---
name: cryptocurrency-trader
description: Production-grade AI trading agent for cryptocurrency markets with advanced mathematical modeling, multi-layer validation, probabilistic analysis, and zero-hallucination tolerance. Implements Bayesian inference, Monte Carlo simulations, advanced risk metrics (VaR, CVaR, Sharpe), chart pattern recognition, and comprehensive cross-verification for real-world trading application.
---

# Cryptocurrency Trading Agent Skill

## Purpose

Provide production-grade cryptocurrency trading analysis with mathematical rigor, multi-layer validation, and comprehensive risk assessment. Designed for real-world trading application with zero-hallucination tolerance through 6-stage validation pipeline.

## When to Use This Skill

Use this skill when users request:
- Analysis of specific cryptocurrency trading pairs (e.g., BTC/USDT, ETH/USDT)
- Market scanning to find best trading opportunities
- Comprehensive risk assessment with probabilistic modeling
- Trading signals with advanced pattern recognition
- Professional risk metrics (VaR, CVaR, Sharpe, Sortino)
- Monte Carlo simulations for scenario analysis
- Bayesian probability calculations for signal confidence

## Core Capabilities

### Validation & Accuracy
- 6-stage validation pipeline with zero-hallucination tolerance
- Statistical anomaly detection (Z-score, IQR, Benford's Law)
- Cross-verification across multiple timeframes
- 14 circuit breakers to prevent invalid signals

### Analysis Methods
- Bayesian inference for probability calculations
- Monte Carlo simulations (10,000 scenarios)
- GARCH volatility forecasting
- Advanced chart pattern recognition
- Multi-timeframe consensus (15m, 1h, 4h)

### Risk Management
- Value at Risk (VaR) and Conditional VaR (CVaR)
- Risk-adjusted metrics (Sharpe, Sortino, Calmar)
- Kelly Criterion position sizing
- Automated stop-loss and take-profit calculation

**Detailed capabilities:** See `references/advanced-capabilities.md`

## Prerequisites

Ensure the following before using this skill:
1. Python 3.8+ environment available
2. Internet connection for real-time market data
3. Required packages installed: `pip install -r requirements.txt`
4. User's account balance known for position sizing

## How to Use This Skill

### Quick Start Commands

**Analyze a specific cryptocurrency:**
```bash
python skill.py analyze BTC/USDT --balance 10000
```

**Scan market for best opportunities:**
```bash
python skill.py scan --top 5 --balance 10000
```

**Interactive mode for exploration:**
```bash
python skill.py interactive --balance 10000
```

### Default Parameters

- **Balance:** If not specified by user, use `--balance 10000`
- **Timeframes:** 15m, 1h, 4h (automatically analyzed)
- **Risk per trade:** 2% of balance (enforced by default)
- **Minimum risk/reward:** 1.5:1 (validated by circuit breakers)

### Common Trading Pairs

Major: BTC/USDT, ETH/USDT, BNB/USDT, SOL/USDT, XRP/USDT
AI Tokens: RENDER/USDT, FET/USDT, AGIX/USDT
Layer 1: ADA/USDT, AVAX/USDT, DOT/USDT
Layer 2: MATIC/USDT, ARB/USDT, OP/USDT
DeFi: UNI/USDT, AAVE/USDT, LINK/USDT
Meme: DOGE/USDT, SHIB/USDT, PEPE/USDT

### Workflow

1. **Gather Information**
   - Ask user for trading pair (if analyzing specific symbol)
   - Ask for account balance (or use default $10,000)
   - Confirm user wants production-grade analysis

2. **Execute Analysis**
   - Run appropriate command (analyze, scan, or interactive)
   - Wait for comprehensive analysis to complete
   - System automatically validates through 6 stages

3. **Present Results**
   - Display trading signal (LONG/SHORT/NO_TRADE)
   - Show confidence level and execution readiness
   - Explain entry, stop-loss, and take-profit prices
   - Present risk metrics and position sizing
   - Highlight validation status (6/6 passed = execution ready)

4. **Interpret Output**
   - Reference `references/output-interpretation.md` for detailed guidance
   - Translate technical metrics into user-friendly language
   - Explain risk/reward in simple terms
   - Always include risk warnings

5. **Handle Edge Cases**
   - If execution_ready = NO: Explain validation failures
   - If confidence <40%: Recommend waiting for better opportunity
   - If circuit breakers triggered: Explain specific issue
   - If network errors: Suggest retry with exponential backoff

### Output Structure

**Trading Signal:**
- Action: LONG/SHORT/NO_TRADE
- Confidence: 0-95% (integer only, no false precision)
- Entry Price: Recommended entry point
- Stop Loss: Risk management exit (always required)
- Take Profit: Profit target
- Risk/Reward: Minimum 1.5:1 ratio

**Probabilistic Analysis:**
- Bayesian probabilities (bullish/bearish)
- Monte Carlo profit probability
- Signal strength (WEAK/MODERATE/STRONG)
- Pattern bias confirmation

**Risk Assessment:**
- VaR and CVaR (Value at Risk metrics)
- Sharpe/Sortino/Calmar ratios
- Max drawdown and win rate
- Profit factor

