{"enrichment":{"faq":[{"a":"Strategy Framework provides a standardized template for documenting trading strategies with precise, machine-testable rules. The template enforces discipline through structured sections covering edge hypotheses, entry/exit conditions, position sizing, risk guardrails, and performance thresholds. This enables reproducible backtesting and live trading validation by ensuring every strategy component is explicitly defined and testable before deployment.","q":"How do I create a trading strategy template with strategy-framework?"},{"a":"Strategy Framework requires you to document entry and exit conditions as explicit, machine-testable rules rather than vague guidelines. You specify the exact price levels, indicators, or market conditions that trigger entry, along with corresponding exit rules including stop-loss and take-profit thresholds. This precision enables automated backtesting and eliminates ambiguity during live trading execution.","q":"How can I define entry and exit rules for trading with this framework?"},{"a":"Strategy Framework establishes portfolio-level risk controls and position sizing rules as core components. You define position size based on account risk, volatility, or fixed percentages, then set guardrails for maximum drawdown, correlation limits, and aggregate exposure. These rules ensure disciplined capital allocation and prevent catastrophic losses across your strategy portfolio.","q":"What position sizing and risk management framework does strategy-framework offer?"},{"a":"Strategy Framework enables backtesting by enforcing documented entry/exit rules and position sizing that can be applied to historical data. Your strategy's testable rules feed directly into validation workflows, allowing you to measure performance metrics and walk-forward validation before live trading. This reproducible approach reveals curve-fitting risks and confirms edge validity.","q":"How do I backtest a trading strategy with historical data using this tool?"},{"a":"Strategy Framework implements a disciplined lifecycle: start with a testable hypothesis about market inefficiency, document entry/exit rules and risk controls, backtest against historical data, validate with paper trading, deploy to live trading with monitoring thresholds, and finally retire the strategy when performance degrades or market regime shifts. Each stage has defined gates and performance criteria.","q":"What is the strategy lifecycle from hypothesis to retirement in strategy-framework?"},{"a":"Strategy Framework enforces walk-forward validation and out-of-sample testing by structuring your strategy documentation upfront, before optimization. By separating hypothesis definition from parameter tuning, and requiring explicit performance thresholds, the framework discourages over-optimization to historical data. Strategy retirement rules also trigger when live performance diverges from backtest results, signaling regime change or overfitting.","q":"How does strategy-framework help me avoid curve fitting in backtesting?"}],"shadow_tags":["systematic-trading","backtesting-framework","risk-guardrails","signal-definition","strategy-lifecycle","performance-benchmarks","market-regimes","position-management","hypothesis-testing","trade-documentation"],"summary_rewrite":"Strategy Framework provides a standardized template for documenting trading strategies with precise, machine-testable rules. It enforces discipline through structured sections covering edge hypotheses, entry/exit conditions, position sizing, risk guardrails, and performance thresholds, enabling reproducible backtesting and live trading validation."},"files":[{"bytes":10454,"path":"skills/strategy-framework/SKILL.md","sha256":"04a8316fcceb99fb6d05af37da9fad7d5f9497e2c9610e4ff774e3db63ea2837","url":"https://skillfed.io/files/agiprolabs/claude-trading-skills/strategy-framework/fd227143/SKILL.md"}],"id":"agiprolabs/claude-trading-skills/strategy-framework","links":{"html":"https://skillfed.io/agiprolabs/claude-trading-skills/strategy-framework","md":"https://skillfed.io/agiprolabs/claude-trading-skills/strategy-framework.md","repo":"https://github.com/agiprolabs/claude-trading-skills"},"meta":{"agents_supported":[],"first_seen":"2026-07-28","forks":52,"language":"Python","last_updated":"2026-06-24","license":"MIT","name":"strategy-framework","publisher":"agiprolabs","stars":248},"relations":{"similar":[{"id":"robonet-tech/skills/test-trading-strategies"},{"id":"agiprolabs/claude-trading-skills/vectorbt"},{"id":"xbklairith/kisune/research"},{"id":"robonet-tech/skills/deploy-live-trading"},{"id":"kirkluokun/awesome-a-stock-openclawskills/data-\u56de\u6d4b\u6846\u67b6"},{"id":"gracefullight/stock-checker/backtesting-trading-strategies"},{"id":"Starchild-ai-agent/official-skills/backtest"},{"id":"robonet-tech/skills/browse-robonet-data"},{"id":"0xrikt/crypto-skills/crypto-backtest"},{"id":"okx/plugin-store/mainstream-spot-order"}]},"slug":{"owner":"agiprolabs","repo":"claude-trading-skills","skill":"strategy-framework"},"version":"fd227143"}