browse-robonet-data

What this skill does

# Browse Robonet Data

## Quick Start

This skill provides fast, read-only access to explore Robonet's trading resources before building anything. All tools execute in under 1 second and cost little to nothing.

**Load the tools first**:
```
Use MCPSearch to select: mcp__workbench__get_all_symbols
Use MCPSearch to select: mcp__workbench__get_all_technical_indicators
Use MCPSearch to select: mcp__workbench__get_data_availability
```

**Common starting pattern**:
```
1. get_all_symbols → See available trading pairs (BTC-USDT, ETH-USDT, etc.)
2. get_all_technical_indicators → Browse 170+ indicators (RSI, MACD, Bollinger Bands)
3. get_data_availability → Check data ranges before backtesting
```

**When to use this skill**:
- Start every workflow by exploring available resources
- Check data availability before building strategies
- Review existing strategies and their performance
- Understand what ML predictions are available (Allora topics)
- Audit recent backtest results

## Available Tools (8)

### Strategy Exploration Tools

**`get_all_strategies`** - List your trading strategies with optional backtest results
- **Parameters**:
  - `include_latest_backtest` (optional, boolean): Include latest backtest summaries
- **Returns**: List of strategies with names, components, and optionally performance metrics
- **Pricing**: $0.001
- **Use when**: Finding existing strategies to review, enhance, or compare

**`get_strategy_code`** - View Python source code of a strategy
- **Parameters**:
  - `strategy_name` (required, string): Name of the strategy
- **Returns**: Complete Python source code
- **Pricing**: Free
- **Use when**: Learning from existing strategies, reviewing before modification, debugging

**`get_strategy_versions`** - Track strategy evolution across versions
- **Parameters**:
  - `base_strategy_name` (required, string): Base name without version suffixes
- **Returns**: List of all versions with creation dates and modification history
- **Pricing**: $0.001
- **Use when**: Understanding how a strategy evolved, comparing versions, auditing changes

### Market Data Tools

**`get_all_symbols`** - List tradeable pairs on Hyperliquid Perpetual
- **Parameters**:
  - `exchange` (optional, string): Filter by exchange name
  - `active_only` (optional, boolean): Only return active symbols (default: true)
- **Returns**: List of symbols with exchange, symbol name, active status, backfill status
- **Pricing**: $0.001
- **Use when**: Choosing which assets to trade, checking what's available before building strategies

**`get_data_availability`** - Check data ranges before backtesting
- **Parameters**:
  - `data_type` (optional, string): Type of data (crypto, polymarket, all)
  - `symbols` (optional, array): Specific crypto symbols to check
  - `exchange` (optional, string): Filter crypto by exchange
  - `asset` (optional, string): Filter Polymarket by asset
  - `include_resolved` (optional, boolean): Include resolved Polymarket markets
  - `only_with_data` (optional, boolean): Only show items with available data
- **Returns**: Data availability with date ranges, candle counts, backfill status
- **Pricing**: $0.001
- **Use when**: Before backtesting (verify sufficient data), choosing test date ranges, checking market coverage

### Indicator & ML Tools

**`get_all_technical_indicators`** - Browse 170+ indicators available in Jesse framework
- **Parameters**:
  - `category` (optional, string): Filter by category (momentum, trend, volatility, volume, overlap, oscillators, cycle, all)
- **Returns**: List of indicators with names, categories, and parameters
- **Pricing**: $0.001
- **Use when**: Exploring indicators for strategy ideas, checking parameter requirements, learning what's available

**`get_allora_topics`** - List Allora Network ML prediction topics
- **Parameters**: None
- **Returns**: List of topics with asset names, network IDs, prediction horizons, and prediction types
- **Pricing**: $0.001
- **Use when**: Planning ML enhancement, checking prediction coverage, understanding available horizons (5m, 8h, 24h, 1 week)

