# 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 synth…

- **Type:** Skill
- **Install:** `agentstack add skill-xonevn-ai-xone-trading-skills-stanley-druckenmiller-investment`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [xonevn-ai](https://agentstack.voostack.com/s/xonevn-ai)
- **Installs:** 0
- **Category:** [Finance & Payments](https://agentstack.voostack.com/c/finance-and-payments)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [xonevn-ai](https://github.com/xonevn-ai)
- **Source:** https://github.com/xonevn-ai/xone-trading-skills/tree/main/skills/stanley-druckenmiller-investment
- **Website:** https://xone.vn

## Install

```sh
agentstack add skill-xonevn-ai-xone-trading-skills-stanley-druckenmiller-investment
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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

- 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)

---

## 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 (= 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** |

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [xonevn-ai](https://github.com/xonevn-ai)
- **Source:** [xonevn-ai/xone-trading-skills](https://github.com/xonevn-ai/xone-trading-skills)
- **License:** MIT
- **Homepage:** https://xone.vn

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-xonevn-ai-xone-trading-skills-stanley-druckenmiller-investment
- Seller: https://agentstack.voostack.com/s/xonevn-ai
- Browse the marketplace: https://agentstack.voostack.com/browse

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