CLAW Betting AI Advisory

AI-powered betting advisory system for gaming platforms like Stake.com. Provides intelligent recommendations based on historical data analysis, risk tolerance, and proven betting strategies.

Website: https://clawde.xyz

Features

Smart Bet Recommendations: AI-analyzed optimal bet amounts and timing
Crash Game Analysis: Historical pattern analysis for crash games
Risk Management: Dynamic stop-loss and take-profit suggestions
Bankroll Protection: Kelly Criterion and flat betting strategies
Multi-Strategy Support: Martingale, Anti-Martingale, Fibonacci, D'Alembert

Quick Start


# Install the skill
clawhub install claw-betting-ai

# Configure your settings
cp config/default.json config/local.json

# Edit config/local.json with your preferences

Supported Games

Game	Analysis Method
Crash	Historical crashpoint analysis, multiplier patterns
Dice	Probability optimization, streak detection
Limbo	Target multiplier recommendations
Slide	Pattern recognition

Files Included

claw-betting-ai/
├── SKILL.md              # This file
├── config/
│   └── default.json      # Default configuration
├── scripts/
│   ├── analyze.py        # Crash history analyzer
│   └── recommend.py      # Bet recommendation engine
└── examples/
    ├── basic-usage.md    # Getting started guide
    └── strategies.md     # Strategy documentation

Configuration

See config/default.json for all available options:

strategy: betting strategy (conservative/balanced/aggressive)
bankroll: starting bankroll amount
baseBetPercent: base bet as % of bankroll
stopLoss: stop-loss threshold
takeProfit: take-profit target
maxBets: maximum bets per session

Core Strategies

1. Conservative (Low Risk)

Target: 1.5x - 2x multipliers
Win rate: ~50-65%
Max 1% bankroll per bet

2. Balanced (Medium Risk)

Target: 2x - 5x multipliers
Win rate: ~25-45%
Max 2% bankroll per bet

3. Aggressive (High Risk)

Target: 5x - 20x multipliers
Win rate: ~5-15%
Max 5% bankroll per bet

API Reference

See examples/basic-usage.md for full API documentation.

Get Recommendation

from scripts.recommend import get_recommendation

result = get_recommendation(
    bankroll=100,
    strategy="balanced",
    recent_history=[1.2, 3.5, 1.8, 2.1, 5.2]
)

# Returns: { shouldBet: true, amount: 2.0, target: 2.5, confidence: 72 }

Safety Features

Tilt Detection: Warns when betting patterns indicate emotional decisions
Session Limits: Enforces time and loss limits
Profit Locking: Auto-protects portion of winnings
Reality Checks: Periodic reminders

Disclaimer

This is an advisory system only. Gambling involves risk of loss. Never bet more than you can afford to lose. Past patterns do not guarantee future results.

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