### Backtest Results Tool

**`get_latest_backtest_results`** - View recent backtest performance
- **Parameters**:
  - `strategy_name` (optional, string): Filter by strategy name
  - `limit` (optional, integer, 1-100): Number of results (default: 10)
  - `include_equity_curve` (optional, boolean): Include equity curve timeseries
  - `equity_curve_max_points` (optional, integer, 50-1000): Maximum points for equity curve
- **Returns**: List of backtest records with metrics (Sharpe, drawdown, win rate, total return, profit factor)
- **Pricing**: Free
- **Use when**: Checking if backtest already exists, comparing strategy performance, avoiding redundant backtests

## Core Concepts

### Symbol Coverage

**Crypto Perpetuals** (Hyperliquid):
- **Major pairs**: BTC-USDT, ETH-USDT, SOL-USDT, NEAR-USDT
- **Data history**: BTC-USDT and ETH-USDT have longest history (2020-present)
- **Typical range**: Most symbols have 6-24 months of data
- **Data quality**: 1-minute candles available for all symbols

**Best practices**:
- Use `get_all_symbols` to see complete list
- Check `get_data_availability` for specific symbol history
- BTC-USDT and ETH-USDT recommended for initial strategy development (longest history)

### Technical Indicators

**170+ indicators organized by category**:

- **Momentum** (16 indicators): RSI, MACD, Stochastic, ADX, CCI, MFI, ROC, Williams %R, Ultimate Oscillator, etc.
- **Trend** (12 indicators): EMA, SMA, DEMA, TEMA, WMA, Supertrend, Parabolic SAR, VWAP, HMA, etc.
- **Volatility** (8 indicators): Bollinger Bands, ATR, Keltner Channels, Donchian Channels, Standard Deviation, etc.
- **Volume** (10 indicators): OBV, Volume Profile, Chaikin Money Flow, Volume Weighted indicators, etc.
- **Overlap** (8 indicators): Various moving averages and envelopes
- **Oscillators** (6 indicators): Specialized momentum oscillators
- **Cycle** (4 indicators): Market cycle detection indicators

**How to use**:
```
1. get_all_technical_indicators(category="momentum") → Browse momentum indicators
2. Pick indicators for your strategy concept
3. Reference indicators in strategy description when building
```

**Note**: All indicators are from the Jesse framework (`jesse.indicators`). Use exact names when creating strategies.

### Allora Network ML Predictions

**Prediction Coverage**:
- **Assets**: BTC, ETH, SOL, NEAR
- **Horizons**: 5 minutes, 8 hours, 24 hours, 1 week
- **Prediction types**:
  - Log return (percentage change prediction)
  - Absolute price (future price prediction)
- **Networks**:
  - Mainnet: 10 production topics
  - Testnet: 26 experimental topics

**Topic structure**:
```
Asset: BTC
Horizon: 24h
Type: Log return
Network: mainnet
```

**How to use**:
```
1. get_allora_topics() → See all available predictions
2. Match prediction horizon to your strategy timeframe
3. Use enhance_with_allora (from improve-trading-strategies skill) to integrate predictions
```

**Best practices**:
- Match prediction horizon to strategy timeframe (don't use 5m predictions for daily strategy)
- Mainnet topics are production-ready, testnet topics are experimental
- Check topic availability before planning ML enhancement

### Backtest Result Interpretation

**Key Metrics**:

**Sharpe Ratio** (risk-adjusted return):
- **>2.0**: Excellent performance
- **1.0-2.0**: Good performance
- **0.5-1.0**: Acceptable performance
- **<0.5**: Poor performance

**Max Drawdown** (largest peak-to-trough decline):
- **<10%**: Conservative risk profile
- **10-20%**: Moderate risk profile
- **20-40%**: Aggressive risk profile
- **>40%**: Very risky (reconsider strategy)

**Win Rate** (percentage of profitable trades):
- **45-65%**: Realistic for most strategies
- **>70%**: Suspicious (possible overfitting or unrealistic fills)
- **<40%**: Needs improvement

**Profit Factor** (gross profit / gross loss):
- **>2.0**: Excellent
- **1.5-2.0**: Good
- **1.2-1.5**: Acceptable
- **<1.2*