific:** Apply relevant case study from `references/case-studies.md`

---

## 7-Component Scoring System

| # | Component | Weight | Source Skill(s) | Key Signal |
|---|-----------|--------|----------------|------------|
| 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 |

## 4 Pattern Classifications

| 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" |

## Conviction Zone Mapping

| 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 |

---

## Output Files

- `druckenmiller_strategy_YYYY-MM-DD_HHMMSS.json` — Structured analysis data
- `druckenmiller_strategy_YYYY-MM-DD_HHMMSS.md` — Human-readable report

## API Requirements

**None.** This skill reads JSON outputs from other skills. No API keys required.

## Reference Documents

### `references/investment-philosophy.md`
- Core Druckenmiller principles: concentration, capital preservation, 18-month horizon
- Quantitative rules: daily vol targets, max position sizing
- Load when providing philosophical context for conviction assessment

### `references/market-analysis-guide.md`
- Signal-to-action mapping framework
- Macro regime interpretation for allocation decisions
- Load when explaining component scores or allocation rationale

### `references/case-studies.md`
- Historical examples: 1992 GBP, 2000 tech bubble, 2008 crisis
- Pattern classification examples with actual market conditions
- Load when user asks about historical parallels

### `references/conviction_matrix.md`
- Quantitative signal-to-action mapping tables
- Market Top Zone x Macro Regime matrix
- Load when user needs precise exposure numbers for specific signal combinations

### When to Load References
- **First use:** Load `investment-philosophy.md` for framework understanding
- **Allocation questions:** Load `market-analysis-guide.md` + `conviction_matrix.md`
- **Historical context:** Load `case-studies.md`
- **Regular execution:** References not needed — script handles scoring

---

## Relationship to Other Skills

| 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** | **Unified conviction** |

© tradermonty · MIT · tradermonty/claude-trading-skills

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