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.
npx skills add tradermonty/claude-trading-skills --skill stanley-druckenmiller-investment -a claude-codeWhat 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-code2Manually: put the files in place
~/.claude/skills/stanley-druckenmiller-investment/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/stanley-druckenmiller-investment/
1Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill stanley-druckenmiller-investment -a codex2Manually: put the files in place
.agents/skills/stanley-druckenmiller-investment/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill stanley-druckenmiller-investment -a cursor2Manually: put the files in place
.cursor/skills/stanley-druckenmiller-investment/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install tradermonty/claude-trading-skills stanley-druckenmiller-investment2Manually: put the files in place
.github/skills/stanley-druckenmiller-investment/SKILL.md1Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill stanley-druckenmiller-investment -a gemini-cli2Platform CLI
gemini skills install https://github.com/tradermonty/claude-trading-skills --path skills/stanley-druckenmiller-investmentManually: put the files in place
.devin/skills/stanley-druckenmiller-investment/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill stanley-druckenmiller-investment -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
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