robonet-tech
- 7 skills
- 0 followers
- 22 hours ago last updated
- ▌ Robonet Workbench · robonet-techUse Robonet's MCP server to build, backtest, optimize, and deploy trading strategies. Provides 24 specialized tools for crypto and prediction market trading: (1) Data tools for browsing strategies, symbols, indicators, Allora topics, and backtest results, (2) AI tools for generating strategy ideas and code, optimizing parameters, and enhancing with ML predictions, (3) Backtesting tools for testing strategy performance on historical data, (4) Prediction market tools for Polymarket trading strategies, (5) Deployment tools for live trading on Hyperliquid, (6) Account tools for credit management. Use when: building trading strategies, backtesting strategies, deploying trading bots, working with Hyperliquid or Polymarket, or enhancing strategies with Allora Network ML predictions.
- ▌ Browse Robonet Data · robonet-techFast, low-cost exploration of Robonet trading resources. Browse 8 data tools to explore available trading pairs, technical indicators, Allora ML topics, existing strategies, and backtest results. All tools execute in <1 second with minimal cost (free to $0.001). Use this skill first before building or testing strategies to understand what resources are available.
- ▌ Deploy Live Trading · robonet-techDeploy and manage live trading agents on Hyperliquid. ⚠️ HIGH RISK - REAL CAPITAL AT STAKE ⚠️ Provides deployment_create (launch agent, $0.50), deployment_list (monitor), deployment_start/stop (control), and account tools (credit management). Supports EOA (1 deployment max) and Hyperliquid Vault (200+ USDC required, unlimited deployments). CRITICAL: NEVER deploy without thorough backtesting (6+ months, Sharpe >1.0, drawdown <20%). Start small, monitor daily, define exit criteria before deploying.
- ▌ Test Trading Strategies · robonet-techBacktest trading strategies on historical data and interpret performance metrics. Provides run_backtest (crypto strategies) and run_prediction_market_backtest (Polymarket strategies). Fast execution (20-60s), minimal cost ($0.001). Returns Sharpe ratio, max drawdown, win rate, profit factor, and trade statistics. Use this skill after building or improving strategies to validate performance before deploying. NEVER deploy without thorough backtesting (6+ months recommended).
- ▌ Build Trading Strategies · robonet-techAI-powered generation of complete trading strategy code. Uses create_strategy and create_prediction_market_strategy to transform requirements into production-ready Python code. Most expensive AI tool ($1.00-$4.50 per generation). Generates complete Jesse framework strategies with entry/exit logic, position sizing, and risk management. Use after exploring data and optionally generating ideas. ALWAYS test with test-trading-strategies before deploying.
- ▌ Design Trading Strategies · robonet-techAI-powered strategy ideation and concept exploration. Generate 1-10 creative trading strategy concepts based on current market data using the generate_ideas tool. Cheapest AI operation ($0.05-$1.00 vs $1-$4.50 for full strategy creation). Use this skill to explore creative concepts before committing to expensive development. Best for: exploring new markets, brainstorming approaches, validating ideas before building.
- ▌ Improve Trading Strategies · robonet-techIterative refinement, parameter optimization, and ML enhancement of existing trading strategies. Provides 3 tools: refine_strategy (targeted code changes, $0.50-$3.00), optimize_strategy (parameter tuning, $2-$4), enhance_with_allora (ML integration, $1-$2.50). More cost-effective than regenerating from scratch. Use when you have working strategies that need improvement. Always test improvements with test-trading-strategies before deploying.