**Position Sizing:**
- Standard (2% risk rule) - recommended
- Kelly Conservative - mathematically optimal
- Kelly Aggressive - higher risk/reward
- Trading fees estimate

**Validation Status:**
- Stages passed (must be 6/6 for execution ready)
- Circuit breakers triggered (if any)
- Warnings and critical failures

**Detailed interpretation:** See `references/output-interpretation.md`

## Presenting Results to Users

### Language Guidelines

Use beginner-friendly explanations:
- "LONG" → "Buy now, sell higher later"
- "SHORT" → "Sell now, buy back cheaper later"
- "Stop Loss" → "Automatic exit to limit loss if wrong"
- "Confidence %" → "How certain we are (higher = better)"
- "Risk/Reward" → "For every $1 risked, potential $X profit"

### Required Risk Warnings

ALWAYS include these reminders:
- Markets are unpredictable - perfect analysis can still be wrong
- Start with small amounts to learn
- Never risk more than 2% per trade (enforced automatically)
- Always use stop losses
- This is analysis, NOT financial advice
- Past performance does NOT guarantee future results
- User is solely responsible for all trading decisions

### When NOT to Trade

Advise users to avoid trading when:
- Validation status <6/6 passed
- Execution Ready flag = NO
- Confidence <60% for moderate signals, <70% for strong
- User doesn't understand the analysis
- User can't afford potential loss
- High emotional stress or fatigue

## Advanced Usage

### Programmatic Integration

For custom workflows, import directly:
```python
from scripts.trading_agent_refactored import TradingAgent

agent = TradingAgent(balance=10000)
analysis = agent.comprehensive_analysis('BTC/USDT')
print(analysis['final_recommendation'])
```

See `example_usage.py` for 5 comprehensive examples.

### Configuration

Customize behavior via `config.yaml`:
- Validation strictness (strict vs normal mode)
- Risk parameters (max risk, position limits)
- Circuit breaker thresholds
- Timeframe preferences

### Testing

Verify installation and functionality:
```bash
# Run compatibility test
./test_claude_code_compat.sh

# Run comprehensive tests
python -m pytest tests/
```

## Reference Documentation

- `references/advanced-capabilities.md` - Detailed technical capabilities
- `references/output-interpretation.md` - Comprehensive output guide
- `references/optimization.md` - Trading optimization strategies
- `references/protocol.md` - Usage protocols and best practices
- `references/psychology.md` - Trading psychology principles
- `references/user-guide.md` - End-user documentation
- `references/technical-docs/` - Implementation details and bug reports

## Architecture

**Core Modules:**
- `scripts/trading_agent_refactored.py` - Main trading agent (production)
- `scripts/advanced_validation.py` - Multi-layer validation system
- `scripts/advanced_analytics.py` - Probabilistic modeling engine
- `scripts/pattern_recognition_refactored.py` - Chart pattern recognition
- `scripts/indicators/` - Technical indicator calculations
- `scripts/market/` - Data provider and market scanner
- `scripts/risk/` - Position sizing and risk management
- `scripts/signals/` - Signal generation and recommendation

**Entry Points:**
- `skill.py` - Command-line interface (recommended)
- `__main__.py` - Python module invocation
- `example_usage.py` - Programmatic usage examples

## Version

**v2.0.1 - Production Hardened Edition**

Recent improvements:
- Fixed critical bugs (division by zero, import paths, NaN handling)
- Enhanced network retry logic with exponential backoff
- Improved logging infrastructure
- Comprehensive input validation
- UTC timezone consistency
- Benford's Law threshold optimization

**Status:** 🟢 PRODUCTION READY

See `references/technical-docs/FIXES_APPLIED.md` for complete changelog.

## Troubleshooting

**Installation issues:**
```bash
pip install --upgrade pip
pip install -r requirements.txt
```

**Import errors:**
Ensure running from skill directory or using `skill.py` entry point.

**Network failures:**
System automatically retries with exponential backoff (3 attempts).

**Validation failures:**
Check validation report in output - explains which stage failed and why.

**For detailed debugging:**
Enable logging in `config.yaml` or check `references/technical-docs/BUG_ANALYSIS_REPORT.md`


---
Source attribution: kbarbel640-del
Original project: https://github.com/kbarbel640-del/skills/blob/e7e336ac628c3e3bd771aff1aaa469c93778f94a/skills/veeramanikandanr48/cryptocurrency-trader-skill/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 clawdbot

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: kbarbel640-del
Original project: https://github.com/kbarbel640-del/skills/blob/e7e336ac628c3e3bd771aff1aaa469c93778f94a/skills/veeramanikandanr48/cryptocurrency-trader-skill/SKILL.md
Attribution basis: Source repository record

Fields of work: Finance & Accounting, Marketing, Sales
Roles: Business Development, CFO / FP&A, Financial Analyst, Growth Marketer, Sales Engineer
Specialties: API
Tools: Python
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: c5d8d72635fdcaf39cc868db9d9cf1806b745bed51afa9be6117c9a3911e1836