Skill detail
super-hedge-fund-skill
Comprehensive multi-agent stock investment analysis.
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SKILL.md
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---
name: super-hedge-fund-skill
description: Multi-agent stock analysis system with Claude-powered investor personas. Use when user mentions stock tickers (AAPL, TSLA, NVDA, GOOGL, MSFT), asks about stock analysis/investment decisions/trading signals, or uses keywords like stock analysis, investment decision, trading advice, hedge fund, bullish/bearish. Triggers on stock ticker symbols and investment-related questions.
---
# Super Hedge Fund Skill
Multi-agent stock analysis system combining rule-based analytics with Claude-powered investor personas.
**⚠️ Educational purposes only - NOT investment advice**
## Workflow
```dot
digraph workflow {
rankdir=TB;
node [shape=box, style="filled,rounded", fillcolor="#f0f0f0"];
input [label="1. Parse Input\nExtract tickers"];
data [label="2. Fetch Data\nPrice/Financials/News"];
agents [label="3. Run Agents\nRule + Claude"];
risk [label="4. Risk Analysis\nVolatility/Position"];
output [label="5. Generate Report\nMarkdown"];
input -> data -> agents -> risk -> output;
}
```
## Agents Quick Reference
| Agent | Type | Focus |
|-------|------|-------|
| Fundamental | Rule | ROE, margins, debt, growth |
| Technical | Rule | EMA, RSI, MACD, momentum |
| Valuation | Rule | DCF, Owner Earnings |
| Sentiment | Rule+Claude | News, insider trades |
| Buffett | Claude | Moat, ROE, intrinsic value |
| Wood | Claude | Disruptive tech, growth |
| Burry | Claude | Deep value, contrarian |
| Lynch | Claude | PEG, understandable biz |
## Execution
**Step 1: Parse Input**
```
Extract: ticker symbols, date range, capital
Mode: full (default) or brief
```
**Step 2: Fetch Data**
```
Use WebSearch for:
- Current price & 52-week range
- Financial metrics (ROE, P/E, margins, debt)
- Recent news headlines
```
**Step 3: Run Agents**
```
Rule-based (deterministic):
- Fundamental analysis → signal + confidence
- Technical analysis → signal + confidence
- Valuation analysis → signal + confidence
Claude-powered (interpretive):
- For each investor persona, analyze with their philosophy
- Return: {signal, confidence, reasoning}
```
**Step 4: Risk Analysis**
```
Calculate: annual volatility from price data
Determine: risk level → position limit
- Low (<15%): 25% max
- Medium (15-30%): 20% max
- High (30-50%): 15% max
- Very High (>50%): 10% max
```
**Step 5: Aggregate & Output**
```
Count signals: bullish / bearish / neutral
Determine consensus by majority
Generate Markdown report
```
## Signal Icons
| Signal | Icon |
|--------|------|
| Bullish | 🟢 |
| Bearish | 🔴 |
| Neutral | 🟡 |
## Common Mistakes
| Mistake | Fix |
|---------|-----|
| Giving real investment advice | Always add disclaimer |
| Missing data errors | Use fallback estimates |
| Single-agent reliance | Must aggregate 8+ signals |
| Overconfident signals | Show confidence %, acknowledge uncertainty |
## References
- `references/investor-agents.md` - Investor persona prompts and frameworks
- `references/analysis-methods.md` - Detailed scoring and calculation methods
- `assets/report-template.md` - Markdown report template
## Scripts
- `scripts/analysts.py` - Rule-based analyst implementations
- `scripts/investor_prompts.py` - Claude investor persona prompts
- `scripts/report_generator.py` - Markdown report generation
- `scripts/data_fetcher.py` - Data fetching utilities
Read the full source on GitHub (opens external page)