Stanley Druckenmiller Investment Agent Skill

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

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

The script will:

• Load and validate all upstream skill JSON reports
• Extract normalized signals from each skill
• Calculate 7 component scores (weighted 0-100)
• Compute composite conviction score
• Classify into one of 4 Druckenmiller patterns
• Generate target allocation and position sizing
• 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 |