mcpbeat

Stanley Druckenmiller Investment

baggat236/stanley-druckenmiller-investment

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".

37k tokens
context cost
the whole folder, loaded on every use
17
files
ships runnable scripts
1
copies elsewhere
how many repositories repackaged it
118
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/BaggaT236/AI-Trading-Skills --skill stanley-druckenmiller-investment

What comes with it

138 660 bytes besides the instruction
assets/strategy_report_template.md
references/case-studies.md
references/conviction_matrix.md
references/investment-philosophy.md
references/market-analysis-guide.md
scripts/allocation_engine.py
scripts/report_generator.py
scripts/report_loader.py
scripts/scorer.py
scripts/strategy_synthesizer.py
scripts/tests/conftest.py
scripts/tests/test_allocation_engine.py
scripts/tests/test_report_generator.py
scripts/tests/test_report_loader.py
scripts/tests/test_scorer.py
scripts/tests/test_strategy_synthesizer.py

The instruction itself

23 sections, as written by the author

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 |

Repackaged in 1 other repositories

same content, different owner
tradermonty/claude-trading-skills open on GitHub →

How to use it

Copy the folder

Take baggat236/stanley-druckenmiller-investment from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

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