stanley-druckenmiller-investment

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---
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:**